Method and system for transferring materials across workshops based on prediction

Abstract

The present application relates to a prediction-based cross-workshop material transfer method and system, the method comprising obtaining predicted processing material transfer information based on a preset processing feature recognition index in combination with current processing task information; determining the original material processing management library and the destination material processing management library according to the predicted processing material transfer information, and determining the original material processing management batch that needs to be transferred; collecting processing production identification information, combining the processing production identification information and the transfer scheme variable information, and generating material transfer task information; based on the material transfer task information, issuing a material transfer request to the logistics control system, and establishing a new destination material processing management batch in the destination material processing management library; and executing the transfer task. The present application has the effects of improving the accuracy and efficiency of material transfer, optimizing the logistics process, improving the execution efficiency of transfer tasks, enhancing the flexibility and response speed of logistics, and ensuring the smooth execution of transfer tasks.

Description

Technical Field

[0001] The present invention relates to the technical field of material transfer in production workshops, and in particular to a prediction-based inter-workshop material transfer method and system. Background Art

[0002] At present, in the modern production process, material distribution in the processing workshop is a key link to ensure production continuity and efficiency. Traditional material distribution methods often rely on manual management and operation, which is not only inefficient, but also prone to errors and difficult to meet complex and changing production needs. With the development of information technology, processing workshops have gradually introduced various automation systems to improve the accuracy and efficiency of material distribution.

[0003] However, existing material distribution methods still have some problems when dealing with material transfers across processing workshops. On the one hand, due to the information island phenomenon between different processing workshops, material distribution often lacks unified scheduling and management, resulting in low efficiency in the execution of transfer tasks. On the other hand, when materials need to be transferred between different processing workshops, complex collaborative processing is often required to ensure the accuracy and timeliness of material transfer. However, existing material distribution methods often have lags in achieving collaborative processing, making it difficult to quickly respond to production changes. Summary of the invention

[0004] In order to improve the accuracy and efficiency of material transfer, optimize the logistics process, improve the execution efficiency of transfer tasks, enhance the flexibility and response speed of logistics, and ensure the smooth execution of transfer tasks, the present application provides a prediction-based cross-workshop material transfer method, system, computer equipment and storage medium.

[0005] In the first aspect, the above-mentioned invention objective of the present application is achieved through the following technical solutions:

[0006] A method for transferring materials across workshops based on prediction is applied to a cloud system of a processing workshop. The method for transferring materials across workshops based on prediction includes:

[0007] Acquire current processing task information, predict material processing progress based on a preset processing feature recognition index and in combination with the current processing task information, and obtain predicted processing material transfer information, wherein the predicted processing material transfer information includes transfer scheme variable information;

[0008] Determine the original material processing management library and the target material processing management library according to the predicted processing material transfer information, and determine the original material processing management batch that needs to be transferred from the original material processing management library;

[0009] Collecting processing and production identification information, combining the processing and production identification information with the transfer scheme variable information, and using the original material processing management batch, the original material processing management library, and the destination material processing management library to generate material transfer task information;

[0010] Based on the material transfer task information, a material transfer request is issued to the logistics control system, wherein the material transfer request indicates that the logistics control system performs collaborative processing based on the material transfer task information, and after the collaborative processing is completed, a new target material processing management batch is established in the target material processing management library;

[0011] For the material transfer task information, when the target logistics object corresponding to the material transfer task information is not retrieved in the destination material processing management batch, the target logistics object is obtained from the original material processing management batch and loaded into the destination material processing management batch to execute the transfer task.

[0012] By adopting the above technical solution, before starting the transfer, the processing progress of each workshop is predicted through the current processing task information of each workshop in the entire factory, and the predicted material transfer information is generated according to the predicted processing progress of each workshop. In this way, in the subsequent processing process, the transfer task can be directly executed according to the predicted material transfer information, which ensures the rapid response of material transfer, improves the execution efficiency of transfer tasks, enhances the flexibility and response speed of logistics, and by determining the original material processing management library and the destination material processing management library, as well as the original material processing management batches that need to be transferred, it realizes the precise distribution control of materials between processing workshops, improves the accuracy and efficiency of material management, and reduces the possibility of material distribution errors.

[0013] In a preferred example, the present application can be further configured as follows: the processing feature recognition index is generated by:

[0014] Obtain historical material processing task information and historical material production monitoring identification information;

[0015] Respectively analyzing the historical material processing task information and the historical material production monitoring identification information to obtain material processing flow feature information and material monitoring identification feature information;

[0016] Generate a process feature index based on the material processing process feature information, and generate a monitoring identification feature index based on the material monitoring identification feature information;

[0017] Associating the process feature index with the monitoring identification feature index to obtain a processing feature identification index;

[0018] Determining the reliability of the process feature index and the monitoring identification feature index, and generating transfer scheme variable information according to the reliability;

[0019] The transfer scheme dependent information is associated with the processing feature identification index.

[0020] By adopting the above technical solution, the processing feature recognition index refers to the index information used to predict the workshop processing progress according to the characteristics of the workshop processing tasks. By respectively analyzing the historical material processing task information and the historical material production monitoring and identification information, the process characteristics and monitoring and identification characteristics of the workshop processing tasks are judged respectively. The process characteristics include whether there is backtracking processing, whether there is a self-inspection process, and whether there is a stop and wait step, etc. The monitoring and identification characteristics refer to the processing characteristics determined by monitoring and identifying the processing quality of the material during the material processing process, for example, additional processing steps such as grinding, rust removal and painting required during material processing, as well as additional visual recognition steps, so as to judge the difference between these characteristics and normal processing steps and the time-consuming difference from normal processing steps, so as to judge the difference in processing tasks caused by the appearance of these characteristics in the current actual processing tasks, and then realize accurate prediction of processing progress.

[0021] In a preferred example, the present application may be further configured as follows: generating a process feature index according to the material processing process feature information, and generating a monitoring identification feature index according to the material monitoring identification feature information, including:

[0022] According to the material processing flow characteristic information, combined with the historical material processing task information, the processing time and the probability of occurrence of each characteristic flow are determined to obtain a first time and a first probability, wherein the first probability corresponds to the distinguished material processing task information;

[0023] Generate a process feature index according to the first duration, the first probability and corresponding material processing task information;

[0024] Extracting abnormal material monitoring identification feature information from the material monitoring identification feature information;

[0025] According to the abnormal material monitoring identification feature information, combined with the historical material production monitoring identification information, determine the increase duration and probability of each abnormal production monitoring data, obtain a second duration and a second probability, and the second probability corresponds to the different production monitoring identification information;

[0026] A monitoring identification feature index is generated according to the second duration, the second probability and the corresponding production monitoring identification information.

[0027] By adopting the above technical solution, when judging the process characteristics of the workshop processing tasks, it is not only necessary to analyze the separate processing flow of each independent workshop, but also to comprehensively analyze the processing tasks of all workshops in the entire factory at that time represented by the historical material processing task information, so as to judge which processes appear in the current material processing task information, which will lead to the occurrence of characteristic processes, as well as the probability of occurrence and the duration of the processing flow after occurrence. This information is associated together, so that when predicting, it is convenient to query the associated index through the current processing task information to realize prediction, thereby improving the prediction speed and enhancing the flexibility and response speed of logistics.

[0028] In a preferred example, the present application may be further configured as follows: determining the original material processing management library and the target material processing management library according to the predicted processing material transfer information includes:

[0029] Based on the current processing task information, determining the processing execution cost parameters of each material processing management library;

[0030] Based on the processing execution cost parameters of each material processing management library and the predicted processing material transfer information, an original material processing management library and a target material processing management library are selected from the multiple material processing management libraries, wherein the processing execution cost parameter of the target material processing management library is smaller than that of the original material processing management library.

[0031] By adopting the above technical solution, the processing execution cost parameter refers to the efficiency and cost-effectiveness cost when executing material processing tasks. The lower the cost parameter, the higher the efficiency and cost-effectiveness of the library when executing material processing tasks. Therefore, the processing execution cost parameters of each material processing management library are calculated, and based on the processing execution cost parameters of each material processing management library, combined with the predicted processing material transfer information, the original material processing management library and the destination material processing management library are determined to ensure that the material can achieve the best efficiency and cost-effectiveness during the transfer process.

[0032] In a preferred example, the present application may be further configured as follows: based on the processing execution cost parameters of each material processing management library and the predicted processing material transfer information, an original material processing management library and a target material processing management library are selected from a plurality of the material processing management libraries, including:

[0033] Arranging the processing execution cost parameters of each material processing management library in a first descending order;

[0034] Arranging the predicted processing material transfer information of each material processing management library in a second descending order;

[0035] According to a preset sorting selection rule, as well as the first descending order and the second descending order, an original material processing management library and a target material processing management library are selected from the plurality of material processing management libraries.

[0036] By adopting the above technical solution, after the processing execution cost parameters of each material processing management library are generated, a first descending order is performed to facilitate the selection of a material processing management library with a lower or higher processing execution cost parameter. In addition, a second descending order is performed on the predicted processing material transfer information of each material processing management library. The second descending order refers to a descending order based on the predicted material transfer time point, that is, the transfer order of materials in each workshop when there is no difference between the actual processing and the prediction. Therefore, it is necessary to comprehensively determine the current original material processing management library and the target material processing management library by combining the first descending order and the second descending order. For example, if the lowest and second lowest material processing management libraries are selected according to the first descending order, and the lowest material processing management library is selected according to the second descending order The lowest and second lowest material processing management warehouses are the predicted material processing management warehouses that will move materials first. At this time, the lowest and second lowest material processing management warehouses can be directly used as the original material processing management warehouse and the destination material processing management warehouse. If the lowest and second lowest material processing management warehouses in the second descending order are not the material processing management warehouses that will move materials first, the accuracy of the prediction needs to be considered. When the accuracy of the prediction is high and the material transfer order of the material processing management warehouse with the lowest and second lowest processing execution cost parameters is third or fourth, the lowest and second lowest material processing management warehouses can also be directly used as the original material processing management warehouse and the destination material processing management warehouse. In this way, more economical and efficient material transfer can be made while considering efficiency and cost-effectiveness.

[0037] In a preferred example, the present application may be further configured as follows: the step of establishing a new target material processing management batch in the target material processing management library includes:

[0038] Obtaining material processing information of the original material processing management batch;

[0039] Creating a copy of the material processing record of the original material processing management batch based on the material processing information of the original material processing management batch;

[0040] A destination material processing management batch having a corresponding relationship to the material processing record copy is established in the destination material processing management library but no actual inventory space is established.

[0041] By adopting the above technical solution, after determining the target material processing management library, it is necessary to establish a target material processing management batch in the target material processing management library to improve material data management. Therefore, the material processing information of the original material processing management batch is obtained, and a new material processing management batch is created in the target material processing management library based on the material processing information of the original material processing management batch. When this new batch is created, a corresponding relationship will be established with the original batch. This relationship may be achieved through batch number, material code or other unique identifier to avoid data confusion.

[0042] In the second aspect, the above invention objective of the present application is achieved through the following technical solutions:

[0043] A prediction-based inter-shop material transfer system, the prediction-based inter-shop material transfer system comprising:

[0044] A processing task acquisition module is used to acquire current processing task information, predict material processing progress based on a preset processing feature recognition index and in combination with the current processing task information, and obtain predicted processing material transfer information, wherein the predicted processing material transfer information includes transfer scheme variable information;

[0045] A management library determination module is used to determine the original material processing management library and the target material processing management library according to the predicted processing material transfer information, and determine the original material processing management batch that needs to be transferred from the original material processing management library;

[0046] A transfer task generation module is used to collect processing and production identification information, combine the processing and production identification information and the transfer scheme variable information, and use the original material processing management batch, the original material processing management library and the target material processing management library to generate material transfer task information;

[0047] A request issuing module, used for issuing a material transfer request to the logistics control system based on the material transfer task information, wherein the material transfer request indicates that the logistics control system performs collaborative processing based on the material transfer task information, and after the collaborative processing is completed, a new target material processing management batch is established in the target material processing management library;

[0048] The task execution module is used to obtain the target logistics object from the original material processing management batch and load it into the destination material processing management batch to execute the transfer task when the target logistics object corresponding to the material transfer task information is not retrieved in the destination material processing management batch.

[0049] Optionally, the prediction-based inter-shop material transfer system further includes:

[0050] The historical information acquisition module is used to obtain historical material processing task information and historical material production monitoring identification information;

[0051] A feature recognition module is used to respectively analyze the historical material processing task information and the historical material production monitoring recognition information to obtain material processing flow feature information and material monitoring recognition feature information;

[0052] A feature analysis module, used to generate a process feature index according to the material processing process feature information, and to generate a monitoring identification feature index according to the material monitoring identification feature information;

[0053] A feature association module, used to associate the process feature index with the monitoring identification feature index to obtain a processing feature identification index;

[0054] A reliability judgment module, used to judge the reliability of the process feature index and the monitoring identification feature index, and generate transfer scheme variable information according to the reliability;

[0055] The variable association module is used to associate the variable information of the transfer scheme with the processing feature identification index.

[0056] In the third aspect, the above invention objective of the present application is achieved through the following technical solutions:

[0057] A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned prediction-based inter-shop material transfer method when executing the computer program.

[0058] In a fourth aspect, the above-mentioned invention objective of the present application is achieved through the following technical solutions:

[0059] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the above-mentioned prediction-based inter-shop material transfer method.

[0060] In summary, the present application includes at least one of the following beneficial technical effects:

[0061] 1. Before the transfer begins, the current processing task information of each workshop in the entire factory is used to predict the processing progress of each workshop, and the predicted material transfer information is generated according to the predicted processing progress of each workshop. In this way, the transfer task can be directly executed according to the predicted material transfer information in the subsequent processing process, ensuring the rapid response of material transfer, improving the execution efficiency of transfer tasks, and enhancing the flexibility and response speed of logistics. In addition, by determining the original material processing management library and the destination material processing management library, as well as the original material processing management batches that need to be transferred, accurate distribution control of materials between processing workshops is achieved, the accuracy and efficiency of material management are improved, and the possibility of material distribution errors is reduced;

[0062] 2. Processing feature identification index refers to the index information used to predict the workshop processing progress according to the characteristics of the workshop processing tasks. By analyzing the historical material processing task information and the historical material production monitoring identification information respectively, the process characteristics and monitoring identification characteristics of the workshop processing tasks are judged respectively. The process characteristics include whether there is backtracking processing, whether there is a self-inspection process, and whether there is a stop waiting step, etc. The monitoring identification feature refers to the processing feature determined by monitoring and identifying the processing quality of the material during the material processing process, such as additional processing steps such as grinding, rust removal and painting, and additional visual recognition steps required for material processing. In this way, the difference between these features and normal processing steps and the difference in time consumption from normal processing steps are judged, so as to judge the difference in processing tasks caused by the appearance of these features in the current actual processing tasks, and then realize the accurate prediction of processing progress;

[0063] 3. When judging the process characteristics of the workshop processing tasks, it is not just about analyzing the separate processing flow of each independent workshop, but a comprehensive analysis of the processing tasks of all workshops in the entire factory at that time represented by the historical material processing task information, so as to determine which processes appear in the current material processing task information, which will lead to the occurrence of characteristic processes, as well as the probability of occurrence and the duration of the processing flow after occurrence. This information is associated together, so that when predicting, it is convenient to query the associated index through the current processing task information to realize prediction, thereby improving the prediction speed and enhancing the flexibility and response speed of logistics. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 is a flow chart of an implementation method of a cross-workshop material transfer method based on prediction in an embodiment of the present application;

[0065] Figure 2 is a flowchart of the method for obtaining the processing feature identification index in the embodiment of the present application;

[0066] Figure 3is a flowchart for implementing S03 of the method for transferring materials between workshops based on prediction in an embodiment of the present application;

[0067] Figure 4 is a flowchart for implementing S20 of the method for transferring materials between workshops based on prediction in an embodiment of the present application;

[0068] Figure 5 is a flowchart for implementing S22 of the method for transferring materials across workshops based on prediction in an embodiment of the present application;

[0069] Figure 6 is a flowchart for implementing S30 of the method for transferring materials between workshops based on prediction in an embodiment of the present application;

[0070] Figure 7 It is a principle block diagram of a device for transferring materials across workshops based on prediction in an embodiment of the present application;

[0071] Figure 8 It is a diagram of the internal structure of a computer device in an embodiment of the present application. DETAILED DESCRIPTION

[0072] In order to enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments 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 the field without creative work should fall within the scope of protection of the present application.

[0073] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0074] In one embodiment, if Figure 1As shown, the present application discloses a cross-workshop material transfer method based on prediction, which is applied to a processing workshop cloud system. It should be understood that in other embodiments, the order of some steps in the cross-processing workshop material distribution method can be exchanged with each other according to actual needs, or some steps can be omitted or deleted. The cross-workshop material transfer method based on prediction specifically includes the following steps:

[0075] S10: obtaining current processing task information, predicting material processing progress based on a preset processing feature recognition index and in combination with the current processing task information, and obtaining predicted processing material transfer information, wherein the predicted processing material transfer information includes transfer scheme variable information.

[0076] In this embodiment, the current processing task information refers to the current processing task information of each workshop in the entire factory. The processing feature identification index refers to the index information used to predict the processing progress of the workshop according to the features of the processing task of the workshop.

[0077] Specifically, before starting the transfer, the factory operators will formulate a production task plan for each workshop. Therefore, when the factory starts operating production, it obtains the current processing task information of each workshop in the entire factory, that is, the current processing task information. In order to be able to respond quickly when material transfer is needed and quickly realize material transfer based on the processing workshop cloud system, the specific circumstances of the required material transfer can be predicted in advance, so as to respond quickly when material transfer is actually needed. Therefore, the preset processing feature identification index for predicting the workshop processing progress according to the characteristics of the workshop's processing tasks is extracted, and the preset processing feature identification index is queried through the current processing task information to predict the processing progress of each workshop, and according to the processing progress of each workshop, the time when material transfer is required and the material information that needs to be transferred are judged to obtain the predicted processing material transfer information. In addition, the preset processing feature identification index also includes transfer plan variable information, which refers to information used to change the material transfer plan when the actual processing progress of the workshop is different from the predicted processing progress of the workshop. The transfer plan variable information includes plan variable information when the actual processing progress of the workshop is different from the predicted processing progress of the workshop. Because the predicted processing material transfer information at this time is obtained by prediction, if an emergency occurs in actual production, it will cause the processing progress of the workshop to change. Therefore, when the preset processing feature identification index is queried through the current processing task information, the transfer plan variable information associated with the processing feature identification index will be extracted together and associated with the predicted processing material transfer information, so as to quickly change the material transfer plan in actual production, thereby enhancing the flexibility and response speed of logistics.

[0078] S20: Determine the original material processing management library and the destination material processing management library according to the predicted processing material transfer information, and determine the original material processing management batch that needs to be transferred from the original material processing management library.

[0079] In this embodiment, the original material processing management library refers to the database corresponding to the workshop that transfers out the material in the processing workshop cloud system. The destination material processing management library refers to the database corresponding to the workshop that receives the material in the processing workshop cloud system.

[0080] Specifically, after obtaining the predicted processing material transfer information, first determine the predicted first transferred material and the corresponding receiving and transferring workshop, and access the database of the processing workshop cloud system or interact with other information systems to identify two corresponding material processing management libraries, for example, the original material processing management library A (located in factory area A) corresponding to the workshop that moves out the material and the destination material processing management library B (located in factory area B) corresponding to the workshop that receives the material. These two material processing management libraries are responsible for material storage and processing at different stages, and determine the original material processing management batch in the original material processing management library based on the relevant information of the material to be transferred indicated by the predicted processing material transfer information in library A, such as original material processing management batch X, which contains 1,000 units of a certain key raw material that is required for the next stage of processing.

[0081] It should be noted that the reason why the predicted first transferred material and the corresponding receiving and transferring workshop are determined first is that some emergencies may occur during the production process. Therefore, at this time, only the first transferred material needs to be analyzed. The probability of changes in the production situation of the predicted subsequent transferred materials is higher than that of the first transferred materials. Therefore, the predicted first transferred material is analyzed first and the corresponding transfer task is generated. After the predicted first transferred material is transferred, the next transferred material is analyzed. In addition, if there are multiple materials predicted to be transferred first and there are multiple corresponding receiving and transferring workshops, the production situation of these materials is analyzed at the same time, and the corresponding transfer tasks are generated at the same time.

[0082] S30: Collect processing and production identification information, combine the processing and production identification information and the transfer plan variable information, and use the original material processing management batch, the original material processing management library and the destination material processing management library to generate material transfer task information.

[0083] Specifically, in the process of material processing and production, in order to ensure the quality of material processing, some sensors are usually installed to monitor various parameters in the process of material processing and production to monitor and ensure the quality of material processing, such as:

[0084] Vibration sensors used to detect the vibration of materials can determine whether the material flows smoothly, whether there is blockage or abnormal vibration, etc. by detecting the vibration state of materials in equipment such as conveyor belts, hoppers, and grinders, so as to adjust equipment parameters or perform maintenance in time to ensure the stability of the material processing process;

[0085] Weight sensors used to detect the weight or load of materials. In equipment such as batching scales and weighing scales, weight sensors can monitor the weight of materials in real time to ensure the accuracy of batching or weighing;

[0086] Photoelectric sensors are used to detect the existence, position and shape of materials. Photoelectric sensors detect the status of materials by emitting and receiving light signals. In equipment such as conveyor belts and material pipelines, photoelectric sensors can monitor in real time whether materials exist, whether their position is correct, and whether their shape meets the requirements, so as to detect abnormal situations in time and take corresponding treatment measures.

[0087] Temperature sensors used to detect the temperature of materials. In the processing process where the material temperature needs to be controlled, such as heat treatment, welding, etc., the temperature sensor can monitor the temperature of the material in real time to ensure that it is processed within the appropriate temperature range;

[0088] Pressure sensors used to detect the pressure on materials. In processing that requires controlling the pressure of materials, such as injection molding and die casting, pressure sensors can monitor the pressure on materials in real time to ensure that they are processed within the appropriate pressure range.

[0089] Position sensors used to detect the position of materials in processing equipment. Position sensors can monitor the position of materials in processing equipment in real time to ensure that they are processed in the correct position. They are essential for processing processes that require precise control of material position, such as cutting and drilling.

[0090] Therefore, the monitoring data of these sensors and the monitoring data of the production process management, that is, the processing production identification information, are collected. Through the processing production identification information, it is determined whether the processing production identification information meets the conditions of the transfer plan variable information, that is, through the processing production identification information, it is determined whether the current processing progress is the same as the predicted processing progress of the workshop. When it is determined that the current actual processing progress of the workshop is different from the predicted processing progress of the workshop, the corresponding transfer plan variable information is queried according to the difference between the current actual processing progress of the workshop and the predicted processing progress of the workshop. The original material processing management batch, the original material processing management library and the destination material processing management library, as well as the transfer plan variable information are used to change the predicted processing material transfer information, that is, change the material information in the original material processing management batch, or change the original material processing management library and the destination material processing management library, etc., to generate material transfer task information.

[0091] S40: Based on the material transfer task information, a material transfer request is issued to the logistics control system. The material transfer request indicates that the logistics control system performs collaborative processing based on the material transfer task information. After the collaborative processing is completed, a new target material processing management batch is established in the target material processing management library.

[0092] Specifically, after the material transfer task information is generated, a detailed material transfer request is sent to the logistics control system through the processing workshop cloud system using an API or a message queue. The request contains detailed information about batch X (such as batch number, material type, quantity, transfer reason, etc.), as well as relevant information about warehouse A and warehouse B (such as warehouse location, receiving time window, etc.). After receiving the request, the logistics control system first verifies the legitimacy and accuracy of the request. Once the verification is passed, all logistics tasks related to batch X are collaboratively processed, for example, collaborative stagnation processing is performed, that is, operations such as warehousing, outbound storage, and transportation involving batch X will be suspended or rescheduled to ensure the smooth progress of the transfer without causing confusion or conflict. After the collaborative processing is completed, a new destination material processing management batch is automatically established in the destination warehouse B, such as material processing management batch Y. The initial state of batch Y is empty, ready to receive materials transferred from warehouse A. At the same time, a unique identifier and corresponding warehouse location will be assigned to batch Y. The collaborative processing is canceled after the destination material processing management batch is established.

[0093] Furthermore, a target material tag pointing to the target material processing management batch can be generated, and the target material tag indicates that the logistics control system switches the logistics direction across the processing workshop according to the target material tag and cancels the coordinated stagnation processing.

[0094] Specifically, a detailed target material tag is generated for the newly created target material processing management batch Y. This target material tag not only contains the basic information of batch Y (such as batch number, material type, quantity, etc.), but may also contain some additional metadata, such as production date, shelf life, quality grade, etc., which are very important for subsequent processing and tracking. After receiving this target material tag, the logistics control system will cancel the previous collaborative stagnation processing of batch X, which means that the logistics activities related to batch X can resume normal and are no longer affected by the transfer request. However, it should be noted that the number of materials in batch X has been reduced at this time (because some materials have been transferred to batch Y), so the system needs to update the inventory information and plan subsequent replenishment or production activities accordingly.

[0095] S50: For the material transfer task information, when the target logistics object corresponding to the material transfer task information is not retrieved in the destination material processing management batch, the target logistics object is obtained from the original material processing management batch and loaded into the destination material processing management batch to execute the transfer task.

[0096] In this embodiment, the material transfer task information is intended to transfer a specific number of materials from batch X of warehouse A to batch Y of warehouse B. This task may include multiple subtasks, such as packing, transportation, unloading, and shelving. However, when executing this task, it is found that there is not enough target material (i.e., the transferred material in batch X) in the destination batch Y. This may be because the previous transfer operation was not completely completed, or due to other unknown abnormal conditions;

[0097] Therefore, we can go back to the original material processing management batch X and first check whether the remaining material quantity in batch X is sufficient to meet the needs of the target logistics task. If it is sufficient, we can obtain the missing materials and automatically perform a series of operations (such as packing, labeling, etc.) to load these materials into the destination batch Y. In this way, the target transfer task can be completed smoothly to ensure the continuity and accuracy of the production process. If the remaining material quantity in batch X is also insufficient, the processing workshop cloud system may need to trigger an emergency replenishment process or adjust the production plan to adapt to this emergency, which may require interaction and coordination with other information systems (such as procurement systems, production scheduling systems, etc.).

[0098] In one embodiment, if Figure 2 As shown, the machining feature recognition index is generated in the following way:

[0099] S01: Obtain historical material processing task information and historical material production monitoring identification information.

[0100] Specifically, historical material processing task information and historical material production monitoring and identification information are obtained. The historical material processing task information includes the historical production task plans for each workshop formulated by the factory operators before the transfer began, and the corresponding historical actual production task plans. The historical material production monitoring and identification information includes the monitoring data of the sensors of the historical production tasks and the monitoring data of the production process management.

[0101] S02: Analyze historical material processing task information and historical material production monitoring identification information respectively to obtain material processing flow feature information and material monitoring identification feature information.

[0102] Specifically, respectively analyze the historical material processing task information and the historical material production monitoring identification information, respectively determine the different process information when each workshop performs different processing tasks, and the different monitoring identification information when each workshop performs different processing tasks, and then determine the time range of all processes in normal processing and production and the time range of abnormal processing and production, as well as the process steps that will not appear in normal processing and production according to the different process information when each workshop performs different processing tasks, so as to analyze the time wasted due to these process steps that will not appear in normal processing and production, and analyze the historical material processing task information corresponding to abnormal processing and production and the process steps that will not appear in normal processing and production, determine the difference between the historical material processing task information when these situations occur and other historical material processing task information, so as to obtain distinguished material processing task information, and correspond and associate the distinguished material processing task information, the time range of all processes in normal processing and production and the time range of abnormal processing and production, the process steps that will not appear in normal processing and production, and the time wasted due to the process steps that will not appear in normal processing and production, to generate material processing process feature information;

[0103] Then, based on the different monitoring and identification information when each workshop performs different processing tasks, the monitoring and identification information of all processing tasks during normal processing and production and the monitoring and identification information during abnormal processing and production, as well as the monitoring and identification information that will not appear during normal processing and production are judged, so as to analyze the time wasted due to these monitoring and identification information that will not appear during normal processing and production, and analyze the historical material production monitoring and identification information corresponding to abnormal processing and production and when monitoring and identification information that will not appear during normal processing and production appears, and judge the difference between the historical material production monitoring and identification information when these situations occur and other historical material production monitoring and identification information, so as to obtain the distinguished material production monitoring and identification information, and associate the distinguished material production monitoring and identification information, the monitoring and identification information of all processing tasks during normal processing and production and the monitoring and identification information during abnormal processing and production, the monitoring and identification information that will not appear during normal processing and production, and the time wasted due to the monitoring and identification information that will not appear during normal processing and production, to generate material monitoring identification feature information.

[0104] S03: Generate a process feature index based on the material processing process feature information, and generate a monitoring identification feature index based on the material monitoring identification feature information.

[0105] Specifically, based on the material processing flow characteristic information, a flow characteristic index is generated to facilitate query, and based on the material monitoring and identification characteristic information, a monitoring and identification characteristic index is generated to facilitate query.

[0106] S04: Associating the process feature index with the monitoring identification feature index to obtain the processing feature identification index.

[0107] Specifically, the process feature index and the monitoring identification feature index are associated to obtain the processing feature identification index.

[0108] S05: Determine the reliability of the process feature index and the monitoring identification feature index, and generate transfer plan variable information based on the reliability.

[0109] Specifically, determine the reliability of the process feature index and the monitoring identification feature index, that is, determine the amount of data used in analyzing the historical material processing task information and the historical material production monitoring identification information and the analysis method used, determine the reliability of each feature in the process feature index and the monitoring identification feature index, compare the reliability with the preset reliability threshold, mark the features below the reliability threshold, and associate the information corresponding to the marked features as the transfer plan variable information. In this way, when the actual processing progress of the workshop is different from the predicted processing progress of the workshop, the marked features can be quickly queried to change the transfer plan.

[0110] S06: Associating the transfer scheme variable information with the processing feature recognition index.

[0111] Specifically, the transfer scheme variable information is associated with the processing feature recognition index.

[0112] In one embodiment, if Figure 3 As shown, in step S03, a process feature index is generated according to the material processing process feature information, and a monitoring identification feature index is generated according to the material monitoring identification feature information, including:

[0113] S031: According to the material processing flow characteristic information and the historical material processing task information, the processing time and the probability of occurrence of each process are determined to obtain a first time and a first probability, and the first probability corresponds to the distinguished material processing task information.

[0114] Specifically, based on the material processing flow characteristic information and combined with the historical material processing task information, the time range of all processes during normal processing and production and the time range of abnormal processing and production are determined, and the time delay caused by process steps that do not appear in normal processing and production is determined, and the probabilities of occurrence of processes corresponding to these time lengths are determined to obtain a first time length and a first probability. Then, combined with the historical material processing task information, the historical material processing task information corresponding to abnormal processing and production and process steps that do not appear in normal processing and production is analyzed to determine the difference between the historical material processing task information when these situations occur and other historical material processing task information, so as to obtain distinguished material processing task information. The probability of abnormal processing and production and process steps that do not appear in normal processing and production in the first probability corresponds to the distinguished material processing task information.

[0115] S032: Generate a process feature index according to the first duration, the first probability and the corresponding material processing task information.

[0116] Specifically, the first duration, the first probability and the corresponding material processing task information are associated to generate a process feature index.

[0117] S033: Extracting abnormal material monitoring identification feature information from the material monitoring identification feature information.

[0118] Specifically, the material monitoring and identification feature information is analyzed, the monitoring and identification information during abnormal processing and production that will not appear during normal processing and production is determined, and the monitoring and identification information is extracted to obtain the abnormal material monitoring and identification feature information.

[0119] S034: Based on the abnormal material monitoring identification feature information and in combination with the historical material production monitoring identification information, determine the increase duration and probability of each abnormal production monitoring data, and obtain a second duration and a second probability, wherein the second probability corresponds to the differentiated production monitoring identification information.

[0120] Specifically, based on the abnormal material monitoring and identification feature information, the time range of the abnormal monitoring and identification feature processing and production, as well as the delay time caused by the monitoring and identification feature that will not appear in normal processing and production are determined, and the probability of occurrence of the processes corresponding to these time ranges is determined to obtain a second time range and a second probability. Combined with the historical material production monitoring and identification information, the historical material production monitoring and identification information corresponding to the abnormal processing and production and the monitoring and identification information that will not appear in normal processing and production is analyzed to determine the difference between the historical material production monitoring and identification information when these situations occur and other historical material production monitoring and identification information, so as to obtain differentiated production monitoring and identification information. The probability of abnormal processing and production and the monitoring and identification information that will not appear in normal processing and production in the second probability corresponds to the differentiated production monitoring and identification information.

[0121] S035: Generate a monitoring identification feature index according to the second duration, the second probability and the corresponding production monitoring identification information.

[0122] Specifically, the second duration, the second probability and the corresponding production monitoring identification information are associated to generate a monitoring identification feature index.

[0123] In one embodiment, if Figure 4 As shown, in step S20, according to the predicted processing material transfer information, the original material processing management library and the target material processing management library are determined, including:

[0124] S21: Based on the current processing task information, determine the processing execution cost parameters of each material processing management library.

[0125] Specifically, based on the current processing task information, the current processing task information includes the current inventory, safety inventory, maximum inventory and other information of various materials, as well as the material processing efficiency data of each warehouse, such as the processing volume per hour, equipment utilization, worker efficiency, etc. Therefore, the processing execution cost parameters of each material processing management warehouse are calculated according to the current processing task information, which will consider multiple factors, such as inventory turnover time, processing cost, equipment depreciation expenses, etc. The lower the cost parameter, the higher the efficiency and cost-effectiveness of the warehouse in performing material processing tasks.

[0126] S22: Based on the processing execution cost parameters of each material processing management library and the predicted processing material transfer information, an original material processing management library and a target material processing management library are selected from multiple material processing management libraries, wherein the processing execution cost parameter of the target material processing management library is smaller than that of the original material processing management library.

[0127] Specifically, all material processing management libraries are sorted according to the predicted processing material transfer information and the calculated processing execution cost parameters. Then, based on the sorting results and specific selection rules (such as selecting the library with the lowest cost parameter as the destination library, and selecting the library with the second lowest cost parameter as the original library), the original material processing management library and the destination material processing management library are selected from multiple libraries. The purpose of this selection is to ensure that the materials can achieve the best efficiency and cost-effectiveness during the transfer process.

[0128] Furthermore, other constraints will be considered, such as the transportation distance between libraries, transportation costs, and capacity limitations of libraries. These constraints can affect the final selection result and ensure that the selected original library and destination library are feasible in actual operation.

[0129] In one embodiment, if Figure 5 As shown, in step S22, based on the processing execution cost parameters of each material processing management library and the predicted processing material transfer information, an original material processing management library and a target material processing management library are selected from multiple material processing management libraries, including:

[0130] S221: Arrange the processing execution cost parameters of each material processing management library in a first descending order.

[0131] Specifically, the processing execution cost parameters of each material processing management library are first arranged in descending order. The sorting algorithm may be one of the common sorting algorithms such as quick sort and merge sort. The specific algorithm selected depends on the performance of the processing workshop cloud system and data processing requirements.

[0132] S222: Arrange the predicted processing material transfer information of each material processing management library in a second descending order.

[0133] Specifically, the predicted processing material transfer information of each material processing management library is sorted in a second descending order. The second descending order refers to the descending order according to the predicted material transfer time point, that is, the transfer order of materials in each workshop when there is no difference between the actual processing and the prediction.

[0134] S223: According to a preset sorting selection rule, and a first descending order and a second descending order, an original material processing management library and a target material processing management library are selected from a plurality of material processing management libraries.

[0135] Specifically, after the sorting is completed, the original material processing management library and the target material processing management library can be selected according to the preset sorting selection rules. The sorting selection rules may be fixed or dynamically adjusted according to actual needs;

[0136] For example, considering only the cost parameter of processing execution, the library with the highest cost parameter in the first descending order (i.e., the library at the first node position) is used as the original material processing management library, because this means that the efficiency and cost-effectiveness of the library in performing material processing tasks are relatively low, and some materials may need to be transferred out to improve overall efficiency. However, in actual applications, the library with the second highest or higher cost parameter can also be selected as the original library, depending on actual needs and constraints; similarly, the library with the second highest or lower cost parameter (i.e., the library at the second node position or later) can also be used as the destination material processing management library. The library with a lower cost parameter is selected as the destination library to ensure that the material can be processed in a more efficient and cost-effective environment after transfer. It should be noted that the first node and the second node here are not fixed positions, but are dynamically determined according to actual conditions and preset rules. For example, if the rule is to select the two libraries with the highest cost parameters as the original library and the destination library respectively, then the first node and the second node are the first two positions in the list; if the rule is to select the two libraries with the second highest cost parameters, then the first node and the second node will be moved back accordingly;

[0137] Alternatively, based on the first descending order and the second descending order, if the lowest and second lowest material processing management warehouses are selected according to the first descending order, and according to the second descending order, the lowest and second lowest material processing management warehouses are the predicted material processing management warehouses that will perform material movement first, then the lowest and second lowest material processing management warehouses can be directly used as the original material processing management warehouse and the destination material processing management warehouse. If the lowest and second lowest material processing management warehouses in the second descending order are not the material processing management warehouses that will perform material movement first, the accuracy of the prediction needs to be considered. When the accuracy of the prediction is high and the transfer order of the materials of the material processing management warehouses with the lowest and second lowest processing execution cost parameters is third or fourth, the lowest and second lowest material processing management warehouses can also be directly used as the original material processing management warehouse and the destination material processing management warehouse.

[0138] In one embodiment, if Figure 6 As shown, in step S30, a new target material processing management batch is established in the target material processing management library, including:

[0139] S31: Obtain material processing information of the original material processing management batch.

[0140] Specifically, a request is first sent to the original material processing management library to obtain material processing information for a specific batch. This information usually includes key data such as material type, quantity, processing status, quality requirements, etc., which are the reference basis necessary for establishing a new batch.

[0141] S32: Create a copy of the material processing record of the original material processing management batch based on the material processing information of the original material processing management batch.

[0142] Specifically, after obtaining the material processing information of the original material processing management batch, a comprehensive analysis is performed on the material processing information, and a material processing record copy is created in the memory or temporary storage area based on the analysis results. This material processing record copy is a complete copy of the processing process of the original material processing management batch, and contains all necessary data and parameters to ensure that the same processing conditions can be reproduced in the destination material processing management library.

[0143] S33: Establishing a corresponding relationship in the target material processing management library to the target material processing management batch for which the material processing record copy is not established but the actual inventory space is not established.

[0144] Specifically, a destination material processing management batch is established in the destination material processing management library with a corresponding relationship to the material processing record copy but no actual inventory space is established. When this new batch is created, a corresponding relationship will be established with the original batch. This relationship may be achieved through batch number, material code or other unique identifier.

[0145] It should be noted that when a new batch is created, the processing workshop cloud system will not immediately allocate actual inventory space for it. This is because the allocation of inventory space usually needs to be dynamically adjusted based on the actual inventory situation of the destination material processing management library, material processing requirements, inventory management strategies, future processing plans, and possible material circulation situations. Therefore, the new batch may only exist in the database or information management system of the destination material processing management library at the initial stage of creation, without corresponding actual physical inventory space. In order to ensure that the new batch can obtain the required inventory space in a timely manner when needed, the processing workshop cloud system can work closely with the inventory management system of the destination material processing management library. When the new batch needs to enter the actual processing process, the processing workshop cloud system can send a request to the inventory management system to request the allocation of corresponding inventory space for the new batch. After receiving the request, the inventory management system will find a suitable inventory location for the new batch based on its inventory allocation algorithm and real-time inventory data, and update the relevant information in the database. In this way, the new batch can smoothly enter the actual processing process of the destination material processing management library.

[0146] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0147] In one embodiment, a prediction-based inter-shop material transfer device is provided, and the prediction-based inter-shop material transfer device corresponds one-to-one to the prediction-based inter-shop material transfer method in the above embodiment. Figure 7 As shown, the prediction-based inter-workshop material transfer device includes a processing task acquisition module, a management library determination module, a transfer task generation module, a request issuance module and a task execution module. The functional modules are described in detail as follows:

[0148] The processing task acquisition module is used to obtain the current processing task information, predict the material processing progress based on the preset processing feature recognition index and the current processing task information, and obtain the predicted processing material transfer information, which includes the transfer scheme variable information;

[0149] A management library determination module is used to determine the original material processing management library and the destination material processing management library according to the predicted processing material transfer information, and determine the original material processing management batch that needs to be transferred from the original material processing management library;

[0150] The transfer task generation module is used to collect processing and production identification information, combine the processing and production identification information and the transfer plan variable information, and use the original material processing management batch, the original material processing management library and the destination material processing management library to generate material transfer task information;

[0151] The request issuing module is used to issue a material transfer request to the logistics control system based on the material transfer task information. The material transfer request indicates that the logistics control system performs collaborative processing based on the material transfer task information. After the collaborative processing is completed, a new target material processing management batch is established in the target material processing management library;

[0152] The task execution module is used to obtain the target logistics object from the original material processing management batch and load it into the destination material processing management batch to execute the transfer task when the target logistics object corresponding to the material transfer task information is not retrieved in the destination material processing management batch.

[0153] Optional, prediction-based inter-shop material transfer systems also include:

[0154] The historical information acquisition module is used to obtain historical material processing task information and historical material production monitoring identification information;

[0155] A feature recognition module is used to analyze historical material processing task information and historical material production monitoring and recognition information, respectively, to obtain material processing flow feature information and material monitoring and recognition feature information;

[0156] The feature analysis module is used to generate a process feature index based on the material processing process feature information, and to generate a monitoring and identification feature index based on the material monitoring and identification feature information;

[0157] A feature association module is used to associate the process feature index with the monitoring identification feature index to obtain the processing feature identification index;

[0158] The reliability judgment module is used to judge the reliability of the process feature index and the monitoring identification feature index, and generate the transfer plan variable information according to the reliability;

[0159] The variable association module is used to associate the variable information of the transfer plan with the processing feature recognition index.

[0160] Optionally, the feature analysis module includes:

[0161] The process analysis submodule is used to determine the processing time and probability of each process according to the material processing process characteristic information and the historical material processing task information, and obtain the first time and the first probability. The first probability corresponds to the different material processing task information;

[0162] A process index generation submodule, used to generate a process feature index according to the first duration, the first probability and the corresponding material processing task information;

[0163] The abnormal identification feature extraction submodule is used to extract abnormal material monitoring identification feature information from the material monitoring identification feature information;

[0164] The abnormal analysis submodule is used to determine the increase duration and probability of each abnormal production monitoring data according to the abnormal material monitoring identification feature information and the historical material production monitoring identification information, and obtain the second duration and the second probability, and the second probability corresponds to the different production monitoring identification information;

[0165] The monitoring index generating submodule is used to generate a monitoring identification feature index according to the second duration, the second probability and the corresponding production monitoring identification information.

[0166] Optionally, the management library determination module includes:

[0167] The cost parameter determination submodule is used to determine the processing execution cost parameters of each material processing management library based on the current processing task information;

[0168] The management library determines the submodule, which is used to select the original material processing management library and the destination material processing management library from multiple material processing management libraries based on the processing execution cost parameters of each material processing management library and the predicted processing material transfer information, wherein the processing execution cost parameters of the destination material processing management library are smaller than those of the original material processing management library.

[0169] Optionally, the management library determines that the submodule includes:

[0170] A first arrangement unit, used for arranging the processing execution cost parameters of each material processing management library in a first descending order;

[0171] A second arrangement unit, used for arranging the predicted processing material transfer information of each material processing management library in a second descending order;

[0172] The comprehensive arrangement unit is used to select an original material processing management library and a target material processing management library from multiple material processing management libraries according to a preset sorting selection rule, a first descending order arrangement and a second descending order arrangement.

[0173] Optionally, the request delivery module includes:

[0174] The processing information acquisition submodule is used to obtain the material processing information of the original material processing management batch;

[0175] The copy creation submodule is used to create a copy of the material processing record of the original material processing management batch based on the material processing information of the original material processing management batch;

[0176] The batch establishment submodule is used to establish a target material processing management batch that corresponds to the material processing record copy in the target material processing management library but has not established the actual inventory space.

[0177] For the specific limitations of the prediction-based inter-workshop material transfer device, please refer to the limitations of the prediction-based inter-workshop material transfer method above, which will not be repeated here. Each module in the above-mentioned prediction-based inter-workshop material transfer device can be implemented in whole or in part through software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0178] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 8 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store predicted processing material transfer information, original material processing management library, destination material processing management library, material transfer task information and destination material processing management batches, etc. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a prediction-based cross-workshop material transfer method is implemented.

[0179] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program:

[0180] Obtain current processing task information, predict material processing progress based on a preset processing feature recognition index and in combination with current processing task information, and obtain predicted processing material transfer information, wherein the predicted processing material transfer information includes transfer scheme variable information;

[0181] According to the predicted processing material transfer information, the original material processing management library and the target material processing management library are determined, and the original material processing management batch that needs to be transferred is determined from the original material processing management library;

[0182] Collect processing and production identification information, combine the processing and production identification information and the transfer plan variable information, and use the original material processing management batch, the original material processing management library and the destination material processing management library to generate material transfer task information;

[0183] Based on the material transfer task information, a material transfer request is issued to the logistics control system. The material transfer request indicates that the logistics control system performs collaborative processing based on the material transfer task information. After the collaborative processing is completed, a new target material processing management batch is established in the target material processing management library.

[0184] For material transfer task information, when the target logistics object corresponding to the material transfer task information is not retrieved in the destination material processing management batch, the target logistics object is obtained from the original material processing management batch and loaded into the destination material processing management batch to execute the transfer task.

[0185] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0186] Obtain current processing task information, predict material processing progress based on a preset processing feature recognition index and in combination with current processing task information, and obtain predicted processing material transfer information, wherein the predicted processing material transfer information includes transfer scheme variable information;

[0187] According to the predicted processing material transfer information, the original material processing management library and the target material processing management library are determined, and the original material processing management batch that needs to be transferred is determined from the original material processing management library;

[0188] Collect processing and production identification information, combine the processing and production identification information and the transfer plan variable information, and use the original material processing management batch, the original material processing management library and the destination material processing management library to generate material transfer task information;

[0189] Based on the material transfer task information, a material transfer request is issued to the logistics control system. The material transfer request indicates that the logistics control system performs collaborative processing based on the material transfer task information. After the collaborative processing is completed, a new target material processing management batch is established in the target material processing management library.

[0190] For material transfer task information, when the target logistics object corresponding to the material transfer task information is not retrieved in the destination material processing management batch, the target logistics object is obtained from the original material processing management batch and loaded into the destination material processing management batch to execute the transfer task.

[0191] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0192] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0193] The embodiments described above 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, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for transferring materials across workshops based on prediction, characterized in that: Applied to the cloud system of a processing workshop, the prediction-based cross-workshop material transfer method includes: The current processing task information is obtained, and based on the preset processing feature recognition index, the material processing progress is predicted in combination with the current processing task information, and the predicted processing material transfer information is obtained, wherein the predicted processing material transfer information includes transfer scheme variable information, and the processing feature recognition index refers to the index information used to predict the workshop processing progress according to the characteristics of the workshop processing task, and the transfer scheme variable information refers to the information used to change the material transfer scheme when the actual workshop processing progress is different from the predicted workshop processing progress, and the processing feature recognition index is generated by the following method: Obtain historical material processing task information and historical material production monitoring identification information; Respectively analyzing the historical material processing task information and the historical material production monitoring identification information to obtain material processing flow feature information and material monitoring identification feature information; Generate a process feature index based on the material processing process feature information, and generate a monitoring identification feature index based on the material monitoring identification feature information; Associating the process feature index with the monitoring identification feature index to obtain a processing feature identification index; Determining the reliability of the process feature index and the monitoring identification feature index, and generating transfer scheme variable information according to the reliability; Associating the transfer scheme variable information with the processing feature identification index; Determine the original material processing management library and the target material processing management library according to the predicted processing material transfer information, and determine the original material processing management batch that needs to be transferred from the original material processing management library; Collecting processing and production identification information, combining the processing and production identification information with the transfer scheme variable information, and using the original material processing management batch, the original material processing management library, and the destination material processing management library to generate material transfer task information; Based on the material transfer task information, a material transfer request is issued to the logistics control system, wherein the material transfer request indicates that the logistics control system performs collaborative processing based on the material transfer task information, and after the collaborative processing is completed, a new target material processing management batch is established in the target material processing management library; For the material transfer task information, when the target logistics object corresponding to the material transfer task information is not retrieved in the destination material processing management batch, the target logistics object is obtained from the original material processing management batch and loaded into the destination material processing management batch to execute the transfer task.

2. The prediction-based inter-shop material transfer method according to claim 1 is characterized in that: The step of generating a process feature index according to the material processing process feature information and generating a monitoring identification feature index according to the material monitoring identification feature information includes: According to the material processing flow characteristic information, combined with the historical material processing task information, the processing time and the probability of occurrence of each process are determined to obtain a first time and a first probability, wherein the first probability corresponds to the distinguished material processing task information; Generate a process feature index according to the first duration, the first probability and corresponding material processing task information; Extracting abnormal material monitoring identification feature information from the material monitoring identification feature information; According to the abnormal material monitoring identification feature information, combined with the historical material production monitoring identification information, determine the increase duration and probability of each abnormal production monitoring data, obtain a second duration and a second probability, and the second probability corresponds to the different production monitoring identification information; A monitoring identification feature index is generated according to the second duration, the second probability and the corresponding production monitoring identification information.

3. The prediction-based inter-shop material transfer method according to claim 1 is characterized in that: The step of determining the original material processing management library and the target material processing management library according to the predicted processing material transfer information includes: Based on the current processing task information, determining the processing execution cost parameters of each material processing management library; Based on the processing execution cost parameters of each material processing management library and the predicted processing material transfer information, an original material processing management library and a target material processing management library are selected from the multiple material processing management libraries, wherein the processing execution cost parameter of the target material processing management library is smaller than that of the original material processing management library.

4. The prediction-based inter-shop material transfer method according to claim 3 is characterized in that: The selecting of an original material processing management library and a target material processing management library from a plurality of material processing management libraries based on the processing execution cost parameters of each material processing management library and the predicted processing material transfer information includes: Arranging the processing execution cost parameters of each material processing management library in a first descending order; Arranging the predicted processing material transfer information of each material processing management library in a second descending order; According to a preset sorting selection rule, as well as the first descending order and the second descending order, an original material processing management library and a target material processing management library are selected from the plurality of material processing management libraries.

5. The prediction-based inter-shop material transfer method according to claim 1 is characterized in that: The step of establishing a new target material processing management batch in the target material processing management library includes: Obtaining material processing information of the original material processing management batch; Creating a copy of the material processing record of the original material processing management batch based on the material processing information of the original material processing management batch; A destination material processing management batch having a corresponding relationship to the material processing record copy is established in the destination material processing management library but no actual inventory space is established.

6. A prediction-based inter-shop material transfer system, characterized in that: The prediction-based inter-shop material transfer system includes: The processing task acquisition module is used to obtain the current processing task information, predict the material processing progress based on the preset processing feature recognition index and the current processing task information, and obtain the predicted processing material transfer information, wherein the predicted processing material transfer information includes the transfer scheme variable information, wherein the processing feature recognition index refers to the index information used to predict the workshop processing progress according to the characteristics of the workshop processing task, and the transfer scheme variable information refers to the information used to change the material transfer scheme when the actual workshop processing progress is different from the predicted workshop processing progress, and further includes: The historical information acquisition module is used to obtain historical material processing task information and historical material production monitoring identification information; A feature recognition module is used to respectively analyze the historical material processing task information and the historical material production monitoring recognition information to obtain material processing flow feature information and material monitoring recognition feature information; A feature analysis module, used to generate a process feature index according to the material processing process feature information, and to generate a monitoring identification feature index according to the material monitoring identification feature information; A feature association module, used to associate the process feature index with the monitoring identification feature index to obtain a processing feature identification index; A reliability judgment module, used to judge the reliability of the process feature index and the monitoring identification feature index, and generate transfer scheme variable information according to the reliability; A variable association module, used for associating the variable information of the transfer scheme with the processing feature identification index; A management library determination module is used to determine the original material processing management library and the target material processing management library according to the predicted processing material transfer information, and determine the original material processing management batch that needs to be transferred from the original material processing management library; A transfer task generation module is used to collect processing and production identification information, combine the processing and production identification information and the transfer scheme variable information, and use the original material processing management batch, the original material processing management library and the target material processing management library to generate material transfer task information; A request issuing module, used for issuing a material transfer request to the logistics control system based on the material transfer task information, wherein the material transfer request indicates that the logistics control system performs collaborative processing based on the material transfer task information, and after the collaborative processing is completed, a new target material processing management batch is established in the target material processing management library; The task execution module is used to obtain the target logistics object from the original material processing management batch and load it into the destination material processing management batch to execute the transfer task when the target logistics object corresponding to the material transfer task information is not retrieved in the destination material processing management batch.

7. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the prediction-based inter-shop material transfer method as described in any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the prediction-based inter-shop material transfer method as described in any one of claims 1 to 5 are implemented.

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