Process flow management method and management platform

Abstract

The present application provides a process flow management method. The method uses flow information of a service and service data reported by a service device executing the service to automatically generate a process flow, so as to obtain the execution order of a plurality of processes in the service. When the process flow is generated, an initial process identifier and a process end condition of an initial process in the process information can be used for constraining an initial process and an end process in the process flow to be generated. When the process flow is generated, the process flow can be automatically generated only by acquiring the process information and the service data of the service. Also disclosed is a process flow management platform.

Description

A process management method and management platform

[0001] This application claims priority to the Chinese patent application filed with the State Intellectual Property Office of China on February 9, 2024, with application number 202410179026.0 and application name “A process flow management method, device and system based on Internet of Things technology”, all of which are incorporated by reference into this application; and this application claims priority to the Chinese patent application filed with the State Intellectual Property Office of China on April 26, 2024, with application number 202410516440.6 and application name “A process flow management method and management platform”, all of which are incorporated by reference into this application. Technical Field

[0002] The present application relates to the field of data processing technology, and in particular to a process flow management method and management platform. Background Art

[0003] Currently, in the manufacturing industry, especially in the batch manufacturing industry, there are a series of production processes. In order to better manage the production process, it is often necessary to configure and visualize the production process. When the process flow changes, the process flow needs to be redrawn.

[0004] However, current solutions for mapping process flows are inefficient and have low accuracy.

[0005] Summary of the Invention

[0006] This application provides a process flow management method and management platform, which can automatically generate process flows based on the process information of the business executed by the business equipment and the business data generated during the operation of the business equipment, so as to improve the efficiency and accuracy of the process flow generation.

[0007] In one possible embodiment, the present application provides a process flow management method. The method is applied to a management platform, the management platform runs on a management device, the management platform is connected to a business device, the business device is used to execute a business, and the business includes multiple processes. The method includes: obtaining process information of the business, the process information including a starting process identifier and a process end condition of a starting process in the multiple processes; receiving multiple business data sent by the business device during operation, each of the multiple business data including a process identifier of a process in the multiple processes; based on the multiple business data and the process information, generating a process flow, the process flow including the execution order between the multiple processes.

[0008] The multiple processes may be all or part of the processes of a business. Thus, the process flow generated by this application may be the execution order between all or part of the processes of the business.

[0009] The business device is a device for executing a business, and the business device may be different in different application scenarios.

[0010] Taking the beer production scenario as an example, this business device can be used to execute the beer production business. The beer production business can include multiple processes, and the business device can include multiple sub-business devices corresponding to different processes. Each process can be executed by a corresponding sub-business device. For example, these processes may include but are not limited to: crushing, gelatinization, filtration, boiling, etc. The corresponding sub-business devices can be crushing equipment, gelatinization equipment, filtration equipment, boiling equipment, etc.

[0011] In some scenarios, the business device may be the entire management system for executing beer production, and the management platform 400 may receive business data reported by the management system for executing beer production.

[0012] In other scenarios, the management platform may receive business data of respective processes reported by sub-business equipment corresponding to different processes.

[0013] The management platform of this application can be a cloud management platform running in the cloud (such as an Internet of Things platform), or a management platform running on an edge device, or a management platform running on other physical devices under the cloud. There is no restriction here. In other words, the management device can be a cloud, such as a public cloud, or an edge device, or other physical device.

[0014] The plurality of business data may be generated by business equipment or collected by business equipment, which is not limited here.

[0015] In related technologies, the configuration and visualization of production processes through drawing tools to draw process flows is time-consuming and has low accuracy. Moreover, when the process flows change, it is difficult to optimize and adjust the process flows in a timely manner, resulting in poor real-time performance of the drawn process flows.

[0016] To this end, the present application provides the aforementioned process flow management method, which can automatically generate a process flow using the process information of the business and the business data reported by the business equipment when executing the business, so as to obtain the execution order between multiple processes during the business execution process. The business data is the business data generated by the business equipment during operation, which is real-time. Using real-time business data, the process flow can be automatically generated in real time. When the process changes, the generated process flow can change accordingly. This makes the process flow generated by the method of the present application highly real-time and can be dynamically generated based on the received business data. In addition, when generating the process flow, the starting process identifier and process end condition of the starting process in the process information can be used to constrain the starting process and ending process in the process flow to be generated, thereby improving the accuracy of the process flow of the present application. In addition, when generating the process flow, only the process information of the business and the business data need to be obtained to automatically generate the process flow. Compared with configuring and visualizing the production process through drawing tools to draw the process flow, the efficiency of generating the process flow can be greatly improved and the difficulty of drawing the process flow can be reduced.

[0017] In one possible embodiment, generating a process flow based on the multiple business data and the process information includes: determining target business data in the multiple business data that matches the process information based on the multiple business data and the process information, wherein the target business data includes first business data whose process identifier matches the starting process identifier, and second business data received after the first business data and that meets the process end condition; generating a process flow based on the target business data, wherein the starting process of the process flow is the first process indicated by the first process identifier in the first business data, and the ending process of the process flow is the second process indicated by the second process identifier in the second business data.

[0018] The process information may include a starting process identifier and a process end condition, so that the process information can be used to constrain the target business data of the process flow to be generated, wherein the target business data may include first business data and second business data. Specifically, the method of this embodiment can use the starting process identifier to find the first business data whose process identifier is the starting process identifier in the received business data. For example, the first business data can be used as the business data of the starting process in the process flow; and the method can also use the process constraint condition to find the second business data that meets the process end condition in the received business data. For example, the second business data can be used as the business data of the terminating process in the process flow. In this way, the business data of the starting process and the terminating process in the process flow have been determined, so that it is convenient to use the target business data to generate an accurate process flow, so as to improve the accuracy of the process flow, such as the accuracy of the starting process and the terminating process.

[0019] In a possible embodiment, the multiple business data include third business data, wherein the third business data is business data received between the first business data and the second business data; generating a process flow based on the target business data includes: determining the receiving time sequence of the first business data, the second business data, and the third business data based on the target business data and the third business data; generating a process flow based on the receiving time sequence, wherein the starting process of the process flow is the first process indicated by the first process identifier in the first business data, the ending process of the process flow is the second process indicated by the second process identifier in the second business data, and the intermediate process of the process flow is the third process indicated by the third process identifier in the third business data.

[0020] In an embodiment of the present application, the method can use the above-mentioned process information to not only determine the first business data and the second business data, but also determine the third business data whose reception time is between the reception time of the first business data and the reception time of the second business data; then, the order between the processes indicated by the process identifiers of the above-mentioned first business data, second business data and third business data can be determined according to the order of reception time, so as to generate a process flow based on the order, for example, the process flow can be the execution order between the processes indicated by the process identifiers. In an embodiment of the present application, the starting process and the ending process in the process flow can be found by using the starting process identifier and the process end condition in the process information, and the business data of the intermediate process between the starting process and the ending process can be found based on the order of reception time of the business data, wherein the reception time of the above-mentioned second business data is later than the reception time of the above-mentioned first business data. This allows the present application to efficiently generate an accurate process flow according to the timing of the business data.

[0021] In a possible embodiment, each of the multiple business data also includes the process execution time of a process among the multiple processes, and the multiple business data also include third business data, wherein the process execution time of the third process indicated by the third process identifier in the third business data is between the process execution time of the first process indicated by the first process identifier in the first business data and the process execution time of the second process indicated by the second process identifier in the second business data; generating a process flow based on the target business data includes: determining the order of the process execution times of the received first business data, the second business data, and the third business data based on the target business data and the third business data; generating a process flow based on the order of the process execution times, wherein the starting process of the process flow is the first process indicated by the first process identifier, the ending process of the process flow is the second process indicated by the second process identifier, and the intermediate process of the process flow is the third process indicated by the third process identifier.

[0022] Among them, the business data generated by the business equipment during operation and received by the management platform of the present application may not only include the process identification, but also the process execution time, which is the time when the process occurs, such as the process start time, the process end time, any time during the process execution, etc.

[0023] In an embodiment of the present application, the method can use the above-mentioned process information to not only determine the first business data and the second business data, but also determine the third business data whose process execution time is between the process execution time of the first business data and the process execution time of the second business data; then, the order between the processes indicated by the process identifiers of the above-mentioned first business data, second business data and third business data can be determined according to the order of the process execution time, so as to generate a process flow based on the order, for example, the process flow can be a logical order between the processes indicated by the process identifiers. In an embodiment of the present application, the starting process and the ending process in the process flow can be found by using the starting process identifier and the process ending condition in the process information, and the business data of the intermediate process between the starting process and the ending process can also be found based on the order of the process execution time of the business data, wherein the process execution time of the above-mentioned second business data is later than the process execution time of the above-mentioned first business data. This allows the present application to accurately generate a process flow according to the order of the execution time of the processes.

[0024] In this embodiment, considering that the process execution times of multiple processes of a business are relatively close, the business data of the later executed process may be received by the management platform before the business data of the earlier executed process, resulting in the order of the reception time of the business data received by the management platform from early to late cannot accurately reflect the execution order between different processes. Therefore, in order to improve the accuracy of the process flow, the above-mentioned second logical order can be determined according to the order of the process execution time from early to late to generate an accurate process flow, so as to avoid the problem of process errors caused by only referring to the order of the reception time of the business data to generate the logical order between processes, thereby ensuring the accuracy of the logical order between nodes in the generated process flow.

[0025] In a possible implementation, the process flow further includes the process execution time of each of the multiple processes.

[0026] In the embodiment of the present application, the generated process flow may include the process execution time of each of the above-mentioned multiple processes. In this way, even if there are certain errors in the logical order of the processes in the generated process flow in some scenarios, since each process in the process flow can also display or carry information about the process execution time, the client can determine whether the automatically generated process flow is accurate by tracing the process execution time, and if there are errors in the process flow, adjust the logical order of the processes with errors.

[0027] In one possible embodiment, the process end condition includes the process flow duration, and the determination of the target business data among the multiple business data that matches the process information includes: when the timing duration reaches the process flow duration, the business data other than the first business data that is received most recently or has the latest process execution time is determined as the second business data that meets the process end condition; wherein the timing duration is the timing duration starting from the first moment, wherein the first moment is the moment of determining the first business data.

[0028] In this embodiment, the process end condition may include the process flow duration, which may be the maximum time for the business equipment to execute the business once estimated based on prior knowledge, such as the maximum time for the beer production business to complete a beer production process, such as 24 hours.

[0029] In a specific implementation, the management platform may start timing at the moment the first business data is determined. This moment may be the moment the first business data is received, or the moment a business data is determined to be the first business data based on a starting process identifier in the process information, without limitation. Furthermore, the timing may be a countdown according to, for example, 24 hours, or may start counting forward from zero. For example, in a scenario where the timing starts from zero in the positive direction, when the timing reaches 24 hours (or in a countdown scenario, when the countdown from 24 hours is zero), in one scenario, when the first logical order is determined in the order of the receiving time from early to late in the above embodiment, the business data received most recently except the first business data can be determined as the second business data that meets the process end condition, thereby finding the termination process in the process flow (the process corresponding to the second business data); in another scenario, when the second logical order is determined in the order of the process execution time from early to late in the above embodiment, the business data received most recently except the first business data with the latest process execution time can be determined as the second business data that meets the process end condition, thereby finding the termination process in the process flow (the process corresponding to the second business data).

[0030] In an embodiment of the present application, the starting process in the process flow can be found by means of the process identifier of the starting process in the process information, and the business data of the terminating process can be found in the received business data by means of the process flow duration in the process information, and the logical order of the starting process and the terminating process and the intermediate processes therebetween can be determined by using the reception time or process execution time, so as to generate the process flow. In this way, the process flow generated by the present application can generate the terminating process in the process flow according to the pre-configured process flow duration. In this way, in the case where the business data whose process identifier matches the process identifier of the terminating process in the process information has not been received, the reliable generation of the process flow can also be ensured. In addition, in the case where the business data whose process identifier matches the process identifier of the starting process in the process information has not been received again, the reliable generation of the process flow can also be ensured.

[0031] In a possible implementation, the process end condition includes a termination process identifier, and determining target business data matching the process information among the multiple business data includes: determining second business data whose process identifier matches the termination process identifier.

[0032] The present application can use the process identifier of the starting process in the process information to find the business data corresponding to the first node in the process flow to be generated, and can also use the process identifier of the terminating process in the process information to find the business data corresponding to the last node in the process flow to be generated, and use the above two process identifiers in the process information to find the business data of the process (also called the intermediate process) whose receiving time or process execution time is between the starting process and the terminating process, and use the receiving time or process execution time to determine the logical order between the intermediate processes for generating the process flow, so that the starting process and the terminating process of the generated process flow meet the actual situation during the business execution process, thereby ensuring the accuracy of the process flow of the present application.

[0033] In a possible embodiment, the process information also includes the number of process iterations N, where N≥2 and N is an integer. Generating a process flow based on the target business data also includes: generating M process flows based on the target business data and the process information, where 1≤M≤N and M is an integer; and merging nodes with the same execution order between the M process flows to obtain an iterative process flow.

[0034] Among them, when the management platform uses the starting process identifier and process end condition in the process information to generate a process flow (for example, process A->process B->process C->process D), an iteration is completed. The number of process iterations N is at least two times, for example, N=3. Then, after completing one iteration, N can be subtracted by 1, so that N is updated to 2; then, for the business data received after the business data of process D, the above process information is continued to be used to determine the target business data for generating the second process flow. Of course, the process logic order of different process flows may be the same. Therefore, after iterating N times according to the above process iteration number N, the number of process flows generated is at most N, but there may be repeated process flows, so M process flows are finally generated, 1≤M≤N. For example, the process flow generated by the second iteration is process A->process B->process E->process D, and then N is reduced by one again, and N is updated to 1; for the business data received after the business data of process D received for the second time, the above process information is continued to be used to determine the target business data to generate the third process flow. For example, the process flow generated by the third iteration is process A->process B->process F->process D, and then N is reduced by one again, and N is updated to 0. There is no need to perform the next iteration on the received business data to generate the process flow.

[0035] After completing N iterations, or during N iterations, M process flows can be merged. In this example, there are processes with the same execution order in the three process flows, specifically process A->process B. Therefore, the logic of the three processes A->process B in the three process flows is merged into one process A->process B. However, the path from process B to process D in the above three process flows can start from process B and reach process D through any one of process C, process E, and process F. Therefore, the three parallel paths from process B to process C, process E, and process F can be retained, and then process C, process E, and process F can be used to reach process D to obtain a merged process flow.

[0036] The combined process flow is:

[0037] In this way, considering that in the same business (such as beer production business), the process flow of the beer production business may be different in scenarios such as different product (such as beer) quality or different product production periods, in order to obtain a complete and accurate process flow, this application can cyclically execute the generation of multiple process flows according to the number of process iterations, and repeatedly merge the generated multiple process flows in a logical order to improve the accuracy of the process flow.

[0038] In a possible implementation, the business data further includes process parameters, and the process flow further includes the process parameters of each of the multiple processes.

[0039] In an embodiment of the present application, business data may include not only process identification, but also process parameters, and in the generated process flow, for example, the process parameters of each process may be displayed, so that the process parameters of the process can be accurately bound to the corresponding nodes in the process flow, to facilitate maintenance personnel to perform data analysis and maintenance.

[0040] In a possible implementation, the process parameters include at least one of the following: process measurement data, production batch, and production line.

[0041] For example, in the beer production business, the measured data for the grinding process might be fineness. Beer production can be divided into different production batches, production lines, and production plans. Therefore, the grinding process parameters might include information about the production batch, production line, and production plan. This allows the client to access the management platform through the user interface to determine which production plan, production line, and batch the generated process flow represents.

[0042] In one possible embodiment, the present application provides a management platform, which runs on a management device, and the management platform is connected to a business device, and the business device is used to execute business, and the business includes multiple processes. The management platform includes: an acquisition module, which is used to obtain process information of the business, and the process information includes a starting process identifier and a process end condition of a starting process among the multiple processes; a receiving module, which is used to receive multiple business data sent by the business device during operation, and each business data in the multiple business data includes a process identifier of a process among the multiple processes; a generation module, which is used to generate a process flow based on the multiple business data and the process information, and the process flow includes the execution order between the multiple processes.

[0043] In a possible implementation, the management platform is a cloud management platform, which is used to manage the infrastructure for providing cloud services. The infrastructure includes multiple cloud data centers located in different regions, with at least one cloud data center located in each region.

[0044] In one possible embodiment, the generation module is specifically used to: determine, based on the business data and the process information, target business data among the multiple business data that matches the process information, wherein the target business data includes first business data whose process identifier matches the starting process identifier, and second business data received after the first business data and that meets the process end condition; generate a process flow based on the target business data, wherein the starting process of the process flow is the first process indicated by the first process identifier in the first business data, and the ending process of the process flow is the second process indicated by the second process identifier in the second business data.

[0045] In a possible embodiment, the multiple business data include third business data, wherein the third business data is business data received between the first business data and the second business data; the generation module is specifically used to: determine the reception time sequence of the first business data, the second business data, and the third business data based on the target business data and the third business data; based on the reception time sequence, generate a process flow, wherein the starting process of the process flow is the first process indicated by the first process identifier in the first business data, the ending process of the process flow is the second process indicated by the second process identifier in the second business data, and the intermediate process of the process flow is the third process indicated by the third process identifier in the third business data.

[0046] In a possible embodiment, each of the multiple business data also includes the process execution time of a process among the multiple processes, and the multiple business data also include third business data, wherein the process execution time of the third process indicated by the third process identifier in the third business data is between the process execution time of the first process indicated by the first process identifier in the first business data and the process execution time of the second process indicated by the second process identifier in the second business data; the generation module is specifically used to: determine the order of the process execution times of the received first business data, the second business data, and the third business data based on the target business data and the third business data; generate a process flow based on the order of the process execution times, wherein the starting process of the process flow is the first process indicated by the first process identifier, the ending process of the process flow is the second process indicated by the second process identifier, and the intermediate process of the process flow is the third process indicated by the third process identifier.

[0047] In a possible implementation, the process flow further includes the process execution time of each of the multiple processes.

[0048] In one possible embodiment, the process end condition includes the process flow duration, and the generation module is specifically used to: when the timing duration reaches the process flow duration, the business data other than the first business data that is received most recently or has the latest process execution time received most recently is determined as the second business data that meets the process end condition; wherein, the timing duration is the timing duration starting from the first moment, wherein the first moment is the moment of determining the first business data.

[0049] In a possible implementation, the process end condition includes a process termination identifier, and the generation module is specifically configured to determine the second business data whose process identifier matches the process termination identifier.

[0050] In a possible embodiment, the process information also includes the number of process iterations N, where N≥2 and N is an integer. The generation module is specifically used to: generate M process flows based on the target business data and the process information, where 1≤M≤N and M is an integer; and merge nodes with the same execution order between the M process flows to obtain an iterative process flow.

[0051] In a possible implementation, the business data further includes process parameters, and the process flow further includes the process parameters of each of the multiple processes.

[0052] In a possible implementation, the process parameters include at least one of the following: process measurement data, production batch, and production line.

[0053] The effects of the management platforms of the above-mentioned embodiments are similar to the effects of the process flow management methods of the above-mentioned embodiments, and will not be repeated here.

[0054] In one possible implementation, the present application provides a management device cluster, including at least one management device, each management device connected to a service device, the service device configured to execute a service, the service including multiple processes, and each management device including a processor and a memory. The processor of at least one management device is configured to execute instructions stored in the memory of the at least one management device, so that the management device cluster executes the process flow management method of any of the possible implementations described above.

[0055] The effect of managing the equipment cluster in this embodiment is similar to the effect of the process flow management method in the above embodiments, and will not be repeated here.

[0056] In one possible embodiment, the present application provides a computer program product comprising instructions, which, when executed by a managed device cluster, enables the managed device cluster to execute the process flow management method in any of the above possible embodiments, wherein the management device cluster is connected to a business device, the business device is used to execute a business, and the business includes multiple processes.

[0057] The effects of the computer program product of this embodiment are similar to the effects of the process flow management methods in the above embodiments, and will not be repeated here.

[0058] In one possible embodiment, the present application provides a computer-readable storage medium comprising computer program instructions. When the computer program instructions are executed by a management device cluster, the management device cluster executes the process flow management method in any one of the above embodiments, wherein the management device cluster is connected to a business device, the business device is used to execute a business, and the business includes multiple processes.

[0059] The effect of the computer-readable storage medium of this embodiment is similar to the effect of the process flow management method in the above embodiments, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] FIG1a is a schematic flow chart of an exemplary process flow management method;

[0061] FIG1b is a schematic diagram of an exemplary system architecture;

[0062] FIG1c is a schematic diagram of an exemplary system architecture;

[0063] FIG2 is a schematic diagram illustrating an exemplary process flow management method;

[0064] FIG3a is a schematic diagram showing an exemplary scenario;

[0065] FIG3 b is a schematic diagram showing an exemplary scenario;

[0066] FIG4a is a schematic diagram showing an exemplary scenario;

[0067] FIG4b is a schematic diagram showing an exemplary scenario;

[0068] FIG4c is a schematic diagram showing an exemplary scenario;

[0069] FIG4d is a schematic diagram showing an exemplary scenario;

[0070] FIG4e is a schematic diagram showing an exemplary scenario;

[0071] FIG4f is a schematic diagram showing an exemplary scenario;

[0072] FIG4g is a schematic diagram showing an exemplary scenario;

[0073] FIG4h is a schematic diagram illustrating an exemplary process flow;

[0074] FIG5 is a schematic diagram illustrating an exemplary beer production process;

[0075] FIG6 is a schematic diagram illustrating an exemplary process flow;

[0076] FIG7 is a schematic diagram showing the structure of an exemplary management platform;

[0077] FIG8 is a schematic diagram showing the structure of an exemplary management device;

[0078] FIG9 is a schematic diagram showing the structure of an exemplary management device;

[0079] FIG10 is a schematic diagram showing the structure of an exemplary management device cluster;

[0080] FIG. 11 is a schematic diagram showing the structure of an exemplary management device cluster. DETAILED DESCRIPTION

[0081] The following is a clear and complete description of the technical solutions in the embodiments of the present application in conjunction with the accompanying drawings. Obviously, the embodiments described are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0082] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0083] References to "one embodiment" or "some embodiments" in this specification mean that a particular feature, structure, or characteristic described in conjunction with that embodiment is included in one or more embodiments of the present application. Thus, phrases such as "in one embodiment," "in some embodiments," "in other embodiments," and "in yet other embodiments" appearing in various places in this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "including," "comprising," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0084] Before describing the technical solutions of the embodiments of the present application, a brief introduction to the background technologies and technical terms involved in the embodiments of the present application is first given:

[0085] A public cloud is a cloud platform provided by a third-party public cloud provider to individuals and businesses. In a public cloud, the hardware, software, and other infrastructure are all owned and managed by the third-party public cloud provider.

[0086] A private cloud is a dedicated cloud platform provided for a business or organization. A private cloud can be operated internally by that business or organization. It's primarily targeted at enterprise users and is also known as an enterprise cloud.

[0087] A hybrid cloud is a cloud platform formed by different cloud platforms. A hybrid cloud includes at least two cloud platforms, also known as a multi-cloud platform or multi-cloud. Alternatively, a hybrid cloud combines public and private clouds. For security reasons, some enterprises prefer to store data in private clouds while still seeking access to public cloud computing resources. In this context, hybrid clouds, which combine public and private clouds, are increasingly being adopted. Hybrid clouds combine and match public and private clouds to achieve optimal results.

[0088] The cloud involved in the embodiments of this application is described using a public cloud as an example. In other embodiments, it may also be a private cloud and / or a hybrid cloud, and this application does not limit this. In other words, the process flow management method described in the embodiments of this application below can also be applied to a private cloud or a hybrid cloud, and this application does not limit this.

[0089] The Internet of Things platform is a software system that provides cloud technology (also known as cloud computing technology) services provided by a cloud provider, and is used to manage the infrastructure that provides cloud services. Specifically, the Internet of Things platform provides an interface related to cloud services for tenants to remotely access cloud services. Tenants can log in to the Internet of Things platform on the cloud service access page using a pre-registered account and password, and after a successful login, select and purchase the corresponding cloud service on the cloud service access page. In an embodiment of the present application, a tenant includes at least one user. A tenant has a main account, and a user has a sub-account. In an embodiment of the present application, tenants and users can be replaced arbitrarily, and will not be repeated below.

[0090] Cloud services include computing services, storage services, virtual machine services, network services, etc. Any devices or functions that tenants' terminals can access on the IoT platform can be considered services provided by the IoT platform.

[0091] Infrastructure refers to the hardware used to enable a cloud system (for example, a public cloud) to provide various cloud services. It can include multiple data centers (DCs) located in different geographic regions. Each data center contains multiple physical servers, each of which can be used to support various cloud services such as virtual machines (VMs), containers (Docker), bare metal servers, and cloud hard drives. Furthermore, the IoT platform communicates with the infrastructure, allowing it to provide tenants with the various cloud services supported by the infrastructure.

[0092] IoT devices are devices connected to the Internet of Things.

[0093] Business device, an IoT device used to perform business.

[0094] Edge devices are devices that communicate with IoT devices faster than IoT platforms. Edge devices can be sensors installed on IoT devices, IoT gateways, IoT systems to which IoT devices are connected, etc.

[0095] In order to automatically generate a process flow, the present application provides a process flow management method. FIG1a exemplarily shows a flow chart of the method.

[0096] As shown in Figure 1a, this method can be applied to a management platform 400, which can run on a management device 500. As shown in Figure 1a, the management platform 400 can be communicatively connected to a service device 101. For example, the management device 500 is connected to the service device 101, so that the management platform 400 and the service device 101 can be communicatively connected, and the service device 101 can be used to execute a service. The service can include multiple processes. During operation, the service device 101 can send multiple service data to the management platform 400 on the management device 500. Each of the multiple service data includes a process identifier for one of the multiple processes.

[0097] The service device 101 is a device for executing services, and the service device may be different in different application scenarios.

[0098] Taking the beer production scenario as an example, the business device 101 can be used to execute the beer production business. The beer production business may include multiple processes during execution, and the business device 101 may include multiple sub-business devices corresponding to different processes. Each process can be executed by a corresponding sub-business device. For example, processes may include, but are not limited to, crushing, gelatinization, filtration, and boiling. The corresponding sub-business devices may be crushing equipment, gelatinization equipment, filtration equipment, boiling equipment, etc.

[0099] In some scenarios, the business device 101 may be the entire management system for executing beer production, and the management platform 400 may receive business data reported by the management system for executing beer production.

[0100] In other scenarios, the management platform 400 may receive business data of respective processes reported by various sub-business devices corresponding to different processes.

[0101] The business data received by the management platform 400 may include a process identifier of at least one process among a plurality of processes executed by the business device 101 .

[0102] 1a, the management platform 400 may also obtain process information corresponding to the business executed by the business device 101. The process information may include a starting process identifier of a starting process among the multiple processes mentioned above, and may also include a process end condition.

[0103] Then, the management platform 400 of the present application may generate a process flow based on the multiple business data and the process information. The process flow may include information on the execution order of the multiple processes executed by the business device 101.

[0104] The management platform 400 of the present application can be a software system, hardware, or a combination of the two, which is not limited here.

[0105] The management platform 400 of the present application may be a cloud management platform running on the cloud (eg, an Internet of Things platform), or a management platform running on an edge device.

[0106] The following describes the implementation process of the process flow management system and method of the present application in different application scenarios in conjunction with Figure 1b and Figure 1c respectively.

[0107] Please refer to FIG. 1 b . In the application scenario shown in FIG. 1 b , the management platform 400 shown in FIG. 1 a is the Internet of Things platform 201 , and the management device shown in FIG. 1 a is the public cloud 200 shown in FIG. 1 b .

[0108] As shown in Figure 1b, the process flow management system may include, but is not limited to, a public cloud 200, a client 300, a business device 101, and an edge device 102. The public cloud 200 may include, but is not limited to, an IoT platform 201 and infrastructure 202. While the system in this application uses a public cloud as an example, in other embodiments, the system is also applicable to private or hybrid clouds, and the principles are the same, so this description will not be repeated here.

[0109] In some embodiments, the Internet of Things platform 201 may provide various interfaces such as a login interface and a data processing interface for access by the tenant's client (e.g., client 300). The client may be a terminal used by the tenant or a browser on a terminal used by the tenant, etc., which is not limited here. The tenant's terminal is also referred to as an electronic device, user device, or terminal device, which is not limited in this application. The terminal may include, but is not limited to: a mobile phone, a tablet computer, a computer, a personal computer (PC), a device in an Internet of Things (IoT) system, etc.

[0110] As shown in FIG. 1 b , the service device 101 is in communication connection with the edge device 102 .

[0111] Continuing with the scenario of a beer production factory as an example, the edge device 102 can be the factory's IoT gateway, the factory's IoT system, or a sensor or other device installed on the business device 101, used to collect business data generated by the business device 101 during the execution of the beer production business.

[0112] The public cloud 200 of the present application can provide a cloud service for generating a process flow. After the beer production factory purchases the cloud service, an account and password for using the cloud service can be allocated to the factory.

[0113] For example, the IoT platform 200 can receive the above-mentioned account and password input by the tenant through the client 300 through the login interface to authenticate the tenant's client 300. After the verification is passed, the tenant's client 300 can be allowed to log in to the IoT platform 200 to use the cloud service for generating the process flow.

[0114] In addition, the Internet of Things platform 200 can also provide a user interface, and the tenant's client 300 can interact with the Internet of Things platform 201 through the user interface to implement the process flow management method of the present application.

[0115] For example, after logging into IoT platform 200, a tenant client 300 can input business process information into IoT platform 201 through the user interface. The business is executed by business device 101 (e.g., beer production). This process information contains process constraint information related to the process to be generated. For example, this process information may include, but is not limited to, a starting process identifier and process end conditions.

[0116] The tenant may input the process information into the interface, import the process information into a file, or input the process information into the IoT platform 201 through software configuration, which is not limited in this application. In this way, the IoT platform 201 may receive the process information of the business.

[0117] During the operation of the business device 101, the business device 101 may generate business data, and the edge device 102 may collect the business data of the business device 101 and upload it to the public cloud 200. In this way, the cloud management platform 201 may receive the business data collected by the edge device 102. The business data may include process information of the process (e.g., crushing) used to perform the business. The process information may include a process identifier. For example, the business data flow generated during the beer production process may correspond to the following processes: crushing, gelatinization, filtration, etc.

[0118] The business data generated by the business equipment can be identical to the business data collected and reported to the public cloud 200 by the edge device 102. Alternatively, considering that the data structures of the business data generated by the sub-business equipment corresponding to different processes, such as a crushing device and a gelatinizing device, are not necessarily identical during their respective operations, and not all business data is required by the IoT platform 201, the edge device 102 can only collect data generated by the business equipment that conforms to a preset data structure (such as a process identifier, process execution time, etc.) and report the collected business data to the public cloud 200.

[0119] In this way, the IoT platform 201 shown in FIG1b can generate a process flow of the business based on the business data from the edge device 102 and the process information from the client 300 , and the process flow may include a logical sequence between multiple processes for executing the business.

[0120] For example, the Internet of Things platform 201 can provide the generated process flow to the tenants for viewing through the above-mentioned user interface.

[0121] In this way, in the IoT scenario, there is no need to use drawing tools to configure and visualize the production process to draw the process flow. The IoT platform can be used to automatically generate and draw the process flow, thereby improving the efficiency of process flow generation and ensuring the accuracy of the generated process flow.

[0122] It should be understood that some structures in Figure 1b are shown with single arrows, which are intended to illustrate the transmission direction of a certain data of current concern. In actual applications, two interacting structures can communicate bidirectionally. The content of the communication is related to the application scenario and is not limited here.

[0123] Figure 1b illustrates the implementation process of the process flow management method of the present application by taking the process flow management method of the present application as an example of applying the process flow management method of the present application to the cloud. In other embodiments, the process flow management method of the present application is not limited to application to the cloud, but can also be applied to devices under the cloud such as edge devices.

[0124] Referring to Figure 1c, in the application scenario shown in Figure 1c, the management platform 400 shown in Figure 1a is the management platform 102a of the IoT platform 201 running on the edge device 102, and the management device 500 shown in Figure 1a is the edge device 102 shown in Figure 1c. The system shown in Figure 1c may also include a service device 101 and a client 301.

[0125] Continuing with the example of the beer production business, the edge device 102 can be a management device for managing the beer production process of the beer production factory, or it can be a physical server of the beer production factory, or it can be a gateway, sensor, etc. of the beer production factory, and there is no restriction here.

[0126] In other scenarios, the management platform 400 shown in FIG1a can run not only on the cloud or edge devices, but also on other devices, as long as the management platform 400 can obtain business process information and business data.

[0127] FIG2 is a flowchart illustrating the steps of a process flow management method of the present application. The process shown in FIG2 is described below using the management platform 400 of the present application applied to the cloud, for example, the management platform 400 is the IoT platform 201 shown in FIG1b. When the method is applied to other scenarios (such as the edge device shown in FIG1c), the implementation principle of the method is similar and will not be repeated here.

[0128] In conjunction with FIG1b , as shown in FIG2 , the IoT platform 201 may perform the following steps:

[0129] S101, obtaining business process information.

[0130] The service is executed by the service device 101 and includes multiple processes.

[0131] For example, the beer production business may include multiple processes such as crushing, gelatinization, and filtration during execution.

[0132] The process information may include a starting process identifier of a starting process of the business (e.g., the entire production process of the beer production business), such as a process identifier of a crushing process;

[0133] The process information may include one or more parameters and their parameter values.

[0134] The parameters may include a parameter indicating a process identifier, such as a field name (key) of the process identifier. The parameters may also include a parameter indicating a process identifier of a starting process.

[0135] An example of the parameters and their values ​​is shown in Table 1

[0136] Table 1

[0137] For example, a tenant (e.g., an administrator) can enter the two records in Table 1 in the interface of the client 300 to input the field name of the process identifier (specifically, "EOP") and the process identifier of the starting process (specifically, "A") into the IoT platform 201. The IoT platform 201 can use the parameter value "EOP" to locate the process identifier carried in the received business data, thereby determining whether the business data is the required target business data. The IoT platform 201 can use the parameter value "EOP" and its value "A" to locate the business data of the starting process.

[0138] In some embodiments, the process information may further include a process end condition.

[0139] The process end condition may be at least one of a process identifier for terminating the process (also expressed as a process end identifier), a process duration, and a start process identifier.

[0140] Optionally, the process information may further include the number of process iterations.

[0141] The starting process identifier can be used to determine the process identifier before the next starting process identifier. Its usage process will be described in the following scenario 1.

[0142] The process identifier of the termination process is the process identifier of the termination process (the last process) in the process flow to be generated. The specific usage process will be described in the following scenario 3.

[0143] The process duration is the maximum duration estimated based on prior knowledge for the tenant's business equipment to execute the process once. For example, the maximum duration for a beer production business to complete a beer production process. The specific usage process will be described in Scenario 4 below.

[0144] Number of process iterations: When the business equipment has not changed, it is considered that there may be differences in the process flow when the business equipment performs the same business at different time periods. For example, the process flow for producing beer during the day is different from the process flow for producing the beer at night. And / or, considering that the business equipment can produce the same product (such as beer) of different qualities, the process flow for producing this product may change. Therefore, in order to be able to generate a complete and accurate process flow, the number of process iterations can be set. The number of process iterations is the number of loop executions of the method of the present application. Each execution of the method of the present application can generate a process flow. Of course, the process flows generated at different times may be the same or different, and there is no limitation here. The specific use of the number of process iterations will be explained in the following scenario 5.

[0145] Another example of the process information can be seen in Table 2. In this way, the process information may also include at least one of the process identifier of the termination process and the process flow duration, and optionally may also include the number of process iterations, so as to jointly constrain the process flow to be generated.

[0146] Table 2

[0147] S101 is equivalent to the initial configuration of the system of the present application for generating a process flow, and the configuration can generate process information that can constrain the process flow to be generated, such as which process is the starting process of the process flow, and the process end condition that characterizes the end of the process flow.

[0148] S102: Receive a plurality of service data sent by the service device during operation.

[0149] For example, the service data is service data generated by the service device during the process of executing the service.

[0150] The business data may include a process identifier of at least one process among the above-mentioned multiple processes;

[0151] For example, the business data may include a process identifier of a process for executing the business (which may be a process being executed or a process that has been recently completed, without limitation);

[0152] In some embodiments, the business data may also include process execution time, which is the time at which the process occurs, such as the process start time, process end time, or any time during the execution of the process. The specific use and function of the process execution time will be explained in Scenario 2 below. Each of the multiple processes has a process identifier. The business data may include the process identifier of each of the at least one process and the process execution time of each of the at least one process.

[0153] In some embodiments, the business data may further include process parameters, where the process parameters are associated with the process identifier.

[0154] In some embodiments, the process parameters may include but are not limited to at least one of the following: process measurement data, production batches, production lines, etc.

[0155] In some scenarios, the business data collected by edge device 100 can be in the form of events. For example, each time a business device executes a process in the beer production process, it generates an event that describes the business data of the executed process. In this way, edge device 100 can receive an event stream and report it to IoT platform 201. The event stream may include multiple events.

[0156] In some scenarios, the business data collected by the edge device 100 can be in the form of time series data. For example, each time a business device executes a process in the beer production process, it generates a set of time series data. This set of time series data can describe the business data of the executed process. In this way, the edge device 100 can receive the time series data of each executed process and report it to the IoT platform 201.

[0157] Therefore, the business data received by the Internet of Things platform 201 may be a business data stream.

[0158] In some embodiments, considering that the business data required by the Internet of Things platform 201 adopts an agreed preset data structure (also called an agreed format), and the data structures of the business data generated by each business device may be different, the edge device 100 can collect business data from each sub-business device executing each process according to a unified preset data structure and report it to the Internet of Things platform 201.

[0159] In some embodiments, S102 is performed after S101 .

[0160] Of course, in some embodiments, the process information in S101 may be updated during the execution of S102, so that S101 and S102 may be executed in parallel.

[0161] S103, based on the plurality of business data and the process information, determining target business data in the plurality of business data that matches the process information;

[0162] The process information is some process constraint information related to the process to be generated. Then the Internet of Things platform 201 can determine part of the business data (here, target business data) that matches the process information in the received business data stream to generate the process flow.

[0163] For example, the process information may include but is not limited to: the starting process identifier and process end conditions of the business.

[0164] Then, the IoT platform 201 may determine the first business data in the business data whose process identifier matches the starting process identifier, and the second business data received after the first business data and meeting the process end condition. The target business data may include the first business data and the second business data.

[0165] S104: Generate a process flow based on the target business data.

[0166] In some embodiments, S103 and S104 may be executed sequentially, such as scenario A shown in FIG3 a , so that after all target business data are found, the target business data may be used to subsequently generate a process flow.

[0167] In some embodiments, S103 and S104 may also be executed in parallel, such as scenario B shown in FIG3 b , so as to generate a process flow in real time based on the target business data found in real time.

[0168] The business data of the starting process in the process flow is the first business data, and the business data of the ending process in the process flow is the second business data.

[0169] The starting process of the process flow is the first process indicated by the first process identifier in the first business data, and the ending process of the process flow is the second process indicated by the second process identifier in the second business data.

[0170] Scenario A, please refer to the post-generation process flow scenario shown in Figure 3a:

[0171] For example, in the scenario of Figure 3a, the configured process information is shown in Table 3, where the process information shown in Table 3 may include the process identifier of the starting process. In addition, the process identifier of the starting process can also be used to determine the process identifier of the process before the next starting process identifier (received or executed). Therefore, the process information shown in Table 3 may also include a process end condition. It should be understood that the process information of Scenario A is not limited to Table 3.

[0172] Table 3

[0173] In FIG3a , FIG3a(2) is an exemplary implementation process diagram of S103 , and FIG3a(3) is an exemplary implementation process diagram of S104 .

[0174] As shown in Figure 3a(1), the IoT platform 201 receives the business data of process A, process B, process C, process D, process A, etc. in the order of reception time indicated by the arrows. For example, the business data of process A is specifically: "EOP" = "A"; the business data of process B is "EOP" = "B". The business data of other processes is similar and will not be given any more examples. In other words, each piece of business data carries the corresponding process identifier.

[0175] Then, when the IoT platform 201 receives the business data of process A, it can determine that the business data is the business data of the starting process based on Table 3, so as to record the business data of process A, specifically referring to FIG3a(2);

[0176] Then, as shown in FIG3a(1), the IoT platform 201 receives the business data of process B. Based on Table 3, it can be determined that the business data is not the business data of the starting process. Then, as shown in FIG3a(2), the IoT platform 201 can record the business data of process B after the business data of process A. Similarly, the IoT platform 201 can record the business data of processes A to D in sequence according to the recording order shown in FIG3a(2).

[0177] Then, as shown in FIG3a(1), after receiving the business data of process D, the IoT platform 201 receives the business data of process A again. Based on Table 3, it can be determined that the business data is the business data of the starting process. In other words, the IoT platform 201 receives the next starting process identifier (the process identifier in the business data of process A after process D). Then the IoT platform 201 can determine the process D that was recorded most recently before the business data of the starting process (here, process A) received again as the ending process in this process flow. Then, as shown in FIG3a(3), the IoT platform 201 can generate the process flow shown in FIG3a(3) based on the business data of each process in the recording order shown in FIG3a(2) (in this example, the target business data includes the business data of process A to process D recorded in FIG3a(2)). The process flow describes the logical order between each process according to the arrows. As shown in FIG3a(3), the process flow is to execute process A, process B, process C and process D in sequence.

[0178] Among them, the process identifiers of process B, process C, and process D are "B", "C", and "D" respectively, which are different from the process identifier of process A (specifically "A").

[0179] As shown in FIG3a(3), the generated process flow can display the process identifiers of the various processes involved in the process flow. In addition, the logical sequence between the various processes can also be reflected in the form of arrows.

[0180] In this scenario, the application can find target business data that matches the process information in the received business data based on the process information, such as the business data of process A to process D as shown in Figure 3a(2), where the business data of process A is the first business data and the business data of process D is the second business data. Then, a complete process flow is generated based on the target business data. The process flow can be generated afterwards with complete and comprehensive target business data to ensure the accuracy of the process flow.

[0181] For scenario B, please refer to the real-time process flow generation scenario shown in Figure 3b:

[0182] For example, in the scenario of FIG3 b , the configured process information is the same as that of scenario A, and is also shown in Table 3. However, the process information of scenario B is not limited to Table 3.

[0183] In scenario B, the business data flow received by the IoT platform 201 is the same as the business data flow shown in FIG3a(1), and will not be described again here.

[0184] In Figure 3b, Figure 3b(1) is an exemplary implementation process diagram of S103, and Figure 3b(2) is an exemplary implementation process diagram of S104. In this scenario B, S103 and S104 can be executed in parallel.

[0185] Specifically, as shown in FIG3b(1), when the IoT platform 201 first receives the business data of process A, it can determine that the business data is the business data of the starting process based on Table 3 to record the business data of process A; then, as shown in FIG3b(2), the IoT platform 201 can generate the first node in the process flow based on the recorded business data of process A, specifically the node of process A.

[0186] Then, after receiving the business data of process A, the IoT platform 201 may receive the business data of process B, and may determine based on Table 3 that the business data is not the business data of the starting process, as shown in FIG3b(1), and may continue to record the business data of process B in the order of recording; then, as shown in FIG3b(2), the IoT platform 201 may continue to add a second node, specifically a node of process B, to the process flow that already has a node A based on the recorded business data of process B, thereby generating a process flow from process A to process B.

[0187] By analogy, after receiving the business data of process C, the IoT platform 201 can continue to record the business data of process C in the recording order as shown in FIG3b(1), and continue to add process C to the generated process flow from process A to process B in real time as shown in FIG3b(2), so as to generate a process flow from process A to process B and then to process C.

[0188] By analogy, after receiving the business data of process D, the IoT platform 201 may continue to record the business data of process D in the recording order as shown in FIG3b(1), and continue to add process D to the generated process flow including process A, process B, and process C in real time as shown in FIG3b(2), so as to generate a process flow from process A to process B, then to process C, and finally to process D. The process flow reflects the logical order between process A and process D, that is, process A is executed first, process B is executed after process A is completed, process C is executed after process B is completed, and process D is executed after process C is completed.

[0189] Next, as shown in Figure 3a(1), after receiving the business data of process D, the IoT platform 201 receives the business data of process A again. Based on Table 3, it can be determined that the business data is the business data of the starting process received again. Then, the ending process in this process flow is determined to be the process corresponding to the business data received most recently before the business data of the starting process received again (specifically, process D). The last node in the generated process flow (corresponding to process D) is generated, so no new node is added after the last node D shown in Figure 3b(2).

[0190] Among them, the process identifiers of process B, process C, and process D are B, C, and D respectively, which are different from the process identifier of process A (specifically "A").

[0191] In this scenario B, this application can find the target business data that matches the process information in the received business data based on the process information (in this case, the business data of process A to the business data of process D), and then generate the process flow in real time based on the target business data, so that the process flow can be updated in real time as the target business data is updated.

[0192] In this embodiment, the business process information can be used to find the target business data that meets the constraint information indicated by the process information from the received business data, so as to generate a process flow. This can realize the automatic and accurate generation of the process flow without the need to use drawing tools to configure and visualize the production process to draw the process flow.

[0193] In both Figure 3a under scenario A and Figure 3b under scenario B, the logical order between business data is determined according to the order of the reception time of the business data from early to late (that is, the order of the reception time from far to near to the current time), and the process flow is generated based on this logical order as an example.

[0194] In other embodiments, the scheme for generating the process flow afterward as defined by scenario A and the scheme for generating the process flow in real time as defined by scenario B are also applicable to determining the logical order between business data based on the order of process execution time from early to late carried in the business data (i.e., the order of process execution time from far to near to the current time), so as to generate a scheme for the process flow based on the logical order.

[0195] In some embodiments, the business data received by the IoT platform 201 may also include process parameters.

[0196] In some embodiments, the process parameters may include but are not limited to at least one of the following: process measurement data, production batches, production lines, production plans, etc.

[0197] Then, when recording various business data, the Internet of Things platform 201 may record the process parameters, so that the tenants can easily understand the process parameters of each node (representing the process) in the generated process flow.

[0198] In some embodiments, the generated process flow (e.g., the process flow shown in FIG. 3a(3) or FIG. 3b(2)) may include the process parameters of each of the multiple processes. For example, the information displayed at each node in the process flow may include not only the process identifier but also the process parameters associated with the process identifier. Alternatively, after the user selects a node through input, the IoT platform 201 may display the process parameters of the process indicated by the node in response to the user input.

[0199] For example, in the case of the pulverization process for beer production, the measurement data may be fineness. Beer production can be divided into different production batches, production lines, and production plans. Therefore, the process parameters of the pulverization process may include information about the production batch, production line, and production plan. This allows the tenant's client 300 to obtain information from the IoT platform 201 through the user interface regarding the beer production process for the production plan, production line, and production batch.

[0200] In combination with the above embodiments, the implementation process of the method of the present application is described below from different application scenarios.

[0201] Scenario 1: Generate a process flow based on the order of business data reception time (for example, the order of reception time from far to near the current time).

[0202] Please refer to Figure 4a. As shown by the direction of the arrow of the receiving time, the Internet of Things platform 201 can receive the business data stream shown in Figure 4a (1) in the order of the receiving time. Specifically, the Internet of Things platform can receive the business data of processes such as process B, process A, process B, process C, process E, process A, process B, process C, process D, process E, and process A from front to back.

[0203] The process information configured in Scenario 1 is, for example, as shown in Table 3 above. Specifically, the process information includes the process identifier of the starting process (e.g., "EOP" = "A") and the process end condition limited by the process identifier of the starting process. Of course, the process information may also include other information, which is not limited here.

[0204] As shown in Figure 4a (1), when the Internet of Things platform 201 first receives the business data of process B, the business data of process B carries the information "EOP=B". Based on Table 3, it can be determined that the business data is not the business data of the starting process, then the Internet of Things platform 201 can discard the business data of process B received this time.

[0205] Then, as shown in FIG4a(1), the IoT platform 201 can continue to receive the business data of process A, and based on Table 3, it can be determined that the business data is the business data of the starting process, thereby generating the first node A shown in FIG4a(2); the IoT platform 201 can refer to the implementation principle and implementation process of the above scenario A or scenario B according to the order of receiving the business data of processes B, C, and E after the first process A from early to late (the order of receiving the second to fifth business data received as shown in FIG4a(1)), and generate a process flow as shown in FIG4a(2) afterwards or in real time. In the process of generating this process flow, since the business data received again after the IoT platform 201 receives the business data of the first process E is the business data of process A (the process identifier is the process identifier of the starting process carried in the process information), then based on Table 3, it can be determined that process E here is the last process in the process flow currently being generated.

[0206] The same principle as that of generating the process flow shown in FIG4a(2) is used. The IoT platform 201 can determine the logical order between the processes based on the order of the receiving time of the business data of the 6th to 10th processes (respectively, process A, process B, process C, process D, and process E) received from early to late, and use the logical order to generate a process flow ex post or in real time based on the principle of the above scenario A or scenario B, such as the process flow shown in FIG4a(3). Optionally, since the first node can be determined as process A, the above logical order can also be the logical order between the remaining processes B, process C, process D, and process E after process A.

[0207] In this embodiment, when the process information does not carry the number of process iterations, the Internet of Things platform 201 can generate a process flow with the starting process as the first node every time the process data of the starting process is detected. In scenario 1 shown in Figure 4a, at least two process flows can be generated. Since the subsequent business data is not shown, more process flows can actually be generated, and there is no restriction here.

[0208] Of course, when the process information does not carry the number of process iterations, the default number of process iterations can also be set to 1. Then, in the scenario of Figure 4a(1), the Internet of Things platform 201 can only generate a process flow as shown in Figure 4a(2), and not generate a process flow as shown in Figure 4a(3).

[0209] In this scenario 1, the method can determine the receiving time sequence of the first business data, the second business data, and the third business data based on the target business data and the third business data; and generate a process flow based on the receiving time sequence, wherein the starting process of the process flow is the first process indicated by the first process identifier in the first business data, the ending process of the process flow is the second process indicated by the second process identifier in the second business data, and the intermediate process of the process flow is the third process indicated by the third process identifier in the third business data.

[0210] The present application can use process information to find the business data of the starting process in the received business data (an example of the first business data). In addition, the process identifier of the starting process in the process information can be used to find the business data of the terminating process in this process flow (an example of the second business data). The business data of the terminating process is specifically the business data received most recently before the business data of the starting process is received again, and the business data with a reception time between the first business data and the second business data is determined as the third business data (wherein, multiple business data may also include the third business data). Then, the first logical order between the process identifiers of the first business data, the second business data, and the third business data can be determined in order of reception time from early to late, to determine the first logical order between the process identifiers indicated by each business data (for example, the order of process A->process B->process C->process E shown in Figure 4a (2)), and generate a process flow based on the first logical order. For example, the process flow can be the logical order between the process identifiers.

[0211] Scenario 2: Generate a process flow based on the order of process execution time of the processes carried in the business data.

[0212] The process execution time may be the start time, end time, or any time during the process execution, and is not limited here.

[0213] In this scenario 2, the business data not only carries a business identifier, but also carries the process execution time associated with the business identifier. Then, the Internet of Things platform 201 can determine the first business data whose process identifier in the business data is the process identifier of the starting process; and the second business data received after the first business data that meets the process end condition; In addition, the Internet of Things platform 201 can also determine the third business data whose execution time is between the first business data and the second business data. And use the process identifier of the starting process to determine the received second business data (business data of the terminating business). According to the order of the process execution time from early to late, determine the second logical order between the process identifiers of the first business data, the second business data, and the third business data; Based on the second logical order, generate a process flow.

[0214] Please refer to Figure 4b. The business data flow shown in Figure 4b (1) is the business data flow received by the Internet of Things platform 201 in the order of receiving time. According to the order of receiving time of the business data from early to late, the Internet of Things platform can receive the business data of process A, process B, process E, process C, process A and other processes from front to back.

[0215] The process information configured in scenario 2 is, for example, as shown in Table 3 above, that is, the process information indicates the process identifier of the starting process, such as "EOP" = "A". Of course, the process information may also include other information, which is not limited here.

[0216] In one possible implementation, the IoT platform 201 may record the received business data stream, as shown in FIG4b . The IoT platform 201 may determine a first logical sequence of A->B->E->C based on the order of the business data's reception time from earliest to latest. Optionally, a process flow as shown in FIG4b (2) may be generated based on the first logical sequence. The process flow may be generated ex post or in real time based on the principles of scenario A or scenario B, without limitation.

[0217] However, the first logical sequence may have at least one of the following situations: incorrect node order, missing nodes, or redundant nodes.

[0218] The case of a missing node includes: a node whose reception time is before the reception time of process A in the first logical sequence above, but whose process execution time is after the process execution time of process A. For example, if the process information includes a process identifier of a terminated process (or other process termination conditions as mentioned above), and the terminated process is process E, then the case of a missing node may also include business data whose reception time is after the business data of process E, but whose process execution time is before the business data of process E and after the business data of process A (the process corresponding to this business data is the missing node).

[0219] The case of redundant nodes: for example, a node whose reception time is after the reception time of process A in the first logical sequence above, but whose process execution time is before the process execution time of process A. For example, if the process information includes the process identifier of the terminated process (or other process termination conditions as mentioned above), for example, the terminated process is process E, then the case of redundant nodes can also be business data whose reception time is before the business data of process E and after the business data of process A (the first node), but whose process execution time is after the business data of process E (the process corresponding to this business data is a redundant node).

[0220] Then, the IoT platform 201 can redetermine the logical order of each process (for example, expressed as a second logical order) based on the order of the process execution time in the business data of each process recorded, which is A->B->C->E. Optionally, when determining the second logical order, there may be at least one operation such as deleting redundant nodes, adding missing nodes, and adjusting the order of nodes with incorrect order. Then, the IoT platform can adjust the generated process flow shown in Figure 4b (2) (or the above-mentioned first logical order) according to the second logical order, specifically adjusting the order between node E and node C, thereby obtaining the process flow shown in Figure 4b (3).

[0221] In this embodiment, a first logical order can be first determined according to the order of the reception time of the business data from early to late, and a process flow can be optionally generated in real time or afterwards according to the first logical order; then, based on the process execution time recorded in the business data of each node in the above process flow, the process flow or the first logical order can be adjusted according to the order of the process execution time from early to late to obtain an adjusted process flow that is consistent with the order of the process execution time of the process, so as to ensure the accuracy of the logical order between the nodes in the generated process flow.

[0222] In another possible implementation, different from the solution in Scenario 1, the process identifier of the starting process in the process information is directly used to find the business data of the starting process, and the business data whose receiving time is before the receiving time of the business data of the starting process is directly discarded.

[0223] In this embodiment, the Internet of Things platform 201 can record each business data in the received business data stream shown in Figure 4b (1), and sort the recorded business data in the order of the process execution time carried in the business data from early to late. The sorting result can be referred to Figure 4b (4). The multiple business data sorted in the order of the process execution time from early to late are the business data of process A, process B, process C, process E, and process A. Then, the Internet of Things platform 201 can find the business data of the starting process and the business data of the ending process in the sorted multiple business data according to the process identifier of the starting process and the process end condition in the process information, so as to determine the first node (for example, node A corresponding to the first process A) and the ending node (for example, node E corresponding to process E) in the process flow to be generated.

[0224] In some embodiments, when there is business data that is arranged before the starting process (process A) among the multiple business data sorted by process execution time (for example, the business data of process F shown in the dotted box in FIG4b(4)), for example, the business data of process F is located between the business data of process A and the business data of process B in the order of reception time shown in FIG4b(1), then the recorded business data (here, the business data of process F) can be discarded.

[0225] As shown in FIG4b(4), the IoT platform 201 can find the first business data of the starting process (here, the business data of process A whose execution time is adjacent to and after the execution time of process F) based on the process identifier and process end condition of the starting process in the process information, find the second business data of the terminating process (here, the business data of process E whose execution time is before the execution time of the business data of process A received again and is the latest execution time), and find the third business data whose execution time is between the execution time of the first business data of process A and process E (the business data of the intermediate process between the starting process and the terminating process), here, the business data of process B and process C. According to the order of the execution time of the processes from earliest to latest, the second logical order between the process identifiers of the first business data, the second business data, and the third business data is determined, for example, A->B->C->E; finally, according to the second logical order, the process flow shown in FIG4b(3) is generated, and the process flow shown in FIG4b(2) does not need to be generated in the intermediate process.

[0226] For example, when determining the second logical order, the second logical order between each business data can be determined in real time based on the process execution time in the currently received business data and the process execution time in the received business data; or after using the process information to find the first business data of the starting process and the second business data of the terminating process, the second logical order can be determined afterwards based on the process execution time of each business data. There is no restriction here.

[0227] In this embodiment, each of the multiple business data also includes the process execution time of a process among the multiple processes, and the multiple business data also include third business data, wherein the process execution time of the third process indicated by the third process identifier in the third business data is between the process execution time of the first process indicated by the first process identifier in the first business data and the process execution time of the second process indicated by the second process identifier in the second business data; generating a process flow based on the target business data includes: determining the order of the process execution times of the received first business data, the second business data, and the third business data based on the target business data and the third business data; generating a process flow based on the order of the process execution times, wherein the starting process of the process flow is the first process indicated by the first process identifier, the ending process of the process flow is the second process indicated by the second process identifier, and the intermediate process of the process flow is the third process indicated by the third process identifier.

[0228] Considering that the execution times of multiple processes of a business are relatively close, the business data of the later-executed process may be reported to the IoT platform 201 before the business data of the earlier-executed process. As a result, the order of the reception time of the business data received by the IoT platform 201 from earliest to latest cannot accurately reflect the execution order of different processes. Therefore, in order to improve the accuracy of the process flow, the first business data with the process identifier of the starting process can be determined; the second business data that meets the process end condition can be determined; and the third business data with the process execution time between the first business data and the second business data can be determined. The second logical order between the process identifiers of the first business data, the second business data, and the third business data can be determined according to the order of the process execution time from earliest to latest. Finally, the second logical order is used to obtain a process flow that can reflect the actual process execution time order of the process, so as to avoid the process error caused by generating the logical order between processes based solely on the order of the reception time of the business data, thereby ensuring the accuracy of the logical order between the nodes in the generated process flow.

[0229] In a possible embodiment, in a technical solution for generating a process flow based on the order of the process execution time of the processes carried in the business data, the generated process flow may include the process execution time of each process in the multiple processes for executing the business. For example, as shown in Figure 4b (2) or Figure 4b (3), the information displayed by each node in the process flow may include not only the process identifier, but also the process execution time associated with the process identifier. In this way, even if there are certain errors in the generated process flow in some scenarios, since each node in the process flow can also display or carry information about the process execution time, the tenant's client can determine whether the automatically generated process flow is accurate by tracing the process execution time, and in the case that there are errors in the process flow, adjust the logical order of the nodes with errors. For example, the tenant can adjust the order between node E and node C as shown in Figure 4b (2) based on the information about the process execution time of each node displayed in the process flow to obtain the process flow as shown in Figure 4b (3).

[0230] Scenario 3

[0231] In the above scenarios 1 and 2, the process end condition indicating the end of the process flow is not limited. Therefore, in the above scenarios 1 and 2, when business data with a process identifier that is the process identifier of the starting process in the process information is received again, the business data received most recently before the business data (the process identifier of the business data is not the process identifier of the starting process) is determined as the process identifier of the termination process of the second business data that meets the process end condition, or a business data with the latest process execution time received before the business data (also called the first business data) other than the first business data is determined as the second business data that meets the process end condition.

[0232] In this scenario 3, the process of generating the process flow of this application will be explained by taking the process end condition including the process identifier of the termination process as an example.

[0233] That is, in this scenario 3, the process information may include not only the process identifier of the starting process, but also the process identifier of the ending process.

[0234] FIG4c exemplarily shows a schematic diagram of the business data flow received and the generated process flow in this scenario 3.

[0235] For example, in the scenario of FIG4c, the configured process information is shown in Table 4.

[0236] Table 4

[0237] Please refer to Figure 4c. The business data flow shown in Figure 4c (1) is the business data flow received by the Internet of Things platform 201 in the order of reception time. According to the order of reception time of the business data from early to late, the Internet of Things platform 201 can receive the business data of process A, process B, process C, process E, process F and other processes from front to back.

[0238] The process information configured in Scenario 3 is, for example, as shown in Table 4 above. The process information indicates the process identifier of the starting process: "EOP" = "A," and the process information indicates the process identifier of the ending process: "EOP" = "E," where the ending process occurs after the starting process. Of course, the process information may also include other information, which is not limited here.

[0239] As shown in Figure 4c(1), the IoT platform 201 may first receive the business data of process A (e.g., "EOP" = "A"), and based on Table 4, it can be determined that the business data is the business data of the starting process, thereby generating the first node A shown in Figure 4c(2); then, the IoT platform 201 may receive the business data of process B (e.g., "EOP" = "B"), and based on Table 4, it can be determined that the business data is neither the business data of the starting process nor the business data of the ending process, and therefore, the business data is the business data of the intermediate process between the starting process and the ending process; similarly, the IoT platform 201 may continue to receive the business data of process C (e.g., "EOP" = "C"), and based on Table 4, it can be determined that the business data is the business data of the intermediate process. Then, the IoT platform 201 may receive the business data of process E, and based on Table 4, it can be determined that the business data of process E is the business data of the ending process (also expressed as second business data). The Internet of Things platform 201 can also receive the business data of process F after the business data of process E. Based on the judgment of Table 4, it can be determined that the business data of process F is not the starting process, nor the ending process, nor the intermediate process between the starting process and the ending process. Therefore, the business data of process F can be discarded without recording.

[0240] In this way, the IoT platform 201 can use the process identifier of the starting process in the process information to find the business data of process A, use the process identifier of the ending process in the process information to find the business data of process E, and use the process identifiers of the starting process and the ending process to find the business data of processes B and C located between processes A and E. These business data together constitute the target business data constrained by the process information.

[0241] Then the Internet of Things platform 201 can use the process identifier indicated by the business data of process A as the first node in the process flow (for example, node A shown in Figure 4c (2)), and the process identifier indicated by the business data of process E as the last node in the process flow (for example, node E shown in Figure 4c (2)). Then, it can be combined with scenario 1 to determine the logical order between process B and process C (here B->C) according to the order of the reception time of the business data from early to late, based on which the process flow shown in Figure 4c (2) can be obtained. Of course, it can also be combined with scenario 2 to determine the logical order between process B and process C for generating a process flow, wherein the business data of the last node E in the process flow is the business data of process E.

[0242] In this scenario 3, this application can use the process identifier of the starting process in the process information to find the business data corresponding to the first node in the process flow to be generated, and can also use the process identifier of the terminating process in the process information to find the business data corresponding to the last node in the process flow to be generated, and use the above two process identifiers in the process information to find the business data of the process (also called the intermediate process) whose receiving time or process execution time is between the starting process and the terminating process, and use the receiving time or process execution time to determine the logical order between the intermediate processes for generating the process flow. In this way, the process flow generated by this application can be used as the terminating process in the process flow according to the pre-configured terminating process.

[0243] Scene 4

[0244] In this scenario 4, the process of generating the process flow of this application will be explained by taking the process end condition including the process flow duration as an example.

[0245] That is, in this scenario 4, the process information may include not only the process identifier of the starting process, but also the duration of the process flow.

[0246] FIG4 d exemplarily shows a schematic diagram of the business data flow received and the generated process flow in this scenario 4 .

[0247] For example, in the scenario of FIG4d , the configured process information is shown in Table 5.

[0248] Table 5

[0249] Please refer to Figure 4d. The business data flow shown in Figure 4d (1) is the business data flow received by the Internet of Things platform 201 in the order of reception time. According to the order of reception time of the business data from early to late, the Internet of Things platform 201 can receive the business data of process A, process B, process C, process E, and process F from time t1 to time t5 respectively.

[0250] The process information configured in Scenario 4 is shown in Table 5 above, for example. The process information indicates the process identifier of the starting process: "EOP" = "A," and the estimated total process duration of the process flow to be generated, which is 24 hours in this case. Of course, the process information may also include other information, which is not limited here.

[0251] As shown in Figure 4d(1), the IoT platform 201 may first receive the business data of process A (for example, "EOP" = "A"), and based on Table 5, it may be determined that the business data is the business data of the starting process (also expressed as the first business data). Then, when the IoT platform 201 determines that the received business data of process A is the business data of the starting process, it may, for example, start counting from time t1 (or count down from time t1, with the countdown duration being 24 hours as shown in Table 5 above). The business data of process A may be used to generate the first node A as shown in Figure 4d(2).

[0252] Next, the IoT platform 201 may receive the business data of process B at time t2 (for example, "EOP" = "B"). Based on Table 5, it can be determined that the business data is not the business data of the starting process, and the timing duration has not reached 24 hours. Then, according to the order of the reception time of the business data from early to late, process B can be used as the node after the most recently recorded process A to generate the logical order of A->B.

[0253] Similarly, the IoT platform 201 may receive the business data of process C at time t3 (for example, "EOP" = "C"). Based on Table 5, it can be determined that the business data is not the business data of the starting process, and the timing duration has not yet reached 24 hours. Then, according to the order of the reception time of the business data from early to late, process C can be used as the node after the most recently recorded process B to generate the logical order of A->B->C.

[0254] Similarly, the IoT platform 201 may receive the business data of process E at time t4 (for example, "EOP" = "E"). Based on Table 5, it can be determined that the business data is not the business data of the starting process. However, the timing duration has reached 24 hours at time t4. In this case, the IoT platform 201 may use the most recently received process E as the termination process that meets the process end condition, and may use process E as the node after process C to generate the logical order of A->B->C->E.

[0255] Optionally, after the process flow is generated based on the logical sequence of A->B->C->E, the above timing can be reset until business data matching the process identifier of the starting process in the process information is received again, and then the timing is started again.

[0256] The IoT platform 201 can also receive the business data of process F at time t5. Since a process flow as shown in Figure 4d (2) has been generated, a starting process is required when the process flow is generated again. Based on the judgment in Table 5, it can be determined that the business data of process F is not the business data of the starting process. Therefore, the business data of process F can be discarded without making any records.

[0257] In the embodiment of FIG4d, the logical order between the intermediate nodes is determined in the order of the reception time of the business data from early to late as an example. In other embodiments, the logical order between the intermediate nodes can also be determined in the order of the process execution time in combination with the above scenario 2. Then, after the timing starts from the moment t1 when the business data of the starting process is received, when the timing reaches the duration of the process flow, the business data other than the first business data with the latest process execution time (that is, the process execution time is closest to the current time) received most recently (whose process identifier is not the process identifier of the starting process in the process information) can be used as the termination process that meets the process end condition.

[0258] In addition, in the embodiment of Figure 4d, taking the real-time generation of a process flow for the received business data (i.e., combined with the above-mentioned scenario B) as an example, in other embodiments, this scenario 4 can also be combined with scenario A to generate a complete process flow after determining all target business data that meets the process information.

[0259] In this scenario 4, the IoT platform 201 can use the process identifier of the starting process in the process information to find the business data of process A, and use the process duration in the process information to find the ending process (for example, process E). The receiving time or process execution time is used to determine the logical order between the intermediate processes to generate the process flow. In this way, the process flow generated by this application can generate the ending process in the process flow according to the pre-configured process duration.

[0260] In some embodiments, scenarios 3 and 4 above can be combined. For example, the configured process information may include the process identifier of the starting process, the process identifier of the ending process, and the process flow duration. In this case, as long as the received business data meets at least one of the following conditions: reaching the process flow duration, or having a process identifier that is the process identifier of the ending process, the process corresponding to the business data can be used as the ending process to generate the process flow.

[0261] Scene 5

[0262] Different from the above-mentioned scenarios 1 to 4, in this scenario 5, the process information may not only include the process identifier of the starting process, but also the number of process iterations N. The process information may also include the process termination conditions, such as the process identifier of the termination process, the process flow duration, the process identifier of the next received starting process, and at least one other information, which is not restricted here.

[0263] In scenario 5, FIG4e is a schematic diagram showing an exemplary received business data flow and a generated process flow.

[0264] For example, in the scenario of FIG4e , the configured process information is shown in Table 6.

[0265] Table 6

[0266] As shown in Table 6, the number of process iterations is set to 2, N=2.

[0267] The service data flow shown in FIG4e(1) is the same as the service data flow shown in FIG4a(1), and will not be described again here.

[0268] Although the number of process iterations is 2, the two generated process flows may be the same. Therefore, when the number of process iterations is 2, the number of generated process flows can be one or two. The two process flows can be merged to obtain a merged process flow, wherein the nodes with the same execution order between the two merged process flows are merged.

[0269] Combined with scenario 1, the process flow is generated in the order of business data reception time from early to late. Scenario 5 can also be combined with scenario 2 to generate the process flow in the order of business data process execution time.

[0270] Similar to the process of scenario 1 shown in FIG4a, the IoT platform 201 may discard the business data of process B that does not comply with Table 6 that is first received; then, the IoT platform 201 may use Table 6 to generate the process flow shown in FIG4e(2), complete the first iteration, and reduce the number of iterations of the process by one, so that only one iteration remains.

[0271] As shown in Figure 4e(1), after receiving the business data of the first process E, the process flow shown in Figure 4e(2) can be generated. Then, the Internet of Things platform 201 can continue to receive the business data of process A, process B, process C, process D, process E, and process A. Then, based on the process identifier of the starting process shown in Table 6, the Internet of Things platform 201 can regenerate the process flow shown in Figure 4e(2), and then reduce the number of process iterations by one so that the number of process iterations is zero. Then, the business data of process A received last can be discarded, without receiving business data again, and without generating another process flow based on the received business data.

[0272] In this way, after two iterations, two process flows as shown in FIG4e(2) and FIG4e(3) can be generated. Then, the Internet of Things platform 201 can merge the two process flows, specifically by merging the nodes with the same logical order (here, node A, node B, node C, the logical order is A->B->C) to generate a merged process flow as shown in FIG4e(4).

[0273] When the number of process iterations is greater than 2, the principle of the implementation process is similar and will not be repeated here.

[0274] Furthermore, in Scenario 5, a process flow is generated after each iteration, and when the number of iterations reaches zero, multiple process flows are merged. In other embodiments, the previously generated (or updated) process flow can be updated in real time during the next iteration to generate a merged process flow.

[0275] For example, FIG4f shows a schematic diagram of a real-time update process flow, which is the same as the business data flow shown in FIG4e(1).

[0276] As shown in FIG4f(1), after discarding the business data of the first process B, the IoT platform 201 may generate a process flow as shown in FIG4f(1) based on the received business data and process information of processes A, B, C, and E, and reduce the number of process iterations by one.

[0277] Then, as shown in FIG4e(1), the IoT platform 201 may receive the business data of process A again after receiving the business data of the first process E. In this case, there is no need to generate a new node A, but the node A in the process flow shown in FIG4e(1) can be reused. Similarly, when the business data of process B is received again, since the logical order A->B this time is the same as the logical order A->B in the generated process flow shown in FIG4e(1), the node B in the process flow shown in FIG4e(1) can be reused. Similarly, when the business data of process C is received again, the node C in the process flow shown in FIG4e(1) can be reused. In this way, in the second iteration, no node update has occurred in the process flow shown in FIG4e(1).

[0278] Next, as shown in FIG4e(1), the IoT platform 201 may receive the business data of process D, and may add node D after node C in the process flow shown in FIG4e(1) to indicate process D, thereby refreshing the process flow from FIG4e(1) to the process flow shown in FIG4e(2).

[0279] Then, as shown in Figure 4e(1), after receiving the business data of process D, the IoT platform 201 can receive the business data of process E. Since the node E of process E has been generated in the first iteration in the process flow shown in Figure 4e(2), the node E in the process flow shown in Figure 4e(2) can be used as the node after node D, so that the process flow is refreshed from Figure 4e(2) to the process flow shown in Figure 4e(3). Finally, as shown in Figure 4e(1), the IoT platform 201 can also receive the business data of process A, indicating that the second iteration has ended, and the number of process iterations is reduced by one, making the number of process iterations zero.

[0280] In this way, in the embodiment of Figure 4f, different from the embodiment of Figure 4e, the present application can use the business data of the process received this time to update the process flow generated or updated in the previous iteration in real time when generating the process flow each time, so as to obtain the process flow after this iteration merger, until the number of process iterations is updated to zero, then the process flow after the iterative merger is the final merged process flow.

[0281] In some embodiments, under scenario 5, the process parameters of the nodes in the process flow may also be iteratively updated.

[0282] Based on FIG. 4 f , FIG. 4 g exemplarily shows a process flow chart showing measurement data.

[0283] The implementation process of FIG. 4g is the same as that of FIG. 4f , and the only difference is that the business data of the process corresponding to the node can be displayed on the process flow. In addition, the business data of the process can be updated and displayed when the process flow is iteratively updated.

[0284] As shown in Figure 4g(1), the measurement data for each node in the first round of generated process flow are: parameter a of process A is 1, parameter b of process B is 2, parameter C is 3, and parameter e of process E is 5.

[0285] Then, during the second round of iterative updates, the parameter d of process D can be displayed as 4 near the newly added node D as shown in FIG4g(2), while the measurement data of each of processes A to C can be temporarily not updated. At the end of this round of iteration, for example, when the process flow shown in FIG4g(3) is generated, the measurement numbers of the repeated processes (such as process A, process B, process C, and process E) can be updated.

[0286] Finally, during the second round of iterative updates, the process flow is updated from FIG4g(2) to the process flow shown in FIG4g(3), and the IoT platform 201 can update the measurement data of each of processes A, B, C, and E received during the second round of iterative updates to the process flow shown in FIG4g(3), so that the measurement data of process A is updated from a=1 to a=1.1, the measurement data of process B is updated from b=2 to a=2.1, the measurement data of process C is updated from c=3 to a=3.1, and the measurement data of process E is updated from e=5 to e=5.1. Of course, the measurement data of each repeated node does not necessarily need to be updated. If its measurement data has not been updated, there is no need to update its displayed measurement data.

[0287] In an embodiment of the present application, taking into account that there may be errors in the accuracy of the business data of the process collected each time during the actual execution of the business, after setting the number of process iterations, each time a process flow is generated or updated, the latest process parameters of the corresponding process received this time can be updated to the process flow, or the process parameters in the business data associated with each node in the recorded process flow can be updated, so that the drawn process flow chart can be adjusted in real time according to the actual data of the executed business, and the logical order and process parameter errors between the process flow chart and the actual process flow can be continuously improved.

[0288] In some embodiments, during the execution of the method of the present application, the tenant may also adjust the input process information according to the actual scenario. The adjustment may include but is not limited to at least one of adjusting parameter values ​​and deleting and adding parameters.

[0289] For example, the parameter value adjustment may be to adjust the number of process iterations from 2 to 10.

[0290] For another example, the deletion of parameters may be: the process information includes the process duration and the process identifier of the termination process, then one of the two may be deleted.

[0291] For another example, the case of adding parameters may be: for example, if the process information originally only includes the process identifier of the starting process, then at least one parameter such as the process flow duration, the number of process iterations, etc. may be added.

[0292] The above examples of adjusting the process information do not limit the process information adjustment scheme of the present application. The adjustment scheme can be applied to the adjustment of various process information mentioned in various embodiments of the present application, and will not be repeated here.

[0293] If the business does not change but the process information is adjusted, the method of the present application can generate the latest process flow of the same business (eg, beer production business) based on the adjusted process information.

[0294] For example, in the scenario of FIG4e(1), during the second iteration, the number of process iterations has been updated to 1. For example, during the second iteration, when receiving the business data of process D, the tenant requests to adjust the number of process iterations from the initial setting of 2 to 10. Then, the IoT platform 201 is performing the second iteration in this round, and the number of process iterations can be adjusted from 1 to 9. After generating the process flow shown in FIG4e(3), the number of process iterations is reduced by one (for example, 9-1=8). Then, when the business data of process A is received again at the end of the second iteration, it is not discarded, but recorded, and the first node in the third process flow is generated. This process is repeated until 10 process flows are generated and 10 iterations are completed. Finally, the 10 generated process flows are merged to obtain a merged process flow. Of course, when the IoT platform 201 is executing the second iteration in this round, it can also adjust the number of process iterations from 1 to 10 times as expected by the tenant, thereby discarding the generated process flow chart shown in Figure 4e (2), and re-generating 10 process flows based on the reset number of process iterations (10 times) based on the received business data, and merging them.

[0295] Here, the scenario of Figure 4e is used as an example for illustration. This solution is also applicable to other scenarios and the adjustment of other process information, which will not be described in detail here.

[0296] Scene 6

[0297] Similar to the process in FIG4g , FIG4h is a schematic diagram of another exemplary process flow.

[0298] In this scenario 6, the tenant-configured process information may also include alarm conditions for process parameters of at least one process (e.g., a threshold range for normal values, etc.). For example, the normal value range for process E is 4.8 to 5.2. As shown in FIG4h , the IoT platform 201 determines that the updated value of parameter e for process E is 5.7, which is not within the normal value range and therefore meets the alarm condition. When displaying the process flow, the IoT platform 201 may display node E representing process E with a gray line to distinguish it from the display of other nodes that do not meet the alarm condition. In this way, when the tenant browses the process flow chart shown in FIG4h generated by the IoT platform 201 through the user interface, they can intuitively and quickly find the abnormal process and its abnormal measurement data.

[0299] Scene 7

[0300] The process flow generated by the methods of various embodiments of the present application, such as the process flow shown in Figure 4h, can support tenants to perform secondary editing of the process flow chart through the client 300, such as adjusting the logical order between nodes (representing processes), such as swapping the positions of node B and node C so that process C is executed after process A, and process B is executed after process C; in addition, the tenant can also adjust the mapping of the nodes in the generated process flow chart through the client (here the mapping of the process is represented by a circle graphic), such as adjusting the mapping of node A from a circle pattern to a triangle pattern, etc. In this way, the Internet of Things platform 201 of the present application can respond to the tenant's editing operations to adjust the logical order, mapping, and other contents of the generated process flow.

[0301] In the above-mentioned scenarios A, B, 1 to 7, the implementation process of the method of the present application is explained for different situations respectively. In actual applications, any of the above scenarios can be flexibly combined according to needs to form new technical solutions, which are all within the scope of the method provided by the present application.

[0302] The following takes the beer production business as an example to illustrate the implementation process of the above method of this application.

[0303] FIG5 is a schematic diagram showing an exemplary process of beer production.

[0304] As shown in Figure 5, a complete beer production process may include: the process of crushing malt, the process of adding water for gelatinization, the process of filtering, the process of boiling with hops and sugar, the process of vortex sedimentation, the process of cooling, the process of fermentation, the process of maturation, the process of re-filtration, and the final process of packaging, after which the packaged beer can be manually distributed.

[0305] In order to generate a complete and accurate process flow for the above-mentioned process of beer production, the method of the present application can receive business data reported by the beer production factory through the edge device. The business data is the data generated by the business equipment (for example, the business equipment of the crushing process is the crushing equipment) when performing the business.

[0306] Table 7 exemplarily shows the business data of each process (the various processes shown in FIG5 ) continuously reported to the Internet of Things platform 201 through the edge device of the beer production process factory.

[0307] Table 7

[0308] Among them, the "time" in each business data in Table 7 represents the process execution time of the process, and the "fields" represents the process parameters, which may include measurement data, production batches, production lines, etc. Table 7 only shows the measurement data. For example, the measurement data of the crushing process is "fineness" = 0.35, where "fineness" represents fineness. Similarly, the interpretation of other measurement data is as follows: "thickness" in Table 7 represents the gelatinization concentration, "filter_rate" represents the filtration rate, "boil_time" represents the boiling time (here 60s), "settle_time" represents the time taken for vortex sedimentation, "cool_time" represents the cooling time, "fermentation_time" represents the fermentation time, "maturation_time" represents the maturity time, and "packaging_rate" represents the packaging rate.

[0309] In addition, the method of the present application can also receive process information of the beer production business, and the process information is shown in Table 8.

[0310] Table 8

[0311] Then, the method of the present application can generate the process flow chart shown in FIG6 based on the process information shown in Table 8 and the received business data shown in Table 7.

[0312] The process flow diagram can present the logical sequence between the various processes (indicated by arrows). In addition, the process flow diagram can also display the process execution time and measurement data of each process.

[0313] In this way, the method of the present application can draw a process flow chart in real time, dynamically and accurately based on real-time business data.

[0314] As shown in Figure 7, an embodiment of the present application provides a management platform 800. The management platform 800 can be run on a management device, and the management platform is connected to a business device, and the business device is used to execute a business, and the business includes multiple processes. Referring to Figure 7, the management platform 800 includes: an acquisition module 801, used to obtain process information of the business, and the process information includes the starting process identifier and process end condition of the starting process in the multiple processes; a receiving module 802, used to receive multiple business data sent by the business device during operation, and each business data in the multiple business data includes the process identifier of one process in the multiple processes; a generation module 803, used to generate a process flow based on the multiple business data and the process information, and the process flow includes the execution order between the multiple processes.

[0315] In a possible implementation, the management platform 800 is a cloud management platform, which is used to manage the infrastructure for providing cloud services. The infrastructure includes multiple cloud data centers located in different regions, with at least one cloud data center located in each region.

[0316] In one possible embodiment, the generation module 803 is specifically used to: determine the target business data that matches the process information among the multiple business data based on the business data and the process information, wherein the target business data includes the first business data whose process identifier matches the starting process identifier, and the second business data received after the first business data and meets the process end condition; generate a process flow based on the target business data, wherein the starting process of the process flow is the first process indicated by the first process identifier in the first business data, and the ending process of the process flow is the second process indicated by the second process identifier in the second business data.

[0317] In a possible embodiment, the multiple business data include third business data, wherein the third business data is business data received between the first business data and the second business data; the generation module 803 is specifically used to: determine the receiving time sequence of the first business data, the second business data, and the third business data based on the target business data and the third business data; based on the receiving time sequence, generate a process flow, wherein the starting process of the process flow is the first process indicated by the first process identifier in the first business data, the ending process of the process flow is the second process indicated by the second process identifier in the second business data, and the intermediate process of the process flow is the third process indicated by the third process identifier in the third business data.

[0318] In a possible embodiment, each of the multiple business data also includes the process execution time of a process among the multiple processes, and the multiple business data also include third business data, wherein the process execution time of the third process indicated by the third process identifier in the third business data is between the process execution time of the first process indicated by the first process identifier in the first business data and the process execution time of the second process indicated by the second process identifier in the second business data; the generation module 803 is specifically used to: determine the order of the process execution times of the received first business data, the second business data, and the third business data based on the target business data and the third business data; generate a process flow based on the order of the process execution times, wherein the starting process of the process flow is the first process indicated by the first process identifier, the ending process of the process flow is the second process indicated by the second process identifier, and the intermediate process of the process flow is the third process indicated by the third process identifier.

[0319] In a possible implementation, the process flow further includes the process execution time of each of the multiple processes.

[0320] In one possible embodiment, the process end condition includes the process flow duration, and the generation module 803 is specifically used to: when the timing duration reaches the process flow duration, the business data other than the first business data that is received most recently or has the latest process execution time is determined as the second business data that meets the process end condition; wherein, the timing duration is the timing duration starting from the first moment, wherein the first moment is the moment of determining the first business data.

[0321] In a possible implementation, the process end condition includes a process termination identifier, and the generation module is specifically configured to determine the second business data whose process identifier matches the process termination identifier.

[0322] In a possible implementation, the process information also includes the number of process iterations N, where N≥2 and N is an integer. The generation module 803 is specifically used to: generate M process flows based on the target business data and the process information, where 1≤M≤N and M is an integer; and merge nodes with the same execution order between the M process flows to obtain an iterative process flow.

[0323] In a possible implementation, the business data further includes process parameters, and the process flow further includes the process parameters of each of the multiple processes.

[0324] In a possible implementation, the process parameters include at least one of the following: process measurement data, production batch, and production line.

[0325] The effects of the management platforms of the above-mentioned embodiments are similar to the effects of the process flow management methods of the above-mentioned embodiments, and will not be described in detail here.

[0326] Among them, the acquisition module 801, the receiving module 802, and the generation module 803 can all be implemented by software or by hardware. For example, the implementation of the acquisition module 801 is described below using the acquisition module 801 as an example. Similarly, the implementation of the receiving module 802 and the generation module 803 can refer to the implementation of the acquisition module 801.

[0327] As an example of a software functional unit, the acquisition module 801 may include code running on a computing instance. The computing instance may include at least one of a physical host (management device), a virtual machine, and a container. Furthermore, the computing instance may be one or more. For example, the acquisition module 801 may include code running on multiple hosts / virtual machines / containers. It should be noted that the multiple hosts / virtual machines / containers used to run the code may be distributed in the same region (region) or in different regions. Furthermore, the multiple hosts / virtual machines / containers used to run the code may be distributed in the same availability zone (AZ) or in different availability zones, each availability zone including one data center or multiple geographically close data centers. Typically, a region may include multiple availability zones.

[0328] Similarly, multiple hosts / virtual machines / containers running the code can be distributed within the same virtual private cloud (VPC) or across multiple VPCs. Typically, a VPC is set up within a region. Cross-region communication between two VPCs within the same region, or between VPCs in different regions, requires a communication gateway within each VPC to interconnect the VPCs.

[0329] As an example of a hardware functional unit, the acquisition module 801 may include at least one management device, such as a server. Alternatively, the acquisition module 801 may be implemented using an application-specific integrated circuit (ASIC) or a programmable logic device (PLD). The PLD may be a complex programmable logical device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL), or any combination thereof.

[0330] The multiple management devices included in the above management platform can be distributed in the same region or in different regions. The multiple management devices included in the above management platform can be distributed in the same AZ or in different AZs. Similarly, the multiple management devices included in the above management platform can be distributed in the same VPC or in multiple VPCs. The multiple management devices can be any combination of management devices such as servers, ASICs, PLDs, CPLDs, FPGAs, and GALs.

[0331] It should be noted that, in other embodiments, the acquisition module 801 can be used to execute any step in the process flow management method, the receiving module 802 and the generating module 803 can be used to execute any step in the process flow management method, and the steps that the acquisition module 801, the receiving module 802 and the generating module 803 are responsible for implementing can be specified as needed. The full functions of the management platform can be realized by respectively implementing different steps in the process flow management method through the acquisition module 801, the receiving module 802 and the generating module 803.

[0332] The above describes in detail the method, device and system of the embodiments of the present application. In order to facilitate better implementation of the above solutions of the embodiments of the present application, correspondingly, related equipment for cooperating in implementing the above solutions is also provided below.

[0333] The present application also provides a management device 900. The management device 900 can be connected to a business device, and the business device is used to execute a business, and the business includes multiple processes. As shown in Figure 8, the management device 900 includes: a bus 902, a processor 904, a memory 906, and a communication interface 909. The processor 904, the memory 906, and the communication interface 909 communicate with each other via the bus 902. The management device 900 can be a server or a terminal device. It should be understood that the present application does not limit the number of processors and memories in the management device 900.

[0334] Bus 902 may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, among others. Buses may be classified as address buses, data buses, control buses, and the like. For ease of illustration, FIG8 illustrates a single bus line, but this does not imply a single bus or type of bus. Bus 902 may include a path for transmitting information between various components of management device 900 (e.g., memory 906, processor 904, and communication interface 909).

[0335] The processor 904 may include any one or more processors such as a central processing unit (CPU), a graphics processing unit (GPU), a microprocessor (MP), or a digital signal processor (DSP).

[0336] The memory 906 may include volatile memory, such as random access memory (RAM). The memory 906 may also include non-volatile memory, such as read-only memory (ROM), flash memory, hard disk drive (HDD), or solid state drive (SSD).

[0337] The memory 906 stores executable program code, and the processor 904 executes the executable program code to respectively implement the functions of the aforementioned acquisition module 801, receiving module 802, and generation module 803, thereby implementing the process flow management method. In other words, the memory 906 stores instructions for executing the process flow management method.

[0338] The communication interface 909 uses a transceiver module such as, but not limited to, a network interface card or a transceiver to implement communication between the management device 900 and other devices or a communication network.

[0339] Embodiments of the present application also provide a management device cluster. The management device cluster includes at least one management device. The management device can be a server, such as a central server, an edge server, or a local server in a local data center. In some embodiments, the management device can also be a terminal device such as a desktop computer, a laptop computer, or a smartphone. Each management device is connected to a service device, and the service device is used to execute a service, which includes multiple processes.

[0340] As shown in Figure 9, the management device cluster includes at least one management device 1000. The memory 1006 in one or more management devices 1000 in the management device cluster may store the same instructions for executing the process flow management method.

[0341] In some possible implementations, the memory 1006 of one or more management devices 1000 in the management device cluster may also store partial instructions for executing the process flow management method. In other words, the combination of one or more management devices 1000 can jointly execute the instructions for executing the process flow management method.

[0342] It should be noted that the memory 1006 in different management devices 1000 in the management device cluster can store different instructions, each for executing a portion of the functions of the management platform. In other words, the instructions stored in the memory 1006 in different management devices 1000 can implement the functions of one or more of the aforementioned acquisition module 801, receiving module 802, and generation module 803.

[0343] In some possible implementations, the memory 1006 of one or more management devices 1000 in the management device cluster may also store partial instructions for executing the process flow management method. In other words, the combination of one or more management devices 1000 can jointly execute the instructions for executing the process flow management method.

[0344] As shown in FIG9 , the management device 1000 includes a bus 1002 , a processor 1004 , a memory 1006 , and a communication interface 1008 . The processor 1004 , the memory 1006 , and the communication interface 1008 communicate with each other via the bus 1002 .

[0345] This embodiment of the present application also provides a management device cluster. This management device cluster may include multiple management devices, each of which is connected to a service device. The service device is used to execute a service, and the service includes multiple processes. Please refer to Figure 10 below, which is another structural diagram of a management device cluster for the process flow management method of an embodiment of the present application. As shown in Figure 10, management device 1100C and management device 1100D are connected via communication interface 309.

[0346] The management device 1100C includes a bus 307 , a processor 308 , a memory 306 , and a communication interface 309 . The processor 308 , the memory 306 , and the communication interface 309 communicate with each other via the bus 307 .

[0347] The management device 1100D includes a bus 307 , a processor 308 , a memory 306 , and a communication interface 309 . The processor 308 , the memory 306 , and the communication interface 309 communicate with each other via the bus 307 .

[0348] The memory 306 in the management device 1100C stores instructions for executing the functions of the receiving module 802. The memory 306 in the management device 1100D stores instructions for executing the functions of the acquiring module 801 and the generating module 803. In other words, the memory 306 of the management device 1100C and the memory 306 of the management device 1100D jointly store instructions for the device to execute the process flow management method.

[0349] The connection method between the management device clusters shown in Figure 10 can be based on the fact that the process flow management method provided in this application requires a large amount of data transmission to the receiving module 802. Considering the data transmission volume and to avoid the management device 1100C from experiencing an overload in the calculation, the functions of the acquisition module 801 and the generation module 803 are delegated to the management device 1100D.

[0350] It should be understood that the functions of the management device 1100C shown in FIG10 may also be completed by multiple management devices 1000. Similarly, the functions of the management device 1100D may also be completed by multiple management devices 1000.

[0351] An embodiment of the present application also provides a management device cluster. The management device cluster may include at least one management device, each of which is connected to a business device, and the business device is used to perform business, and the business includes multiple processes. Please refer to Figure 11 below, which is another structural diagram of the management device cluster of the process flow management method of an embodiment of the present application. In some possible implementations, one or more management devices in the management device cluster can be connected through a network. The network can be a wide area network or a local area network, etc. Figure 11 shows a possible implementation. As shown in Figure 11, two management devices 1100A and 1100B are connected through a network. Specifically, the communication interface 1108 in each management device is connected to the network.

[0352] As shown in Figure 11 , the management device 1100A includes a bus 1102, a processor 1104, a memory 1106, and a communication interface 1108. The processor 1104, the memory 1106, and the communication interface 1108 communicate with each other via the bus 1102.

[0353] The management device 1100B includes a bus 1102 , a processor 1104 , a memory 1106 , and a communication interface 1108 . The processor 1104 , the memory 1106 , and the communication interface 1108 communicate with each other via the bus 1102 .

[0354] In this type of possible implementation, the memory 1106 in the management device 1100A stores instructions for executing the functions of the acquisition module 801 . Meanwhile, the memory 1106 in the management device 1100B stores instructions for executing the functions of the receiving module 802 and the generating module 803 .

[0355] The connection method between the management device clusters shown in Figure 11 can be based on the fact that the process flow management method provided in this application requires a large amount of data transmission and needs to be connected through a network. These functions of the acquisition module 801 are relatively independent. In order to optimize the storage and computing performance, it is considered to entrust the functions of the receiving module 802 and the generating module 803 to the management device 1100B for execution.

[0356] It should be understood that the functions of the management device 1100A shown in FIG11 may also be completed by multiple management devices 1100. Similarly, the functions of the management device 1100B may also be completed by multiple management devices 1100.

[0357] The present application also provides another management device cluster. The connection relationship between the management devices in this management device cluster can be similar to the connection methods of the management device clusters described in Figures 8 and 11 . However, the memory 1106 in one or more management devices 1100 in this management device cluster can store the same instructions for executing the process flow management method.

[0358] In some possible implementations, the memory 1106 of one or more management devices 1100 in the management device cluster may also store partial instructions for executing the process flow management method. In other words, the combination of one or more management devices 1100 can jointly execute the instructions for executing the process flow management method.

[0359] It should be noted that the memory 1106 in different management devices 1100 in the management device cluster can store different instructions for executing part of the functions of the management platform. In other words, the instructions stored in the memory 1106 in different management devices 1100 can implement the functions of one or more management platforms.

[0360] The present application also provides a computer program product containing instructions. The computer program product may be software or a program product containing instructions that can be run on a management device or stored in any available medium. When the computer program product is run on at least one management device, it causes the at least one management device to execute the process flow management method described in the above embodiments, wherein the management device is connected to a service device, the service device is used to execute a service, and the service includes multiple processes.

[0361] An embodiment of the present application also provides a computer-readable storage medium. The computer-readable storage medium can be any available medium that can be stored by the management device or a data storage device such as a data center that contains one or more available media. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a tape), an optical medium (for example, a DVD), or a semiconductor medium (for example, a solid-state hard disk), etc. The computer-readable storage medium includes instructions that instruct the management device to execute the process flow management method in the above embodiment, wherein the management device cluster is connected to a business device, the business device is used to execute a business, and the business includes multiple processes.

[0362] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the protection scope of the technical solutions of the embodiments of the present application.

Claims

1. A process flow management method, characterized in that: The method is applied to a management platform, the management platform running on a management device, the management platform connected to a business device, the business device used to execute a business, the business including multiple processes, the method comprising: Acquire process information of the business, where the process information includes a starting process identifier and a process end condition of a starting process among the multiple processes; receiving a plurality of business data sent by the business device during operation, each of the plurality of business data including a process identifier of a process among the plurality of processes; A process flow is generated based on the plurality of business data and the process information, where the process flow includes an execution sequence of the plurality of processes.

2. The method according to claim 1, characterized in that Generating a process flow based on the plurality of business data and the process information includes: Determining, based on the multiple business data and the process information, target business data from the multiple business data that matches the process information, wherein the target business data includes first business data whose process identifier matches the starting process identifier, and second business data received after the first business data and that meets the process end condition; A process flow is generated based on the target business data, wherein the starting process of the process flow is the first process indicated by the first process identifier in the first business data, and the ending process of the process flow is the second process indicated by the second process identifier in the second business data.

3. The method according to claim 2, characterized in that The plurality of business data includes third business data, wherein the third business data is business data received between the first business data and the second business data; and generating a process flow based on the target business data further includes: Determining a receiving time sequence of the first service data, the second service data, and the third service data based on the target service data and the third service data; Based on the receiving time sequence, a process flow is generated, wherein the starting process of the process flow is the first process indicated by the first process identifier in the first business data, the ending process of the process flow is the second process indicated by the second process identifier in the second business data, and the intermediate process of the process flow is the third process indicated by the third process identifier in the third business data.

4. The method according to claim 2, characterized in that Each of the plurality of business data further includes a process execution time of a process among the plurality of processes, and the plurality of business data further includes third business data, wherein the process execution time of a third process indicated by a third process identifier in the third business data is between the process execution time of a first process indicated by a first process identifier in the first business data and the process execution time of a second process indicated by a second process identifier in the second business data; generating a process flow based on the target business data includes: Determining, based on the target business data and the third business data, a sequence of process execution times of the received first business data, the second business data, and the third business data; Based on the sequence of the process execution time, a process flow is generated, wherein the starting process of the process flow is the first process indicated by the first process identifier, the ending process of the process flow is the second process indicated by the second process identifier, and the intermediate process of the process flow is the third process indicated by the third process identifier.

5. The method according to claim 4, characterized in that The process flow further includes the process execution time of each of the plurality of processes.

6. The method according to any one of claims 2 to 5, characterized in that The process end condition includes the process duration, and determining target business data matching the process information among the plurality of business data includes: When the timing duration reaches the process duration, determining the business data other than the first business data that is received most recently or has the latest process execution time as the second business data that meets the process end condition; The timing duration is the timing duration starting from a first moment, wherein the first moment is the moment when the first service data is determined.

7. The method according to any one of claims 2 to 5, characterized in that The process end condition includes a termination process identifier, and determining target business data matching the process information among the plurality of business data includes: Determine second business data whose process identifier matches the termination process identifier.

8. The method according to any one of claims 2 to 7, characterized in that The process information also includes the number of process iterations N, where N≥2, and N is an integer. The process flow generated based on the target business data also includes: Based on the target business data and the process information, generate M process flows, where 1≤M≤N, and M is an integer; Nodes with the same execution order among the M process flows are merged to obtain an iterative process flow.

9. The method according to any one of claims 1 to 8, characterized in that The business data further includes process parameters, and the process flow further includes the process parameters of each of the multiple processes.

10. The method according to claim 9, characterized in that The process parameters include at least one of the following: process measurement data, production batch, and production line.

11. A management platform, characterized in that: The management platform runs on a management device, and the management platform is connected to a business device. The business device is used to execute a business, and the business includes multiple processes. The management platform includes: An acquisition module, configured to acquire process information of the business, wherein the process information includes a starting process identifier and a process end condition of a starting process among the multiple processes; a receiving module, configured to receive a plurality of business data sent by the business device during operation, wherein each of the plurality of business data includes a process identifier of one of the plurality of processes; A generation module is used to generate a process flow based on the multiple business data and the process information, where the process flow includes an execution sequence between the multiple processes.

12. The management platform according to claim 11, characterized in that: The generation module is specifically used for: Determining, based on the multiple business data and the process information, target business data from the multiple business data that matches the process information, wherein the target business data includes first business data whose process identifier matches the starting process identifier, and second business data received after the first business data and that meets the process end condition; A process flow is generated based on the target business data, wherein the starting process of the process flow is the first process indicated by the first process identifier in the first business data, and the ending process of the process flow is the second process indicated by the second process identifier in the second business data.

13. The management platform according to claim 12, characterized in that: The plurality of business data includes third business data, wherein the third business data is business data received between the first business data and the second business data; and the generating module is specifically configured to: Determining a receiving time sequence of the first service data, the second service data, and the third service data based on the target service data and the third service data; Based on the receiving time sequence, a process flow is generated, wherein the starting process of the process flow is the first process indicated by the first process identifier in the first business data, the ending process of the process flow is the second process indicated by the second process identifier in the second business data, and the intermediate process of the process flow is the third process indicated by the third process identifier in the third business data.

14. The management platform according to claim 12, characterized in that: Each of the plurality of business data further includes a process execution time of one of the plurality of processes, and the plurality of business data further includes third business data, wherein the process execution time of the third process indicated by the third process identifier in the third business data is between the process execution time of the first process indicated by the first process identifier in the first business data and the process execution time of the second process indicated by the second process identifier in the second business data; the generating module is specifically configured to: Determining, based on the target business data and the third business data, a sequence of process execution times of the received first business data, the second business data, and the third business data; Based on the order of the process execution time, a process flow is generated, wherein the starting process of the process flow is the first process identifier The first process indicated by the second process identifier, the terminal process of the process flow is the second process indicated by the second process identifier, and the intermediate process of the process flow is the third process indicated by the third process identifier.

15. The management platform according to claim 14, characterized in that: The process flow further includes the process execution time of each of the plurality of processes.

16. The management platform according to any one of claims 12 to 15, characterized in that: The process end condition includes the process duration, and the generation module is specifically used to: When the timing duration reaches the process duration, determining the business data other than the first business data that is received most recently or has the latest process execution time as the second business data that meets the process end condition; The timing duration is the timing duration starting from a first moment, wherein the first moment is the moment when the first service data is determined.

17. The management platform according to any one of claims 12 to 15, characterized in that: The process end condition includes a process termination identifier, and the generating module is specifically configured to determine the second business data whose process identifier matches the process termination identifier.

18. The management platform according to any one of claims 12 to 17, characterized in that: The process information also includes the number of process iterations N, where N≥2 and N is an integer. The generation module is specifically configured to: Based on the target business data and the process information, generate M process flows, where 1≤M≤N, and M is an integer; Nodes with the same execution order among the M process flows are merged to obtain an iterative process flow.

19. The management platform according to any one of claims 11 to 18, characterized in that: The business data further includes process parameters, and the process flow further includes the process parameters of each of the multiple processes.

20. The management platform according to claim 19, characterized in that: The process parameters include at least one of the following: process measurement data, production batch, and production line.

21. A management device cluster, characterized in that: The system comprises at least one management device, each management device is connected to a service device, the service device is used to execute a service, the service includes a plurality of processes, and each management device includes a processor and a memory; The processor of the at least one management device is configured to execute instructions stored in a memory of the at least one management device, so that the management device cluster executes the method according to any one of claims 1 to 10.

22. A computer program product comprising instructions, characterized in that When the instruction is executed by the management device cluster, the management device cluster executes the method according to any one of claims 1 to 10, wherein the management device cluster is connected to a service device, the service device is used to execute a service, and the service includes multiple processes.

23. A computer-readable storage medium, characterized in that The method comprises computer program instructions, and when the computer program instructions are executed by a management device cluster, the management device cluster executes the method according to any one of claims 1 to 10, wherein the management device cluster is connected to a business device, the business device is used to execute a business, and the business includes multiple processes.

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