Abnormal information processing method and device, electronic equipment and storage medium
By quickly matching and notifying the appropriate employees for handling exceptions using an employee model, the inefficiency of the Andon system in processing vehicle production workshop exceptions was solved, improving the success rate of information transmission and processing efficiency, and reducing workshop risks.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- NIO TECH ANHUI CO LTD
- Filing Date
- 2026-03-18
- Publication Date
- 2026-06-19
AI Technical Summary
The existing Andon system is unable to quickly and accurately handle abnormal issues in the vehicle production workshop, which may lead to workshop shutdowns and product quality problems.
By matching employees using an employee model, and based on the location of the anomaly and the description of the problem, the most suitable employee for handling the anomaly can be quickly identified and notified. The anomaly information can be sent using a terminal device so that the employee can handle the anomaly quickly.
It improved the success rate of abnormal information transmission, increased the matching rate between abnormal issues and handling personnel, reduced the risk of workshop downtime and product quality problems, enhanced the scalability of the dimming system, and reduced noise impact.
Smart Images
Figure CN122243064A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the manufacturing field, and specifically to a method, apparatus, electronic device, and storage medium for processing abnormal information. Background Technology
[0002] Andon, also known as Dark Light, is a multimedia automated control system with sound and light. It is specifically designed for information management and control systems in automobile production and assembly lines, and has become an indispensable part of the complete automobile production line. The Andon system can collect relevant equipment and quality management information on the production line, process it, and then control the lighting and sound alarm systems distributed throughout the workshop.
[0003] In vehicle production workshops, the Andon system is typically used to collect information on equipment and production status on the production line, including whether the equipment is operating normally (whether there are alarms), whether individual workstations are experiencing material shortages or blockages, and whether there are personnel operating on-site or needing assistance with quality issues.
[0004] The Andon system reads equipment operating status signals from field device controllers and places corresponding buttons or pull ropes at workstations where personnel are present. When workers need assistance, they press the button or pull the rope. These statuses are collected by the Andon system's backend service and converted into on-site displays and audible / visual alarms. Field team leaders or equipment maintenance personnel, who need to respond to anomalies, will hear the alarm and check the Andon system for the problem. However, after the Andon system is configured with anomaly reporting mode, the relevant personnel passively receive reports, making it uncertain whether the personnel handling the problem can quickly resolve anomalies occurring in the vehicle production workshop, potentially causing production line shutdowns and product quality issues.
[0005] Accordingly, there is a need in the field for a new solution that can quickly and reasonably handle anomalies on the vehicle production line to address the above problems. Summary of the Invention
[0006] In order to overcome the above-mentioned shortcomings, this application is made to solve or at least partially solve the technical problem that current dimming systems are unable to quickly and accurately handle abnormal problems in vehicle production workshops.
[0007] In a first aspect, a method for processing abnormal information is provided, including:
[0008] In response to receiving abnormal information from the target production area, extract the abnormal location and problem description information from the abnormal information;
[0009] Using an employee model, employees are matched based on the abnormal location and the problem description information to obtain employees for abnormal handling. The employee model is obtained by modeling multiple employees based on their work information and skill information in the target production area.
[0010] The exception information is sent to the exception handling staff so that the exception handling staff can perform exception handling based on the exception information.
[0011] In one technical solution of the above method, before using the employee model to match employees based on the abnormal location and the problem description to obtain the abnormal handling employees, the method further includes: modeling the multiple employees based on their work information, skill information and abnormal historical handling records to obtain the employee model.
[0012] In one technical solution of the above method, the work information includes workstation location, shift clock information, and job information.
[0013] In one technical solution of the above method, the step of using an employee model to match employees based on the anomaly location and the problem description to obtain anomaly handling employees includes:
[0014] Using the employee model, based on the abnormal location, and the workstation location and shift clock information of the multiple employees, on-duty employees are matched to obtain a first set of employees;
[0015] Using the employee model, anomaly handling capabilities are matched based on the problem description information, the job information, skill information, and anomaly history handling records of the multiple employees to obtain a second set of employees;
[0016] The employee to be handled for the anomaly is determined based on the first set of employees and the second set of employees.
[0017] In one technical solution of the above method, the employee model is used to match anomaly handling capabilities based on the problem description information, the job information, skill information, and anomaly history handling records of the multiple employees to obtain a second employee set, including:
[0018] Using the employee model, job matching is performed based on the problem description information and the job information of the multiple employees to obtain a third employee set;
[0019] Using the employee model, skill matching is performed based on the problem description information and the skill information of the multiple employees to obtain a fourth employee set;
[0020] Using the employee model, the historical processing information is matched with the abnormal historical processing records of the multiple employees to obtain the fifth employee set;
[0021] The second employee set is determined based on the third employee set, the fourth employee set, and the fifth employee set.
[0022] In one technical solution of the above method, sending the exception information to the exception handling employee so that the exception handling employee can perform exception handling based on the exception information includes: sending the exception information to the mobile terminal bound to the exception handling employee so that the exception handling employee can learn the exception details through the exception information and perform exception handling.
[0023] In a second aspect, an apparatus for processing abnormal information is provided, comprising:
[0024] The information extraction module is used to extract the abnormal location and problem description information from the abnormal information in response to receiving abnormal information from the target production area;
[0025] The matching module is used to match employees based on the abnormal location and the problem description information using an employee model to obtain employees for abnormal handling. The employee model is obtained by modeling multiple employees based on their work information and skill information in the target production area.
[0026] A communication module is used to send the exception information to the exception handling employee so that the exception handling employee can perform exception handling based on the exception information.
[0027] In one technical solution of the above-mentioned device, the device further includes: an employee modeling module, used to model the multiple employees based on their work information, skill information and abnormal history processing records, to obtain the employee model.
[0028] In one technical solution of the above-mentioned device, the work information includes workstation location, shift clock information, and job information.
[0029] In one technical solution of the above-mentioned device, the matching module is used to use the employee model to match on-duty employees based on the abnormal location and the workstation locations and shift clock information of the multiple employees to obtain a first set of employees; the matching module is also used to use the employee model to match abnormal handling capabilities based on the problem description information, the job information, skill information and abnormal historical handling records of the multiple employees to obtain a second set of employees; the matching module is also used to determine the abnormal handling employees based on the first set of employees and the second set of employees.
[0030] In one technical solution of the above-mentioned device, the matching module is used to perform job matching based on the problem description information and the job information of the multiple employees using the employee model to obtain a third employee set; the matching module is also used to perform skill matching based on the problem description information and the skill information of the multiple employees using the employee model to obtain a fourth employee set; the matching module is also used to perform historical processing matching based on the problem description information and the abnormal historical processing records of the multiple employees using the employee model to obtain a fifth employee set; the matching module is also used to determine a second employee set based on the third employee set, the fourth employee set, and the fifth employee set.
[0031] In one technical solution of the above device, the communication module is used to send the abnormal information to the mobile terminal bound to the abnormal handling employee, so that the abnormal handling employee can learn the abnormal details through the abnormal information and perform abnormal handling.
[0032] In a third aspect, an electronic device is provided, comprising at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program that, when executed by the at least one processor, implements the aforementioned method for processing abnormal information.
[0033] In a fourth aspect, a computer-readable storage medium is provided, wherein a plurality of program codes are stored therein, the program codes being adapted to be loaded and run by a processor to perform the above-described method for handling exception information.
[0034] The above-described technical solutions of this application have at least one or more of the following beneficial effects:
[0035] In the anomaly information processing scheme provided in this application, when an anomaly occurs in the production area, employees in the production area can send anomaly information carrying the anomaly location and problem description information to a server (e.g., a server integrated with a dimming control system) via terminal devices (such as smart bracelets or other mobile terminals). The server uses a pre-trained employee model to match employees based on the anomaly location and problem description information, quickly and accurately matching employees capable of handling the anomaly. The anomaly information is then sent to the terminal devices of these employees, allowing them to quickly understand the details of the anomaly and resolve it promptly. This anomaly handling technology improves the success rate of on-site information transmission and the matching degree between anomalies and handling personnel, reducing the risk of production line downtime and product quality problems. Furthermore, it adds problem description information representing specific details of the anomaly to the anomaly information, thereby improving the success rate and efficiency of anomaly handling employees. In addition, it improves the scalability of the dimming system and reduces the impact of on-site noise on information transmission. Attached Figure Description
[0036] The disclosure of this application will become more readily understood with reference to the accompanying drawings. It will be readily understood by those skilled in the art that these drawings are for illustrative purposes only and are not intended to limit the scope of protection of this application. Wherein:
[0037] Figure 1 This is a flowchart illustrating the main steps of the abnormal information processing method in some embodiments of this application;
[0038] Figure 2 This is a schematic diagram illustrating the working principle of an exception handling method in one example of this application;
[0039] Figure 3 This is a structural block diagram of the abnormal information processing device in some embodiments of this application;
[0040] Figure 4 These are structural block diagrams of some embodiments of this application. Detailed Implementation
[0041] Some embodiments of this application are described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of this application and are not intended to limit the scope of protection of this application.
[0042] In the description of this application, "module" and "processor" can include hardware, software, or a combination of both. A module can include hardware circuitry, various suitable sensors, communication ports, memory, and may also include software components, such as program code, or a combination of software and hardware. A processor can be a central processing unit, microprocessor, image processor, digital signal processor, or any other suitable processor. The processor has data and / or signal processing capabilities. The processor can be implemented in software, in hardware, or a combination of both. Computer-readable storage media includes any suitable medium capable of storing program code, such as magnetic disks, hard disks, optical disks, flash memory, read-only memory, random access memory, etc. The term "A and / or B" means all possible combinations of A and B, such as only A, only B, or A and B. The terms "at least one A or B" or "at least one of A and B" have a similar meaning to "A and / or B" and can include only A, only B, or A and B. The singular terms "a" or "this" can also include plural forms.
[0043] The relevant user personal information that may be involved in the various embodiments of this application is processed in strict accordance with the requirements of laws and regulations, following the principles of legality, legitimacy, and necessity, based on the reasonable purpose of the business scenario, and includes personal information that users actively provide or that is generated as a result of using the product / service, as well as personal information obtained with user authorization.
[0044] The personal information processed in this application will vary depending on the specific product / service scenario and will be based on the specific scenario in which the user uses the product / service. This may involve the user's account information, device information, driving information, vehicle information, or other related information. This application will treat the user's personal information and its processing with the utmost diligence.
[0045] This application attaches great importance to the security of users' personal information and has taken reasonable and feasible security protection measures that comply with industry standards to protect users' information and prevent unauthorized access, disclosure, use, modification, damage or loss of personal information.
[0046] Figure 1 This is a schematic flowchart illustrating the main steps of the abnormal information processing method in some embodiments of this application. For example... Figure 1 As shown, the method for processing abnormal information in this application embodiment includes the following steps:
[0047] S1: In response to receiving abnormal information from the target production area, extract the abnormal location and problem description information from the abnormal information.
[0048] In this embodiment, when an employee discovers an anomaly while working in the target production area, they can send an anomaly message carrying the location of the anomaly and a description of the problem to the server through a terminal device.
[0049] The target production area can include vehicle production workshops, vehicle assembly workshops, vehicle repair workshops, etc. Anomalies discovered by staff can include quality issues with parts or equipment malfunctions. The terminal devices used by employees to send anomaly information can be fixed / mobile terminals with integrated dimming systems. The server can be a server with an integrated dimming control system. The anomaly location can be the location provided by the employee or the employee's workstation location. The problem description information can be a textual or audio description of the anomaly provided by the employee, as well as images or videos showing the anomaly.
[0050] After receiving the exception information, the server extracts the exception location and problem description information from the exception information.
[0051] S2: Using the employee model, employees are matched based on the location of the anomaly and the problem description information to obtain the employees who handle the anomaly.
[0052] In this embodiment, the employee model is obtained by modeling multiple employees based on their work and skill information in the target production area. The abnormal location and problem description information are used as input to the employee model. The model is then used to match employees, outputting the abnormal handling employees that precisely match the abnormal location and problem description information. The employee model can include at least one of the following models: Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM).
[0053] In one implementation, multiple employees are modeled based on their work information, skill information, and historical anomaly handling records to obtain an employee model. The employee's work information reflects their job content; when an employee's work content is similar to the problem description, that employee is more likely to solve the anomaly. The employee's skill information reflects their mastery of a particular skill; when an employee's skill information is similar to the required skill corresponding to the problem description, that employee is more likely to solve the anomaly. The employee's historical anomaly handling records reflect their handling of anomalies (whether they have resolved any historical anomalies, the types of anomalies resolved, etc.); when an employee's historical anomaly handling records show that the resolved historical anomalies are similar to the problem description, that employee is more likely to solve the anomaly.
[0054] In one implementation, the work information includes workstation location, shift clock information, and job position information. When multiple employees can resolve an anomaly corresponding to the problem description, the employee closest to the anomaly location and who has already clocked in is selected to resolve the anomaly by considering their workstation locations and shift clock information, thereby improving the efficiency of anomaly resolution. The employee's job position information reflects their job duties and required skills, which is helpful in determining whether they can resolve the anomaly corresponding to the problem description.
[0055] In one implementation, S2 may include the following steps:
[0056] S2-1: Using the employee model, based on abnormal locations and the workstation locations and shift clock information of multiple employees, on-duty employees are matched to obtain the first set of employees.
[0057] In this embodiment, the employee model may include an on-duty employee matching sub-model. After determining the employees who have clocked in and out in the target production area based on the shift clock information using the on-duty employee matching sub-model, the abnormal location and workstation location are matched to obtain a set of all employees who are located near the abnormal location (determined by a preset distance threshold) and have clocked in and out, which is denoted as the first employee set.
[0058] S2-2: Using the employee model, based on the problem description information, the job information, skill information and anomaly history processing records of multiple employees, the anomaly handling capabilities are matched to obtain the second set of employees.
[0059] In this embodiment, the employee model may include an exception handling capability matching sub-model. Using the exception handling capability matching sub-model, based on the job information, skill information, and exception handling history records of each employee among multiple employees (e.g., all employees) in the target production area, exception handling capability matching is performed on the problem description information to obtain a set of all employees with the capabilities required to solve the exception problem corresponding to the problem description information, denoted as the second employee set.
[0060] In one implementation, S2-2 may include the following steps:
[0061] S2-2-1: Using the employee model, based on the problem description information and the job information of multiple employees, job matching is performed to obtain a third set of employees.
[0062] S2-2-2: Using the employee model, skill matching is performed based on the problem description information and the skill information of multiple employees to obtain the fourth employee set.
[0063] S2-2-3: Using the employee model, based on the problem description information and the historical processing records of multiple employees, the historical processing situation is matched to obtain the fifth employee set.
[0064] S2-2-4: Determine the second set of employees based on the third set of employees, the fourth set of employees, and the fifth set of employees.
[0065] In this embodiment, an anomaly handling capability matching sub-model can be used to match anomaly description information and employee capabilities from three dimensions: job position, skills, and historical handling status, resulting in a third, fourth, and fifth employee set. The union of the third, fourth, and fifth employee sets can be used to obtain a second employee set. All employees in the second employee set have three matching results (successful or unsuccessful) corresponding to the aforementioned three dimensions, which helps to ultimately determine the employees for anomaly handling based on the number and degree of matching among the three results.
[0066] S2-3: Based on the first set of employees and the second set of employees, determine the employees to be handled in case of anomalies.
[0067] In this embodiment, the intersection of the first set of employees and the second set of employees can be obtained to obtain all employees who are near the abnormal location, have clocked in and have the ability required to solve the abnormal problem corresponding to the problem description information, and then the abnormal handling employees can be selected from them.
[0068] S3: Send exception information to the exception handling staff so that they can handle the exception based on the exception information.
[0069] In this embodiment, the exception information is sent to the terminal bound to the exception handling employee. Upon receiving the exception information, the exception handling employee can promptly understand the exception content and quickly resolve the issue. The terminal bound to the exception handling employee may include at least one of the following: a smart bracelet, mobile phone, tablet computer, or desktop computer.
[0070] In one implementation, S3 may include the following steps: sending exception information to the mobile terminal bound to the exception handling employee, so that the exception handling employee can learn the exception details through the exception information and handle the exception.
[0071] In this embodiment, the mobile terminal includes at least one of a smart bracelet and a mobile phone, preferably a smart bracelet. When the smart bracelet worn by the employee handling the anomaly receives the anomaly information, it can provide a prompt via audio or vibration. The employee handling the anomaly can understand the details of the anomaly through the anomaly information, so that they can promptly prepare the necessary tools and technical means to solve the problem, thereby quickly resolving the anomaly.
[0072] Figure 2 This is a schematic diagram illustrating the working principle of an exception handling method in one example of this application. For example... Figure 2 As shown, employee Zhang San discovers a quality issue with a vehicle part. He adds descriptive text / images / videos about the problem to the Andon system, then pushes an anomaly message containing the problem description and location to the Andon system. The status controller then generates a problem work order by producing the status parameters of the equipment handling the part. This work order, combined with the Andon system's employee model, receives the anomaly information via a smart bracelet. The Agent module analyzes the nearest workstation, identifies the employee Xiao Li, who is already scheduled for work, has clocked in, and meets the required skills. Xiao Li's bracelet receives the anomaly information, displaying the specific location of the problem, its description, and the person who discovered it. Based on this information, Xiao Li quickly goes to the site to resolve the issue. The system analyzes Xiao Li's problem-solving efficiency based on the processing time and results, creating historical data on the anomaly information.
[0073] In the anomaly handling solution provided in this application, when an anomaly occurs in the production area, employees in the production area can send anomaly information carrying the anomaly location and problem description to the server via terminal devices. The server uses a pre-trained employee model to match employees based on the anomaly location and problem description information, quickly and accurately matching employees capable of handling the anomaly. The anomaly information is then sent to the terminal devices of these employees, allowing them to quickly understand the details of the anomaly and resolve it promptly. This anomaly handling technology improves the success rate of on-site information transmission and enhances the matching degree between anomalies and handling personnel, reducing the risk of production line downtime and product quality issues. Furthermore, it allows for the addition of problem description information representing specific details of the anomaly to the anomaly information, thereby improving the success rate and efficiency of anomaly handling employees. In addition, it improves the scalability of the dimming system and reduces the impact of on-site noise on information transmission.
[0074] It should be noted that although the steps in the above embodiments are described in a specific order, those skilled in the art will understand that in order to achieve the effect of this application, different steps do not necessarily have to be executed in such an order. They can be executed simultaneously (in parallel) or in other orders. These adjusted solutions are equivalent to the technical solutions described in this application and therefore will also fall within the protection scope of this application.
[0075] Those skilled in the art will understand that all or part of the processes in the method of the above-described embodiment can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form. The computer-readable storage medium can include any entity or device capable of carrying computer program code, a medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory, a random access memory, an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.
[0076] Figure 3 This is a structural block diagram of an anomaly information processing apparatus in some embodiments of this application. For example... Figure 3 As shown, the abnormal information processing device includes:
[0077] The information extraction module 100 is used to extract the abnormal location and problem description information from the abnormal information in response to receiving abnormal information from the target production area.
[0078] The matching module 200 is used to match employees based on the abnormal location and problem description information using the employee model to obtain the employees to handle the abnormality. The employee model is obtained by modeling multiple employees based on the work information and skill information of multiple employees in the target production area.
[0079] The communication module 300 is used to send exception information to the exception handling staff so that the exception handling staff can handle the exception based on the exception information.
[0080] In one technical solution of the above-mentioned device, the abnormal information processing device further includes: an employee modeling module, which is used to model multiple employees based on their work information, skill information and abnormal historical processing records, to obtain an employee model.
[0081] In one technical solution of the aforementioned device, the work information includes workstation location, shift clock information, and job information.
[0082] In one technical solution of the above-mentioned device, the matching module 200 is used to use the employee model to match on-duty employees based on the abnormal location, as well as the workstation location and shift clock information of multiple employees, to obtain a first set of employees; the matching module 200 is also used to use the employee model to match abnormal handling capabilities based on the problem description information, the job information, skill information and abnormal historical handling records of multiple employees, to obtain a second set of employees; the matching module 200 is also used to determine the abnormal handling employees based on the first set of employees and the second set of employees.
[0083] In one technical solution of the above-mentioned device, the matching module 200 is used to perform job matching based on the problem description information and the job information of multiple employees using the employee model to obtain a third employee set; the matching module 200 is also used to perform skill matching based on the problem description information and the skill information of multiple employees using the employee model to obtain a fourth employee set; the matching module 200 is also used to perform historical processing matching based on the problem description information and the abnormal historical processing records of multiple employees using the employee model to obtain a fifth employee set; the matching module 200 is also used to determine a second employee set based on the third employee set, the fourth employee set, and the fifth employee set.
[0084] In one technical solution of the above-mentioned device, the communication module 300 is used to send abnormal information to the mobile terminal bound to the abnormal handling employee, so that the abnormal handling employee can know the abnormal details through the abnormal information and perform abnormal handling. The mobile terminal includes at least one of a smart bracelet and a mobile phone.
[0085] It should be noted that the specific implementation of the abnormal information processing device in this application embodiment is similar to the specific implementation of the abnormal information processing method in this disclosure embodiment, and the technical effects of the abnormal information processing device in this disclosure embodiment are similar to the technical effects of the abnormal information processing method in this disclosure embodiment. For details, please refer to the description of the abnormal information processing method section. In order to reduce redundancy, it will not be described in detail.
[0086] Another aspect of this application provides an electronic device, which includes at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program, which, when executed by the at least one processor, implements the method described in any of the above-mentioned technical solutions for processing abnormal information.
[0087] Below, for reference Figure 4 To describe an electronic device according to embodiments of this disclosure. For example... Figure 4 As shown, a processor can be a central processing unit (CPU) or other form of processing unit with data processing capabilities and / or instruction execution capabilities, and can control other components in an electronic device to perform desired functions.
[0088] The memory can store one or more computer program products, and the memory can include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program products can be stored on the computer-readable storage medium, and the processor can run the computer program products to implement the exception information processing methods and / or other desired functions of the various embodiments of this disclosure described above.
[0089] In one example, the electronic device may also include input devices and output devices, which are interconnected via a bus system and / or other forms of connection mechanism (not shown).
[0090] In addition, the input device may also include, for example, a keyboard, a mouse, etc.
[0091] This output device can output various information to the outside, including determined distance information, direction information, etc. The output device may include, for example, a display, a speaker, a printer, and a communication network and its connected remote output devices, etc.
[0092] Of course, for the sake of simplicity, Figure 4Only some of the components of the electronic device relevant to this disclosure are shown, omitting components such as buses, input / output interfaces, etc. In addition, the electronic device may include any other suitable components depending on the specific application.
[0093] Another aspect of this application provides a computer-readable storage medium.
[0094] In one embodiment of a computer-readable storage medium according to this application, the computer-readable storage medium can be configured to store a program for processing exception information in accordance with the above-described method embodiments. This program can be loaded and run by a processor to implement the above-described exception information processing method. For ease of explanation, only the parts related to the embodiments of this application are shown; for specific technical details not disclosed, please refer to the method section of the embodiments of this application. The computer-readable storage medium can be a storage device comprising various electronic devices. Optionally, in the embodiments of this application, the computer-readable storage medium is a non-transitory computer-readable storage medium.
[0095] The computer-readable storage medium may be any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof.
[0096] The technical solution of this application has been described above with reference to one embodiment shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of this application is obviously not limited to these specific embodiments. Without departing from the principles of this application, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of this application.
Claims
1. A method for processing abnormal information, characterized in that, include: In response to receiving abnormal information from the target production area, extract the abnormal location and problem description information from the abnormal information; Using an employee model, employees are matched based on the abnormal location and the problem description information to obtain employees for abnormal handling. The employee model is obtained by modeling multiple employees based on their work information and skill information in the target production area. The exception information is sent to the exception handling staff so that the exception handling staff can perform exception handling based on the exception information.
2. The method according to claim 1, characterized in that, Before using the employee model to match employees based on the anomaly location and the problem description to obtain the employees for anomaly handling, the process further includes: Based on the work information, skill information, and anomaly handling records of the multiple employees, the multiple employees are modeled to obtain the employee model.
3. The method according to claim 2, characterized in that, The work information includes workstation location, shift schedule and clock-in information, and job position information.
4. The method according to claim 3, characterized in that, The step of using an employee model to match employees based on the anomaly location and the problem description to obtain employees for anomaly handling includes: Using the employee model, based on the abnormal location, and the workstation location and shift clock information of the multiple employees, on-duty employees are matched to obtain a first set of employees; Using the employee model, anomaly handling capabilities are matched based on the problem description information, the job information, skill information, and anomaly history handling records of the multiple employees to obtain a second set of employees; The employee to be handled for the anomaly is determined based on the first set of employees and the second set of employees.
5. The method according to claim 4, characterized in that, The process involves using the employee model to match anomaly handling capabilities based on the problem description information, the job information, skill information, and anomaly history handling records of the multiple employees, resulting in a second employee set, including: Using the employee model, job matching is performed based on the problem description information and the job information of the multiple employees to obtain a third employee set; Using the employee model, skill matching is performed based on the problem description information and the skill information of the multiple employees to obtain a fourth employee set; Using the employee model, the historical processing information is matched with the abnormal historical processing records of the multiple employees to obtain the fifth employee set; The second employee set is determined based on the third employee set, the fourth employee set, and the fifth employee set.
6. The method according to any one of claims 1-5, characterized in that, Sending the exception information to the exception handling employee so that the exception handling employee can perform exception handling based on the exception information includes: The exception information is sent to the mobile terminal bound to the exception handling employee so that the exception handling employee can learn about the exception details and handle the exception through the exception information.
7. An apparatus for processing abnormal information, characterized in that, include: The information extraction module is used to extract the abnormal location and problem description information from the abnormal information in response to receiving abnormal information from the target production area; The matching module is used to match employees based on the abnormal location and the problem description information using an employee model to obtain employees for abnormal handling. The employee model is obtained by modeling multiple employees based on their work information and skill information in the target production area. A communication module is used to send the exception information to the exception handling employee so that the exception handling employee can perform exception handling based on the exception information.
8. The apparatus according to claim 7, characterized in that, Also includes: The employee modeling module is used to model the multiple employees based on their work information, skill information, and anomaly history processing records, thereby obtaining the employee model.
9. An electronic device, characterized in that, include: At least one processor; And, a memory communicatively connected to the at least one processor; The memory stores a computer program that, when executed by the at least one processor, implements the method of any one of claims 1 to 6.
10. A computer-readable storage medium storing a plurality of program codes, characterized in that, The program code is adapted to be loaded and run by a processor to perform the method of any one of claims 1 to 6.