A method, system, medium, and program product for operation management of an industrial device

Abstract

The application relates to the technical field of artificial intelligence, and discloses an operation management method and system of an industrial device, a medium and a program product. The method comprises the following steps: a current device-side proxy robot interacts with device operation software of a corresponding current non-standard customized device based on an extended application programming interface, and first running state data corresponding to the current non-standard customized device is collected; if it is detected that the current non-standard customized device is abnormal according to the first running state data, an abnormality assistance request is generated, and the abnormality assistance request and the first running state data are sent to a manufacturer-side proxy robot; the abnormality assistance request and the first running state data are sent to a manufacturer after-sales management personnel by calling a first instant messaging tool by the manufacturer-side proxy robot, so that the manufacturer after-sales management personnel performs abnormality disposal. Efficient and accurate abnormality diagnosis of the non-standard customized device can be realized, and the operation management efficiency of the industrial device can be improved.

Description

Technical Field

[0001] This invention relates to the field of artificial intelligence technology, and in particular to a method, system, medium, and program product for the operation and management of industrial equipment. Background Technology

[0002] For complex mechatronic equipment delivered in the discrete manufacturing industry, the high degree of customization of its functions and the low similarity between each piece of equipment pose new challenges to equipment operation and management.

[0003] Currently, existing methods for managing the operation of industrial equipment, particularly non-standard customized equipment, typically involve the customer's equipment operators remotely contacting the equipment manufacturer to diagnose abnormalities or malfunctions. However, this method of remote contact by personnel is not only inefficient but also fails to provide accurate equipment operating data, leading to low accuracy in abnormality diagnosis. Summary of the Invention

[0004] This invention provides an operation management method, system, medium, and program product for industrial equipment, which can achieve efficient and accurate anomaly diagnosis for non-standard customized equipment and improve the operation management efficiency of industrial equipment.

[0005] According to one aspect of the present invention, an operation management method for industrial equipment is provided, applied to an industrial equipment operation management system including a manufacturer-side agent robot and multiple equipment-side agent robots, wherein the equipment-side agent robots operate on non-standard customized equipment, comprising:

[0006] The agent robot on the current device side interacts with the device operation software of the corresponding current non-standard customized device through the extended application programming interface, and collects the first operating status data corresponding to the current non-standard customized device.

[0007] If the current non-standard customized equipment is detected to be abnormal by the agent robot on the current device side based on the first operating status data, an abnormality assistance request is generated and the abnormality assistance request and the first operating status data are sent to the agent robot on the manufacturer side.

[0008] The manufacturer-side agent robot invokes a first instant messaging tool to send the abnormality assistance request and the first operating status data to a first terminal device used by the manufacturer's after-sales management personnel, so that the manufacturer's after-sales management personnel can handle the abnormality based on the abnormality assistance request and the first operating status data.

[0009] According to another aspect of the present invention, an industrial equipment operation management system is provided, including a manufacturer-side agent robot and a plurality of equipment-side agent robots, wherein the equipment-side agent robots operate on non-standard customized equipment;

[0010] Each of the aforementioned device-side agent robots is used to interact with the device operation software of the corresponding non-standard customized equipment based on the extended application programming interface, and to collect the first operating status data corresponding to the non-standard customized equipment.

[0011] If an anomaly is detected in the non-standard customized equipment based on the first operating status data, an anomaly assistance request is generated, and the anomaly assistance request and the first operating status data are sent to the manufacturer-side agent robot.

[0012] The manufacturer-side agent robot is used to invoke a first instant messaging tool to send the abnormality assistance request and the first operating status data to a first terminal device used by the manufacturer's after-sales management personnel, so that the manufacturer's after-sales management personnel can handle the abnormality based on the abnormality assistance request and the first operating status data.

[0013] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing a computer program, the computer program being configured to cause a processor to execute and implement the operation management method for industrial equipment according to any embodiment of the present invention.

[0014] According to another aspect of the present invention, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the operation management method for industrial equipment as described in any embodiment of the present invention.

[0015] The technical solution of this invention involves an agent robot on the current equipment side interacting with the equipment operation software of the corresponding non-standard customized equipment via an extended application programming interface (API) to collect first operating status data corresponding to the non-standard customized equipment. If the agent robot on the current equipment side detects an anomaly in the non-standard customized equipment based on the first operating status data, an anomaly assistance request is generated and sent along with the first operating status data to the manufacturer-side agent robot. The manufacturer-side agent robot then invokes a first instant messaging tool to send the anomaly assistance request and the first operating status data to a first terminal device used by the manufacturer's after-sales management personnel, enabling the after-sales management personnel to handle the anomaly based on the request and data. By setting up manufacturer-side and equipment-side agent robots and adding an extended API to the equipment operation software, the interaction between these robots enables automatic reporting of equipment operating status and anomalies. This allows for efficient and accurate anomaly diagnosis of non-standard customized equipment, improving the operational management efficiency of industrial equipment.

[0016] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart of an operation management method for industrial equipment provided according to Embodiment 1 of the present invention;

[0019] Figure 2 This is a flowchart of an operation management method for industrial equipment according to Embodiment 2 of the present invention;

[0020] Figure 3 This is a schematic diagram of the structure of the industrial equipment operation management system provided in Embodiment 2 of the present invention;

[0021] Figure 4 This is a schematic diagram of the structure of an industrial equipment operation management system provided in Embodiment 3 of the present invention. Detailed Implementation

[0022] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0023] It should be noted that the terms "first," "second," "target," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such terms can be used interchangeably where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0024] Example 1

[0025] Figure 1 This is a flowchart of an industrial equipment operation management method provided in Embodiment 1 of the present invention. This embodiment is applicable to the operation management of non-standard customized industrial equipment. The method can be applied to an industrial equipment operation management system including a manufacturer-side agent robot and multiple equipment-side agent robots. The equipment-side agent robots operate on non-standard customized equipment. The industrial equipment operation management system can be implemented in software. Figure 1 As shown, the method includes:

[0026] S110. The agent robot on the current device side interacts with the device operation software of the corresponding current non-standard customized device through the extended application programming interface to collect the first operating status data corresponding to the current non-standard customized device.

[0027] The device-side agent robot and the manufacturer-side agent robot can be intelligent entities based on a public artificial intelligence model foundation (such as a large language model), capable of autonomously perceiving the environment, making decisions, and executing tasks. This embodiment does not specifically limit the artificial intelligence model foundation. The device-side agent robot can be deployed locally on the device, corresponding one-to-one with non-standard customized equipment, while the manufacturer-side agent robot can be deployed remotely in the cloud. This embodiment does not specifically limit the non-standard customized equipment. The device-side agent robot and the manufacturer-side agent robot can interact based on an Application Programming Interface (API). The device-side agent robot reports to and accepts queries from the manufacturer-side agent robot, which then reports to the manufacturer's after-sales management personnel.

[0028] In this embodiment, the non-standard customized equipment is controlled by pre-deployed equipment operation software in the host computer. Since these non-standard customized devices vary, their original equipment operation software cannot directly communicate with the device-side agent robot. To address this issue, this embodiment adds an extended application programming interface (API) to the equipment operation software, specifically for communication and interaction with the corresponding device-side agent robot. The interaction content is constrained by manufacturer-preset parameters in the standalone software, which can be reconfigured later under secure conditions. For example, the extended API can adopt a RESTful (Representational State Transfer) architecture, providing a Hypertext Transfer Protocol (HTTP) access interface, with the interface response data using a unified JSON (JavaScript Object Notation) format.

[0029] Specifically, the agent robot on the current device side can send operational data collection requests to the device operation software via an extended API at set intervals. After receiving the operational data collection request, the device operation software uses its original functional modules to collect or retrieve the operational status data corresponding to the current non-standard customized device in real time, and then sends the operational status data to the agent robot on the current device side via the extended API.

[0030] The operational status data can include basic equipment data and equipment status data. For example, basic equipment data can include equipment type, manufacturing time, and equipment parameters, while equipment status data can include real-time operational status, historical operations, and fault repair history. In this embodiment, the equipment operation software can feed back the usage status of the equipment hardware to the equipment-side agent robot. Through statistical analysis, the equipment-side agent robot can quickly determine the health status of the hardware and consumables, avoiding the need for the device-side agent robot to directly read local files or databases, thus ensuring equipment and data security.

[0031] S120. If the current non-standard customized equipment is detected to be abnormal by the current device-side agent robot based on the first operating status data, an abnormality assistance request is generated and the abnormality assistance request and the first operating status data are sent to the manufacturer-side agent robot.

[0032] Specifically, if the current device-side agent robot detects abnormal alarm information from the first operating status data, it determines that the current non-standard customized equipment has malfunctioned. Alternatively, it extracts the real-time status information of the equipment from the first operating status data; if it detects that the real-time status information exceeds the preset normal state range, it determines that the current non-standard customized equipment has malfunctioned. Then, the current device-side agent robot can generate an abnormality assistance request based on preset configuration information and send the abnormality assistance request along with the first operating status data to the manufacturer-side agent robot.

[0033] Optionally, after detecting an anomaly in the current non-standard customized equipment based on the first operating status data, the following may also be included:

[0034] The first operating status data is sent to the second terminal device used by the customer equipment manager corresponding to the current non-standard customized equipment by calling the second instant messaging tool through the agent robot on the current device side.

[0035] In this embodiment, the information reporting hierarchy of the industrial equipment operation management system may include a customer layer in addition to the equipment layer and the manufacturer layer. Specifically, while the current equipment-side agent robot reports the first operating status data to the manufacturer-side agent robot, it can also report it to the customer equipment manager corresponding to the current non-standard customized equipment via instant messaging. The correspondence between the non-standard customized equipment and the customer equipment manager can be preset.

[0036] Optionally, when there are no abnormalities, the equipment-side agent robot can automatically submit operational status data to the customer equipment manager corresponding to the non-standard customized equipment via instant messaging tools at set intervals (such as 1 hour). When an abnormality occurs, the equipment operation software can immediately send operational status data to the corresponding equipment-side agent robot, which will then immediately forward the operational status data to the corresponding customer equipment manager and the manufacturer-side agent robot.

[0037] The advantage of the above setup is that it enables a multi-level information reporting system, allowing customer equipment managers to obtain real-time equipment operating status in a timely manner, thereby reducing the complexity of equipment management.

[0038] S130. The manufacturer-side agent robot invokes a first instant messaging tool to send the abnormal assistance request and the first operating status data to a first terminal device used by the manufacturer's after-sales management personnel, so that the manufacturer's after-sales management personnel can handle the abnormality based on the abnormal assistance request and the first operating status data.

[0039] Specifically, after receiving an abnormal assistance request and initial operational status data, the manufacturer-side agent robot can forward the received information to the designated manufacturer after-sales management personnel via instant messaging. The manufacturer's after-sales management personnel will then arrange for a specific after-sales engineer to provide on-site repair or remote guidance based on the assessment. This embodiment does not specifically limit the instant messaging tool. The interaction between the manufacturer-side agent robot and the manufacturer's after-sales management personnel is relayed through an instant messaging server. The manufacturer-side agent robot can store historical conversations in the cloud, allowing it to recall past conversations and facilitating historical task retrieval for other personnel.

[0040] It should be noted that all data interactions between the agent robot and other non-local systems via the API interface require traversing a public network. This public network can be accessed through wired networks, wireless network communication technologies, 4G mobile communication technologies, industrial internet, or other similar means. Furthermore, each API interface has authentication functionality. The agent robot can store historical conversations and data / information obtained through the API on the device it operates on.

[0041] Optionally, the equipment operation software can record the operator's usage style and habits, and report the recorded information to the equipment-side agent robot, assisting developers in optimizing the equipment and software design from the perspective of on-site operators. Additionally, the manufacturer's after-sales management personnel can use the agent robot to update firmware for batches of equipment to improve equipment usage quality.

[0042] Optionally, the manufacturer-side agent robot may invoke a first instant messaging tool to send the exception assistance request and the first operational status data to a first terminal device used by the manufacturer's after-sales management personnel. This may include:

[0043] The manufacturer-side agent robot invokes a pre-trained anomaly handling model to obtain the anomaly type and handling suggestions based on the first operating status data.

[0044] The manufacturer-side agent robot invokes a first instant messaging tool to send the exception assistance request, the first operating status data, the exception type, and the handling suggestions to a first terminal device used by the manufacturer's after-sales management personnel.

[0045] The anomaly handling model can be obtained by fine-tuning and training a basic large language model using historical operating status data of non-standard customized equipment, along with corresponding anomaly types and handling suggestions. In this embodiment, firstly, the manufacturer-side agent robot can invoke the anomaly handling model and generate a current prompt word based on the first operating status data and a preset prompt word template. Next, the manufacturer-side agent robot can input the current prompt word into the anomaly handling model and obtain the anomaly type and handling suggestions output by the model. Finally, the manufacturer-side agent robot can provide the anomaly assistance request, the first operating status data, the anomaly type, and the handling suggestions to the manufacturer's after-sales management personnel via instant messaging tools or web-based dialogue. For example, the anomaly type can include mechanical, electrical, or software issues.

[0046] The advantage of the above settings is that they can improve the efficiency of anomaly detection and the efficiency of equipment anomaly repair.

[0047] The technical solution of this invention involves an agent robot on the current equipment side interacting with the equipment operation software of the corresponding non-standard customized equipment via an extended application programming interface (API) to collect first operating status data corresponding to the non-standard customized equipment. If the agent robot on the current equipment side detects an anomaly in the non-standard customized equipment based on the first operating status data, an anomaly assistance request is generated and sent along with the first operating status data to the manufacturer-side agent robot. The manufacturer-side agent robot then invokes a first instant messaging tool to send the anomaly assistance request and the first operating status data to a first terminal device used by the manufacturer's after-sales management personnel, enabling the after-sales management personnel to handle the anomaly based on the request and data. By setting up manufacturer-side and equipment-side agent robots and adding an extended API to the equipment operation software, the interaction between these robots enables automatic reporting of equipment operating status and anomalies. This allows for efficient and accurate anomaly diagnosis of non-standard customized equipment, improving the operational management efficiency of industrial equipment.

[0048] Example 2

[0049] Figure 2 This is a flowchart illustrating an industrial equipment operation management method according to Embodiment 2 of the present invention. This embodiment is a further refinement of the above technical solution, and the technical solution in this embodiment can be combined with one or more of the above implementation methods. For example... Figure 2 As shown, the method includes:

[0050] S210. The agent robot on the current device side interacts with the device operation software of the corresponding current non-standard customized device through the extended application programming interface, and collects the first operating status data corresponding to the current non-standard customized device.

[0051] S220. If the current non-standard customized equipment is detected to be abnormal by the current device-side agent robot based on the first operating status data, an abnormality assistance request is generated and the abnormality assistance request and the first operating status data are sent to the manufacturer-side agent robot.

[0052] S230. The manufacturer-side agent robot invokes a first instant messaging tool to send the abnormal assistance request and the first operating status data to a first terminal device used by the manufacturer's after-sales management personnel, so that the manufacturer's after-sales management personnel can handle the abnormality based on the abnormal assistance request and the first operating status data.

[0053] S240. The manufacturer-side agent robot obtains other non-standard customized equipment corresponding to the current non-standard customized equipment based on the first operating status data.

[0054] In this embodiment, when an anomaly is detected in the current non-standard customized equipment, the manufacturer-side agent robot can perform anomaly assessments on other related non-standard customized equipment, thereby enabling proactive maintenance of potentially malfunctioning equipment. Specifically, the manufacturer-side agent robot can extract the manufacturing date of the current non-standard customized equipment from the first operating status data and identify other non-standard customized equipment with the same manufacturing date (time interval within a preset range) as its corresponding other non-standard customized equipment. Alternatively, the manufacturer-side agent robot can extract the previous fault repair time of the current non-standard customized equipment from the first operating status data and identify other non-standard customized equipment with the same previous fault repair time as its corresponding other non-standard customized equipment.

[0055] Optionally, the manufacturer-side agent robot may obtain other non-standard customized equipment corresponding to the current non-standard customized equipment based on the first operating status data, which may include:

[0056] The manufacturer-side agent robot obtains the equipment type corresponding to the current non-standard customized equipment based on the first operating status data, and obtains other non-standard customized equipment corresponding to the current non-standard customized equipment based on the equipment type.

[0057] In an optional example, firstly, the device type corresponding to the current non-standard customized device is extracted from the first operating status data, and the device types corresponding to all non-standard customized devices are extracted from the stored historical operating status data. Then, non-standard customized devices belonging to the same device type as the current non-standard customized device are designated as other non-standard customized devices.

[0058] The advantage of the above settings is that they can predict anomalies in non-standard customized equipment of the same type, thus avoiding a concentrated outbreak of anomalies in a certain type of equipment.

[0059] S250. Obtain the other equipment-side agent robot corresponding to each of the other non-standard customized equipment through the manufacturer-side agent robot, and obtain the second operating status data corresponding to each of the other non-standard customized equipment through the other equipment-side agent robot.

[0060] After identifying other non-standard customized equipment, the manufacturer-side agent robot can determine the corresponding other device-side agent robot for each non-standard customized equipment based on the preset correspondence between non-standard customized equipment and device-side agent robots. Then, the manufacturer-side agent robot can send data collection requests to each other device-side agent robot and receive the second operating status data corresponding to each other non-standard customized equipment from the other device-side agent robots.

[0061] S260. The manufacturer-side agent robot calls the pre-trained anomaly prediction model, obtains the anomaly probability corresponding to each of the other non-standard customized devices according to each of the second operating state data, and determines the non-standard customized device to be tested among the other non-standard customized devices according to the anomaly probability.

[0062] The anomaly prediction model can be built based on machine learning or neural network algorithms. The input is runtime status data, and the output is anomaly determination results and confidence levels. In this embodiment, an initial anomaly prediction model can be built according to preset model parameters. The initial anomaly prediction model is then trained using historical runtime status data and corresponding anomaly determination results until a preset iteration termination condition is met, resulting in a fully trained anomaly prediction model.

[0063] Next, the manufacturer-side agent robot can input the second operational status data into the anomaly prediction model and obtain the confidence level of the anomaly occurrence output by the anomaly prediction model, which is used as the anomaly probability. Furthermore, if the anomaly probability corresponding to another non-standard customized device is detected to be greater than a preset probability threshold, that other non-standard customized device can be identified as the non-standard customized device to be tested. Thus, the non-standard customized device to be tested can be selected from all other non-standard customized devices.

[0064] S270. Obtain the target after-sales engineer corresponding to the non-standard customized equipment to be tested through the manufacturer-side agent robot, and generate a test work order corresponding to the non-standard customized equipment to be tested, so as to send the test work order to the third terminal device used by the target after-sales engineer, so that the target after-sales engineer can perform maintenance operations based on the test work order.

[0065] Specifically, the manufacturer-side agent robot can be randomly assigned among all after-sales engineers to identify the target after-sales engineer for each non-standard customized device to be tested. It then automatically generates a testing work order for each device through a collaborative office system and sends the work order to the corresponding target after-sales engineer. The testing work order may include operational status data, customer information, and task deadlines. Upon receiving the work order, the target after-sales engineer can contact the customer and perform on-site maintenance independently.

[0066] Optionally, after obtaining the second operating status data corresponding to each of the other non-standard customized devices, the process may further include: calling a pre-trained anomaly prediction model through a manufacturer-side agent robot to obtain the anomaly probability and anomaly time corresponding to each of the other non-standard customized devices based on the second operating status data; filtering out non-standard customized devices with an anomaly probability greater than a preset probability threshold from among the other non-standard customized devices; obtaining the target after-sales engineer corresponding to the non-standard customized device to be tested based on the anomaly time, and generating a test work order for the non-standard customized device to be tested and sending it to the third terminal device used by the target after-sales engineer.

[0067] Here, "abnormal time" refers to the time when the corresponding equipment may malfunction. In this case, the training data for the anomaly prediction model can be adjusted to include historical operating status data, corresponding anomaly judgment results, and anomaly times. In this embodiment, the non-standard customized equipment to be tested can be evenly distributed among all after-sales engineers based on the abnormal time, ensuring that the daily workload of after-sales engineers remains within a reasonable range.

[0068] Optionally, obtaining the target after-sales engineer corresponding to the non-standard customized equipment under test through the manufacturer-side agent robot may include:

[0069] The manufacturer-side agent robot obtains each candidate after-sales engineer corresponding to the non-standard customized equipment under test according to the equipment type, and obtains the number of pending work orders corresponding to each candidate after-sales engineer.

[0070] The target after-sales engineer is determined from among the candidate after-sales engineers based on the number of pending work orders by the manufacturer-side agent robot.

[0071] In this embodiment, when assigning a target after-sales engineer to the non-standard customized equipment under test, firstly, based on the equipment type corresponding to the non-standard customized equipment under test and the preset correspondence between equipment types and after-sales engineers, the candidate after-sales engineers corresponding to the non-standard customized equipment under test are found. Next, the number of pending work orders corresponding to each candidate after-sales engineer is obtained through the collaborative office system. Finally, the candidate after-sales engineer with the smallest number of pending work orders is selected as the target after-sales engineer.

[0072] The advantage of the above settings is that they can improve the scheduling rationality of the workload of after-sales engineers and improve the maintenance efficiency of non-standard customized equipment under test.

[0073] Optionally, the technical solution of this embodiment may further include: generating an online detection task through the manufacturer-side agent robot according to preset detection configuration information, and generating online detection information based on the online detection task and sending it to each of the device-side agent robots;

[0074] The manufacturer-side agent robot obtains the online detection results corresponding to each device-side agent robot based on the feedback from each device-side agent robot regarding the online detection information, and obtains the number of devices in operation based on the online detection results.

[0075] The preset detection configuration information can be the configuration information for daily online detection, including interval time, triggering method, etc. In this embodiment, the manufacturer-side agent robot can automatically create online detection tasks according to the preset detection configuration information. These online detection tasks can run independently as background threads. Then, the online detection tasks can automatically send online detection information to each device-side agent robot at set intervals. If a device-side agent robot is online, it will generate corresponding feedback information and send it to the manufacturer-side agent robot upon receiving the online detection information. If the manufacturer-side agent robot successfully receives feedback information from a device-side agent robot, it can determine that the online detection result for that device-side agent robot is online; otherwise, it can determine that the online detection result for that device-side agent robot is offline. Thus, the online detection result for each device-side agent robot can be obtained. Finally, the manufacturer-side agent robot can count the number of online non-standard customized devices based on the online detection results, which can be used as the number of running devices.

[0076] The advantages of the above settings are that they enable real-time online monitoring of equipment, timely detection of offline equipment, and improved equipment maintenance efficiency.

[0077] The technical solution of this invention involves a manufacturer-side agent robot acquiring other non-standard customized devices corresponding to the current non-standard customized device based on first operating status data; acquiring other device-side agent robots corresponding to each other non-standard customized device through the manufacturer-side agent robot, and acquiring second operating status data corresponding to each other non-standard customized device through the other device-side agent robots; calling a pre-trained anomaly prediction model through the manufacturer-side agent robot, acquiring the anomaly probability corresponding to each other non-standard customized device based on each second operating status data, and determining the non-standard customized device to be tested among the other non-standard customized devices based on the anomaly probability; and then, through the manufacturer-side... The agent robot identifies the target after-sales engineer for the non-standard customized equipment under test and generates a corresponding test work order for the equipment. This work order is then sent to the third-party terminal device used by the target after-sales engineer, enabling the engineer to perform maintenance operations based on the work order. By establishing an anomaly prediction model, anomalies can be predicted for other non-standard customized equipment that has not yet shown any anomalies. Based on the anomaly prediction results, appropriate after-sales engineers can be assigned to perform equipment maintenance. This allows for reasonable scheduling of the after-sales engineer's workload, proactive maintenance of potentially faulty equipment, avoidance of sudden fault peaks, reduction of equipment downtime, improved service quality, and increased customer satisfaction.

[0078] In one specific embodiment of this example, the structure of the industrial equipment operation management system can be as follows: Figure 3 As shown, the system comprises a device layer, a customer layer, and a manufacturer layer. The device layer includes device-side agent robot 1, device-side agent robot 2, and device-side agent robot 3. Device-side agent robot 1 operates on equipment delivered to customer 22, while device-side agent robots 2 and 3 operate on equipment delivered to customer 11. The customer layer has two customers: customer 11 and customer 22. Customer 11's device manager directly receives data reports from device-side agent robots 2 and 3, while customer 22's device manager directly receives data reports from device-side agent robot 1. Device-side agent robots 1-3 report to and accept queries from the manufacturer-side agent robot, which then reports to the manufacturer's after-sales management personnel.

[0079] In a specific example, the device-side agent robot is not online 24 / 7, but rather activates based on the device's power-on and usage. Initially, when the equipment operator brings device 2 online, device-side agent robot 2 proactively reports to the customer's (11) equipment manager and the manufacturer's (11) agent robot, for example, by sending an online notification message to inform them that it is online. Afterwards, when the equipment operator uses device 2, the customer's (11) equipment manager sends query tasks to device-side agent robot 2 via instant messaging to obtain the current operating status data of the device, and based on the basic settings, it can receive a normal equipment report once per hour. Simultaneously, device-side agent robot 2 can accept scheduled queries from the manufacturer's (11) agent robot and report accordingly.

[0080] When equipment malfunctions, the equipment-side agent robot 2 can immediately notify both the customer's (11) equipment manager and the manufacturer-side agent robot. The manufacturer-side agent robot then sends the malfunction notification to the manufacturer's after-sales management personnel. The customer's (11) equipment manager receives timely alerts and a brief report of the malfunction, allowing for an initial assessment of whether the issue can be resolved independently. If the issue can be resolved independently, the manager handles the malfunction and notifies the equipment-side agent robot 2 to clear the fault alarm. Correspondingly, the manufacturer-side agent robot clears the corresponding malfunction alarm notification.

[0081] If the problem cannot be resolved independently, Customer 11's equipment manager sends a fault assistance request to the manufacturer's agent robot via the equipment-side agent robot 2. Based on the infrastructure, the manufacturer-side agent robot summarizes the operational status information and fault assistance requests sent by the faulty equipment-side agent robot and immediately notifies the manufacturer's after-sales management personnel for handling. This triggers an assessment of potential faults in other equipment, alerting the manufacturer's after-sales management personnel to other possible equipment malfunctions, allowing them to appropriately arrange for after-sales engineers to conduct on-site inspections. After completing the repair, the manufacturer-side agent robot can update the manufacturer's equipment database for future assessments.

[0082] The manufacturer-side agent robot is online 24 / 7. It can receive reports from the device-side agent robot and periodically inspect the operating status of the device-side agent robot based on the number of online devices. When a device malfunctions, the manufacturer-side agent robot can notify the manufacturer's after-sales management personnel. Upon receiving a new malfunction request from the device-side agent robot, it can summarize the device's operating status information and then notify the manufacturer's after-sales management personnel for handling.

[0083] Example 3

[0084] Figure 4This is a schematic diagram of an industrial equipment operation management system provided in Embodiment 3 of the present invention. The industrial equipment operation management system 30 may include a manufacturer-side agent robot 31 and multiple equipment-side agent robots 32, wherein the equipment-side agent robots 32 operate on non-standard customized equipment;

[0085] Each of the device-side agent robots 32 is used to interact with the device operation software of the corresponding non-standard customized equipment based on the extended application programming interface, and to collect the first operating status data corresponding to the non-standard customized equipment.

[0086] If an anomaly is detected in the non-standard customized equipment based on the first operating status data, an anomaly assistance request is generated, and the anomaly assistance request and the first operating status data are sent to the manufacturer-side agent robot 31.

[0087] The manufacturer-side agent robot 31 is used to call a first instant messaging tool to send the abnormal assistance request and the first operating status data to a first terminal device used by the manufacturer's after-sales management personnel, so that the manufacturer's after-sales management personnel can handle the abnormality based on the abnormal assistance request and the first operating status data.

[0088] The technical solution of this invention involves an equipment-side agent robot 32 interacting with the corresponding non-standard customized equipment's operating software via an extended application programming interface (API) to collect first operating status data corresponding to the non-standard customized equipment. If an anomaly is detected in the non-standard customized equipment based on the first operating status data, an anomaly assistance request is generated and sent along with the first operating status data to the manufacturer-side agent robot 31. The manufacturer-side agent robot 31 then invokes a first instant messaging tool to send the anomaly assistance request and the first operating status data to a first terminal device used by the manufacturer's after-sales management personnel, enabling the manufacturer's after-sales management personnel to handle the anomaly based on the anomaly assistance request and the first operating status data. By setting up manufacturer-side agent robots and equipment-side agent robots, and adding an extended API to the equipment operating software, the interaction between the manufacturer-side agent robots, equipment-side agent robots, and equipment operating software enables automatic reporting of equipment operating status and anomalies. This allows for efficient and accurate anomaly diagnosis of non-standard customized equipment, improving the operational management efficiency of industrial equipment.

[0089] In some embodiments, the operation management method for industrial equipment may be implemented as a computer program tangibly contained in a computer-readable storage medium. When the computer program is executed by a processor, one or more steps of the operation management method for industrial equipment described above may be performed. Alternatively, in other embodiments, the processor may be configured to perform the operation management method for industrial equipment by any other suitable means (e.g., by means of firmware).

[0090] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays, application-specific integrated circuits (ASICs), application-specific standard products (ASICs), system-on-a-chip (SoCs), complex programmable logic devices, computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0091] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0092] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory, read-only memory, erasable programmable read-only memory, optical fibers, portable compact disk read-only memory, optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0093] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0094] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact via a communication network. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server.

[0095] This embodiment may also include a computer program product, which includes a computer program that, when executed by a processor, implements the operation management method for industrial equipment provided in any embodiment of the present invention.

[0096] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0097] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for operating and managing industrial equipment, characterized in that, An industrial equipment operation management system applied to include manufacturer-side agent robots and multiple equipment-side agent robots, wherein the equipment-side agent robots operate on non-standard customized equipment, including: The agent robot on the current device side interacts with the device operation software of the corresponding current non-standard customized device through the extended application programming interface, and collects the first operating status data corresponding to the current non-standard customized device. If the current non-standard customized equipment is detected to be abnormal by the agent robot on the current device side based on the first operating status data, an abnormality assistance request is generated and the abnormality assistance request and the first operating status data are sent to the agent robot on the manufacturer side. The manufacturer-side agent robot invokes a first instant messaging tool to send the abnormal assistance request and the first operating status data to a first terminal device used by the manufacturer's after-sales management personnel, so that the manufacturer's after-sales management personnel can handle the abnormality based on the abnormal assistance request and the first operating status data. The manufacturer-side agent robot obtains other non-standard customized equipment corresponding to the current non-standard customized equipment based on the first operating status data; The manufacturer-side agent robot obtains the other equipment-side agent robot corresponding to each of the other non-standard customized equipment, and the other equipment-side agent robot obtains the second operating status data corresponding to each of the other non-standard customized equipment. The manufacturer-side agent robot invokes a pre-trained anomaly prediction model, obtains the anomaly probability corresponding to each of the other non-standard customized devices based on each of the second operating state data, and determines the non-standard customized device to be tested among the other non-standard customized devices based on the anomaly probability. The manufacturer-side agent robot obtains the target after-sales engineer corresponding to the non-standard customized equipment to be tested, and generates a test work order corresponding to the non-standard customized equipment to be tested. The test work order is then sent to the third terminal device used by the target after-sales engineer so that the target after-sales engineer can perform maintenance operations based on the test work order.

2. The method according to claim 1, characterized in that, After detecting an anomaly in the current non-standard customized equipment based on the first operating status data, the method further includes: The first operating status data is sent to the second terminal device used by the customer equipment manager corresponding to the current non-standard customized equipment by calling the second instant messaging tool through the agent robot on the current device side.

3. The method according to claim 1, characterized in that, The manufacturer-side agent robot invokes a first instant messaging tool to send the exception assistance request and the first operational status data to a first terminal device used by the manufacturer's after-sales management personnel, including: The manufacturer-side agent robot invokes a pre-trained anomaly handling model to obtain the anomaly type and handling suggestions based on the first operating status data. The manufacturer-side agent robot invokes a first instant messaging tool to send the exception assistance request, the first operating status data, the exception type, and the handling suggestions to a first terminal device used by the manufacturer's after-sales management personnel.

4. The method according to claim 1, characterized in that, Based on the first operating status data, the manufacturer-side agent robot obtains other non-standard customized equipment corresponding to the current non-standard customized equipment, including: The manufacturer-side agent robot obtains the equipment type corresponding to the current non-standard customized equipment based on the first operating status data, and obtains other non-standard customized equipment corresponding to the current non-standard customized equipment based on the equipment type.

5. The method according to claim 1, characterized in that, The target after-sales engineer corresponding to the non-standard customized equipment under test is obtained through the manufacturer-side agent robot, including: The manufacturer-side agent robot obtains each candidate after-sales engineer corresponding to the non-standard customized equipment under test according to the equipment type, and obtains the number of pending work orders corresponding to each candidate after-sales engineer. The target after-sales engineer is determined from among the candidate after-sales engineers based on the number of pending work orders by the manufacturer-side agent robot.

6. The method according to claim 1, characterized in that, Also includes: The manufacturer-side agent robot generates online detection tasks based on preset detection configuration information, and generates online detection information based on the online detection tasks, which is then sent to each of the device-side agent robots. The manufacturer-side agent robot obtains the online detection results corresponding to each device-side agent robot based on the feedback from each device-side agent robot regarding the online detection information, and obtains the number of devices in operation based on the online detection results.

7. An industrial equipment operation management system, characterized in that, It includes manufacturer-side agent robots and multiple device-side agent robots, the device-side agent robots operating on non-standard customized equipment; Each of the aforementioned device-side agent robots is used to interact with the device operation software of the corresponding non-standard customized equipment based on the extended application programming interface, and to collect the first operating status data corresponding to the non-standard customized equipment. If an anomaly is detected in the non-standard customized equipment based on the first operating status data, an anomaly assistance request is generated, and the anomaly assistance request and the first operating status data are sent to the manufacturer-side agent robot. The manufacturer-side agent robot is used to call a first instant messaging tool to send the abnormal assistance request and the first operating status data to a first terminal device used by the manufacturer's after-sales management personnel, so that the manufacturer's after-sales management personnel can handle the abnormality based on the abnormal assistance request and the first operating status data. Based on the first operating status data, obtain the other non-standard customized equipment corresponding to the current non-standard customized equipment; Obtain the other equipment-side agent robot corresponding to each of the other non-standard customized equipment, and obtain the second operating status data corresponding to each of the other non-standard customized equipment through the other equipment-side agent robot; The pre-trained anomaly prediction model is invoked, and the anomaly probability corresponding to each of the other non-standard customized devices is obtained based on each of the second running state data. Based on the anomaly probability, the non-standard customized device to be tested is determined among the other non-standard customized devices. The target after-sales engineer corresponding to the non-standard customized equipment to be tested is obtained, and a test work order corresponding to the non-standard customized equipment to be tested is generated. The test work order is then sent to a third terminal device used by the target after-sales engineer so that the target after-sales engineer can perform maintenance operations based on the test work order.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the operation management method for the industrial equipment as described in any one of claims 1-6.

9. A computer program product, characterized in that, It includes a computer program that, when executed by a processor, implements the operation management method for the industrial equipment as described in any one of claims 1-6.

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