Process allocation method and device and cluster

Abstract

A process allocation method, device and cluster can be applied to the technical field of production. The method comprises the following steps: acquiring a first process allocation target of a first production line input by a first user, first constraint information of the first production line, and skill information of personnel capable of being allocated to the first production line; wherein the first production line comprises a plurality of processes, and the first constraint information is used for constraining distribution of the plurality of processes; based on the first process distribution target, the first constraint information and the skill information of the personnel capable of being distributed to the first production line, obtaining a distribution result of the plurality of processes; and providing the allocation results of the plurality of processes to the first user. And the working procedures of the production line can be efficiently and reasonably distributed.

Description

Technical Field

[0001] The present application relates to the field of production technology, and in particular to a process allocation method, device and cluster. Background Art

[0002] The production lines of automobile manufacturing, electronic product manufacturing, hardware manufacturing, clothing manufacturing, etc. are mostly multi-process, streamlined, and continuous production lines. Since the current production lines have undergone subdivision of operations, the operation time of each process on the production line cannot be exactly the same, and the rhythm of each station and personnel cannot be the same, resulting in personnel or equipment waiting, which affects production efficiency.

[0003] In order to avoid or reduce the phenomenon of personnel or equipment waiting, it is necessary to reasonably allocate the processes in the production line, such as allocating personnel to the processes and the positions of the processes. At present, the process allocation in the production line is mostly completed based on manual experience. After the production management system releases the reviewed product process route, the production order of the processes is manually adjusted to keep the processes using the same equipment as continuous as possible.

[0004] Since there are many factors that affect production efficiency, the manual allocation process based on intuition cannot take multiple factors into account at the same time. Not only is the allocation efficiency low, but the difference between the allocation result and the ideal result may also be large. Summary of the invention

[0005] The embodiments of the present application provide a process allocation method, device and cluster, which can efficiently and reasonably allocate the processes of a production line.

[0006] In a first aspect, a process allocation method is provided, the method comprising: obtaining a first process allocation target of a first production line input by a first user, first constraint information of the first production line, and skill information of personnel who can be allocated to the first production line; wherein the first production line comprises a plurality of processes, and the first constraint information is used to constrain the allocation of the plurality of processes; based on the first process allocation target, the first constraint information, and the skill information of personnel who can be allocated to the first production line, obtaining allocation results of the plurality of processes; and providing the allocation results of the plurality of processes to the first user.

[0007] This method can allocate the processes of the production line based on the process allocation goals and constraint information configured by the user, as well as the skill information of the personnel who can be assigned to the production line. When the allocation goals and constraints are met, appropriate personnel can be allocated to the processes on the production line, thereby achieving efficient and reasonable allocation of processes.

[0008] In a possible implementation, based on the first process allocation target, the first constraint information, and the skill information of the personnel who can be allocated to the first production line, the allocation results of multiple processes are obtained, including: obtaining the personnel allocation target and the position allocation target from the first process allocation target; and obtaining the personnel allocation constraint and the position allocation constraint from the first constraint information; based on the personnel allocation target, the personnel allocation constraint and the skill information of the personnel who can be allocated to the first production line, personnel are allocated to multiple processes to obtain a first allocation result; based on the first allocation result, the position allocation target and the position allocation constraint, positions are allocated to multiple processes to obtain a second allocation result; wherein the allocation results of multiple processes include the first allocation result and the second allocation result.

[0009] This implementation method divides the process target of the production line configured by the user into a personnel allocation target and a station allocation target, and divides the constraint information of the production line configured by the user into a personnel allocation constraint and a station allocation constraint. Then, personnel are first allocated to the processes in the production line using the personnel allocation target, the personnel allocation constraint and the personnel's skill information; before that, stations are allocated to the processes in the production line based on the personnel allocation results, the station allocation target and the station allocation constraint. In this way, the complex multi-problem optimization problem of process allocation in the production line can be divided into two stages for processing, and suitable personnel and stations can be efficiently allocated to the processes. In addition, allocating personnel first and then allocating stations can ensure that the obtained process allocation result is the optimal solution that satisfies all targets (personnel allocation targets and station allocation targets) and constraints (personnel allocation constraints and station allocation constraints) at the same time. In addition, in the allocation order, personnel are allocated first, so that the balance rate of the production line can be prioritized, thereby ensuring the production efficiency of the production line.

[0010] In one possible implementation, the skill information of a personnel includes the working time of the personnel on at least one process among multiple processes, and the method further includes: obtaining historical work data of personnel who can be assigned to the first production line, wherein the historical work data of each personnel includes multiple work data of the personnel, and each of the multiple work data includes process characteristics and working time; based on the multiple work data of the personnel and the characteristics of at least one process, obtaining the working time of the personnel on at least one process.

[0011] In this implementation, the historical work data of personnel is used to evaluate the personnel's work time and other skill information in each process of the production line, so that the efficiency of personnel in each process of the production line can be accurately predicted or evaluated. In this way, the most suitable personnel can be selected for each process in the production line, which improves the enthusiasm of the personnel and the production efficiency of the production line.

[0012] In one possible implementation, based on multiple work data of personnel and characteristics of at least one process, the working time of personnel on at least one process is obtained, including: using multiple work data of personnel as a training set to train a personnel skill evaluation model; inputting the characteristics of at least one process into the personnel skill evaluation model, so that the personnel skill evaluation model outputs the working time of personnel on at least one process.

[0013] In this implementation, machine learning technology can be used to learn the working hours of personnel on processes with different process characteristics to obtain a personnel skill evaluation model. Then, the process characteristics of the process to be assigned can be input into the personnel skill evaluation model to obtain the working hours of personnel on the process to be assigned.

[0014] In a possible implementation, the method also includes: obtaining a second process allocation target for the second production line and second constraint information of the second production line input by a second user, the second constraint information being used to constrain the allocation of processes in the second production line; allocating stations to the processes in the second production line based on the second process allocation target and the second constraint information to obtain a third allocation result; and providing the third allocation result to the second user.

[0015] This method can also be used to allocate processes in unmanned production lines and has high flexibility.

[0016] In a possible implementation, the first process allocation target includes multiple targets, wherein each of the multiple targets corresponds to a preset weight.

[0017] In one possible implementation, the first process allocation target includes: the balance rate of the production line, the bottleneck cycle time, the walking distance when personnel have multiple stations, and at least one of the use costs of scarce equipment; and / or, the first constraint information includes: the skill threshold of the personnel who allocate the process, the number of processes and the number of stations assigned to a single person, the type and size of the equipment placed at the station, the cycle difference limit between personnel, the walking distance limit between multiple stations assigned, the range of personnel assigned to special processes, the association and mutual exclusion restrictions when the process allocation is combined, the upper limit of the number of equipment at a single station, the upper limit of the number of stations assigned to a single person, the upper limit of the number of times the same process is split, the upper limit of the number of laps that all processes run on the production line rails, the upper and lower limits of the total operation time of the process assigned to a single person, the maximum cycle, and at least one of the minimum cycle; and / or, the first production line is any one of an automobile production line, a hardware production line, an electronic product production line, and a clothing production line.

[0018] Through this method, users can flexibly configure various process objectives and constraint information so that process allocation can be carried out according to user needs.

[0019] Moreover, this method can be suitable for process allocation in different industries, different products, and different production lines. It has high versatility and does not need to rely on manual experience.

[0020] In a second aspect, a process allocation device is provided, which includes: an acquisition module for acquiring a first process allocation target of a first production line input by a first user, first constraint information of the first production line, and skill information of personnel who can be allocated to the first production line; wherein the first production line includes multiple processes, and the first constraint information is used to constrain the allocation of multiple processes; an obtaining module for obtaining allocation results of multiple processes based on the first process allocation target, the first constraint information, and the skill information of personnel who can be allocated to the first production line; and a providing module for providing the allocation results of multiple processes to the first user.

[0021] In one possible implementation, the obtaining module is used to: obtain a personnel allocation target and a position allocation target from a first process allocation target; and obtain a personnel allocation constraint and a position allocation constraint from a first constraint information; based on the personnel allocation target, the personnel allocation constraint and the skill information of the personnel who can be assigned to the first production line, allocate personnel to multiple processes to obtain a first allocation result; based on the first allocation result, the position allocation target and the position allocation constraint, allocate positions to multiple processes to obtain a second allocation result; wherein the allocation results of multiple processes include the first allocation result and the second allocation result.

[0022] In one possible implementation, the skill information of a personnel includes the working time of the personnel in at least one process among multiple processes; the acquisition module is also used to obtain historical work data of personnel who can be assigned to the first production line, wherein the historical work data of each personnel includes multiple work data of the personnel, and each of the multiple work data includes process characteristics and working time; the acquisition module is also used to obtain the working time of the personnel in at least one process based on the multiple work data of the personnel and the characteristics of at least one process.

[0023] In one possible implementation, the module is used to: train a personnel skill evaluation model using multiple work data of personnel as a training set; input the characteristics of at least one process into the personnel skill evaluation model, so that the personnel skill evaluation model outputs the working time of the personnel in at least one process.

[0024] In one possible implementation, the acquisition module is also used to obtain the second process allocation target of the second production line and the second constraint information of the second production line input by the second user, and the second constraint information is used to constrain the allocation of processes in the second production line; the acquisition module is also used to allocate stations to the processes in the second production line based on the second process allocation target and the second constraint information to obtain a third allocation result; the providing module is also used to provide the third allocation result to the second user.

[0025] In a third aspect, a computing device cluster is provided, comprising at least one computing device, each computing device comprising a processor and a memory; the processor of at least one computing device is used to execute instructions stored in the memory of at least one computing device, so that the computing device cluster executes the method provided in the first aspect.

[0026] In a fourth aspect, a computer-readable storage medium is provided, comprising computer program instructions. When the computer program instructions are executed by a computing device cluster, the computing device cluster executes the method provided in the first aspect.

[0027] In a fifth aspect, a computer program product comprising instructions is provided. When the instructions are executed by a computer device cluster, the computer device cluster executes the method provided in the first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 A schematic diagram of the structure of a process allocation system provided in an embodiment of the present application;

[0029] Figure 2 A flowchart of a process allocation method provided in an embodiment of the present application;

[0030] Figure 3 A schematic diagram of personnel skill information evaluation provided in an embodiment of the present application;

[0031] Figure 4 A schematic diagram of a production line provided in an embodiment of the present application;

[0032] Figure 5 A schematic diagram of the structure of a production system provided in an embodiment of the present application;

[0033] Figure 6 A flowchart of a process allocation method provided in an embodiment of the present application;

[0034] Figure 7 A schematic diagram of the structure of a process allocation device provided in an embodiment of the present application;

[0035] Figure 8 A schematic diagram of the structure of a computing device provided in an embodiment of the present application;

[0036] Fig. 9 A schematic diagram of the structure of a computing device cluster provided in an embodiment of the present application;

[0037] Fig.10 A schematic diagram of the structure of a computing device cluster provided in an embodiment of the present application. DETAILED DESCRIPTION

[0038] The scheme provided by the embodiment of the present application will be described below in conjunction with the accompanying drawings. In the embodiment of the present application, "multiple" means two or more, and "multiple" means two or more. "First", "second", etc. are only used to distinguish similar objects and are not necessarily used to describe a specific order or number of objects.

[0039] To facilitate understanding of the solutions provided by the embodiments of the present application, the technical terms that may be involved in the embodiments of the present application are first introduced.

[0040] Production line: Also known as production line, it refers to the route that a product takes during the production process, that is, the route that starts from the raw materials entering the production site and goes through multiple production stages such as processing, transportation, assembly, and inspection. A production line consists of multiple processes. Each of the multiple production stages is completed in one or more processes.

[0041] Process: An independent unit of work, usually completed by a machine or person at one station.

[0042] Characteristics of a process: refers to information that reflects the characteristics of a process, such as the standard working hours of the process, the production stage to which the process belongs, the type of equipment required for the process, the difficulty coefficient of the process, and the raw material information of the process.

[0043] Difficulty coefficient: also known as the leniency coefficient, expressed by the preset difficulty level.

[0044] Station: The location of the machine or person performing the process.

[0045] Takt time: The time it takes for a machine (unmanned production line) or person at a station to complete all the processes assigned to that station or person.

[0046] Bottleneck: The station or person with the longest cycle time in the production line.

[0047] Fixed-station process: If the equipment used in the process is immovable (it cannot be temporarily moved, i.e. added or deleted during production), the process completed using this equipment is called a fixed-station process.

[0048] Secondary entry: When the production line is a circular production line, the entire product needs to be run on the production line for multiple rounds to complete all processes. If the same product needs to enter the same station twice or more in different rounds to complete different processes, this phenomenon is called secondary entry. Since two or more different processes need to be completed at the same station, congestion is very likely to occur. In the production process, this type of allocation plan is generally avoided as much as possible;

[0049] Process sequence: also known as process flow sequence, refers to the sequence in which the processes in a production line must be followed.

[0050] Node process: Since process production must meet a strong sequence, if process A must be completed before process B, then process B is the node process of process A; in addition, the order of process A and process B is irrelevant, as long as process A and process B are completed before process C, then process C is the node process of process A and process B.

[0051] Idle time: When the rhythms of different stations or personnel in a production line are inconsistent, other stations or personnel except the bottleneck will have to wait. During the waiting time, they cannot perform effective work tasks, which is idle time.

[0052] Standard working hours: the time required for people with normal technical level to complete a process calculated by an authoritative organization.

[0053] Actual working hours: the actual time it takes for a person to complete a process.

[0054] Personnel skill matrix: Based on personnel and process dimensions, it shows the work efficiency values ​​(standard working hours / actual working hours) of different personnel completing different processes. Due to differences in personnel skills, different people will do different types of processes, and different people will complete the same process at different efficiencies.

[0055] Balance rate: refers to the difference between all positions or personnel rhythms. The smaller the difference, the greater the balance rate.

[0056] Production line balance: refers to the operation of improving the balance rate of the production line. Specifically, it means that after load analysis of all processes in the production line, the order of processes, the personnel of the processes, and the work combination of the processes are adjusted to adjust the load distribution between processes, so that each station (or personnel) can achieve a beat balance, reduce the idle time of different stations (or personnel), eliminate waiting waste, enhance the work enthusiasm of personnel, and improve production efficiency. By improving the balance rate of the production line, the labor time consumption of a single product can be reduced, the cost can be reduced, and in addition, the work-in-progress and site occupancy in the production process can be reduced.

[0057] When allocating processes to a production line, in addition to considering the balance of the production line, many factors need to be considered, such as the product manufacturing process (the sequence of processes, the time interval between production processes, the requirements for station spacing), the differences in equipment required for different processes (such as whether they are movable and the size of the floor space), the impact between different equipment (such as whether they are mutually exclusive), the requirements for equipment placement at different stations, the cost of using scarce equipment, the distance people walk when changing products, the number of times equipment is moved, and other multiple goals. The problem scenarios are complex and changeable.

[0058] After investigating and analyzing multiple production lines in different fields of manufacturing, it was found that the process allocation in the production line has the following requirements.

[0059] a. Complex allocation constraints: Factors that need to be considered for static process allocation include process flow sequence, single process duration, personnel skills, equipment type and size, number of equipment, number and size of stations, and other requirements, as follows.

[0060] a1. The working order of the processes must satisfy the process flow order, and each process must be completed before its corresponding node process.

[0061] a2. Different processes require different skills to complete. Simple processes require more people with the required skills, while complex processes require fewer people with the required skills. In addition, different people have different work efficiency and yield rates for the same process. When dividing the work, the process cannot be assigned to people who do not have the corresponding work skills.

[0062] a3. Different processes require different equipment to complete. When the process is assigned to a station, the equipment required for the process must also be assigned to the station.

[0063] a4. The number and type of equipment assigned to a single station are limited: Due to the limited size of a single station, the number of equipment that can be placed at a single station has an upper limit and is affected by the type, size, and characteristics of the placed equipment. Some equipment cannot be moved and can only be placed at fixed stations, resulting in processes that require the equipment being assigned to these stations only; some equipment can only be placed at independent stations due to size and other reasons, so processes that require the equipment and processes of other equipment cannot be assigned to the same station at the same time; some equipment has a mutually exclusive relationship with other equipment for safety reasons, so processes of the equipment and processes of mutually exclusive equipment of the equipment cannot be assigned to the same station at the same time. Among them, the process of the equipment refers to the process completed using the equipment.

[0064] a5. The number and distance of multiple stations assigned to the same person are limited: Due to the influence of the type and number of equipment placed at a single station and the order of process flow, the same person may be assigned to multiple stations because he or she is performing multiple processes, but the number of stations assigned to multiple stations cannot exceed the upper limit; in addition, the assigned multiple stations should be adjacent to each other, so as to reduce the waste of work time caused by personnel movement time.

[0065] a6. The pace of all personnel must be within a certain upper and lower limit of the average pace to avoid long waiting times and improve production efficiency.

[0066] a7. Only one person can be assigned to one station, and the cycle time at one station must not be lower than the lower limit to avoid wasting production time due to personnel movement time.

[0067] a8, the total number of allocated stations cannot exceed the number of stations available on the production line.

[0068] a9. Some special processes will be completed by designated external stations and personnel.

[0069] a10, the production line is similar to a circular production line. Due to the influence of the process flow sequence and the fixed position of the equipment, if the product has not completed all the processes after one circle on the production line, it can be turned again, but the total number of circles cannot exceed the upper limit.

[0070] b. The allocation targets are diverse, as follows.

[0071] b1, the rhythm of all personnel should be balanced as much as possible to improve production efficiency;

[0072] b2. Assign each person the process they are good at as much as possible to cultivate the skills of specialized personnel;

[0073] b3, the bottleneck cycle should be as small as possible to improve the production efficiency of the products on the production line;

[0074] b4. The number of revolutions required to complete a product should be as small as possible to reduce the time wasted on the guide rails;

[0075] b5, use as few scarce equipment as possible to complete a product;

[0076] b6. The new positions assigned to personnel and equipment should be as small as possible compared to their current positions, thus reducing the time required for product changeover;

[0077] In short, there are many constraints and objectives to consider for the process allocation of production lines. The process allocation of production lines is a multi-objective and multi-constraint combinatorial optimization problem with complex constraints.

[0078] In view of the above situation, an embodiment of the present application provides a process allocation method. The method can obtain the process allocation target of the production line input by the user, the constraint information of the production line, and the skill information of the personnel who can be assigned to the production line. Among them, the process allocation target can include multiple targets, and the constraint information can include multiple constraints. The method can allocate the processes in the production line based on the process allocation target, the constraint information, and the skill information of the personnel who can be assigned to the production line to obtain an allocation result. Then, the allocation result can be provided to the user so that the user can allocate the processes of the production line according to the allocation result. Among them, the processes in the production line refer to the processes included in the production line, that is, the processes that constitute the production line. This method can effectively solve the multi-objective and multi-constraint combinatorial optimization problem of production line process allocation, obtain the reasonable allocation results of the processes in the production line under the requirements of multiple objectives and the constraints of multiple constraints, and improve production efficiency.

[0079] Next, the process allocation method provided in the embodiment of the present application is introduced.

[0080] Figure 1 A process allocation system 100 is shown, and the process allocation system 100 can be used to implement the process allocation method provided in the embodiment of the present application. The process allocation system 100 can be deployed in the cloud or locally on the production line. When the process allocation system 100 is deployed in the cloud, the process allocation system 100 can communicate with relevant systems locally on the production line through the network.

[0081] like Figure 1 As shown, the process allocation system 100 includes an acquisition module 110, a parsing module 120, a personnel allocation module 130 and a station allocation module 140. The local related systems of the production line include a process management system, a production management system and a manufacturing execution system (MES).

[0082] The process management system is also called a process management system, which has process information of the production line. The process information of the production line is also called process flow information, including multiple processes, the order of the multiple processes in the production line, and the characteristics of each process. The characteristics of the process include standard working hours, the production stage to which the process belongs, the type of equipment required for the process, etc. The acquisition module 110 can acquire the process information of the production line from the process management system.

[0083] The production management system has information about assignable personnel. The assignable personnel of a production line refers to the personnel who can be assigned to the production line, that is, the personnel who can be selected from the assignable personnel to work on the production line. The information about assignable personnel may include the number of assignable personnel, the identity of each person (e.g., person number), etc.

[0084] The production management system includes a skill evaluation module. The skill evaluation module is used to evaluate the skills of personnel and obtain the skill information of personnel. Among them, the function of the skill evaluation module will be specifically introduced below and will not be repeated here.

[0085] The production management system includes an input module. The input module allows users (such as production line managers) to input process objectives and constraint information of the production line. The constraint information is used to constrain the process allocation in the production line.

[0086] The acquisition module 110 can acquire the information of assignable personnel, the skill information of assignable personnel, and the process objectives and constraint information of the production line from the production management system.

[0087] The manufacturing execution system has the current position information of the equipment and the current position information of the personnel. The acquisition module 110 can acquire the current position information of the equipment and the current position information of the personnel from the manufacturing execution system.

[0088] The acquisition module 110 can organize the acquired data and perform format conversion. The acquisition module 110 sends the format-converted data to the parsing module 120. The parsing module 120 extracts the process target and constraint information of the production line from the received data, and parses the process target and constraint information. The process target is parsed into the personnel allocation target and the station allocation target, and the constraint information is parsed into the personnel allocation constraint and the station allocation constraint.

[0089] The personnel allocation module 130 obtains the personnel allocation goals and personnel allocation constraints from the analysis module 120, and obtains the skill information of the assignable personnel from the analysis module 120 or the acquisition module 110, and based on the personnel allocation goals, personnel allocation constraints and the skill information of the assignable personnel, allocates personnel to the processes in the production line to obtain the personnel allocation results.

[0090] The station allocation module 140 obtains the personnel allocation results from the personnel allocation module 1140, and obtains the station allocation targets and station allocation constraints from the analysis module 120, and allocates stations to the processes in the production line based on the personnel allocation results, the station allocation targets and the station allocation constraints to obtain the station allocation results.

[0091] The station allocation result and the personnel allocation result constitute the process allocation result. The manufacturing execution system can obtain the process allocation result from the process allocation system 100, for example, from the station allocation module 140. After obtaining the process allocation result, the manufacturing execution system can update the current station information of the equipment and the current station information of the personnel based on the station allocation result in the process allocation result.

[0092] Next, combine Figure 2 The process allocation flow shown introduces the specific functions of the above modules.

[0093] People have different skills, so different people take different amounts of time to complete the same process or a group of processes, that is, different people have different beats. The difference in beats of different people directly affects whether the production line is balanced, and the maximum beat directly determines the production efficiency of the production line (that is, the unit hourly output of the production line). Therefore, when allocating the processes of the production line, it is crucial to assign appropriate personnel to the processes in the production line, which is crucial to improving the enthusiasm of the personnel (that is, reducing waiting time) and improving the production efficiency of the production line. Therefore, it is necessary to evaluate the working time of personnel in each or each group of processes in the production line.

[0094] The skill evaluation module can be used to evaluate the working time of a person on one or more processes. Specifically, the skill evaluation module obtains the historical working data of the person. The historical working data of the person includes multiple working data in the history of the person, and each working data includes the process characteristics of the process and the working time of the person on the process. The process can be a single process or a combination of multiple processes. Different working data may include different processes.

[0095] Among them, the skill assessment module can obtain the historical work records of personnel and extract the historical work data of personnel from the historical work records.

[0096] In some embodiments, different personnel have different learning rates, resulting in different effective times of historical work data of different personnel. The skill assessment module can obtain historical work records generated in the recent period of time (for example, the last three months, the last six months, etc.), or it can obtain historical work records of a certain number of recent times (for example, the last 1,000 work records, 10,000 work records, etc.). Among them, obtaining historical work records generated in the recent period of time and only calculating and evaluating skills based on work records within a limited time can eliminate or reduce the impact of learning rate on skill assessment. Obtaining a certain number of recent historical work records can eliminate or reduce the impact of missing historical work records on skill assessment.

[0097] In step 213, the skill of the person in a process may be evaluated based on the multiple historical work data of the person and the process characteristics of the process, that is, the working time of the person in the process may be predicted or evaluated, for example, the working time of the person in at least one process on a production line may be predicted or evaluated.

[0098] In some embodiments, Figure 2 As shown, before step 213, step 211 may be performed to clean the data to remove abnormal historical work data. Figure 3 During the work, equipment failures and improper operation by personnel may lead to abnormal work data, such as unreasonable work time (i.e., time anomaly), missing basic data (i.e., group anomaly), abnormal records (e.g., repair records), etc. In step 211, the abnormal work data in the acquired historical work data is cleaned up.

[0099] In some embodiments, Figure 2As shown, before step 213, step 212 can also be performed to split and combine processes. As described above, the process characteristics and working time in a historical work data can be a group of processes, and the group of processes includes multiple processes. The process characteristics of the multiple processes in the historical work data can be split to obtain the process characteristics of each process, and the working time of the multiple processes can be split to obtain the working time of each process. In addition, the process characteristics in different historical work data can be combined to obtain the process characteristics of a group of processes, and the working time in multiple historical work data can be combined to obtain the duration of a group of processes. By splitting and combining processes, the working time of personnel on more processes can be obtained.

[0100] In some embodiments, a plurality of work data of personnel can be used as a training set to train a personnel skill evaluation model. The personnel skill evaluation model can be trained based on artificial intelligence (AI) technology, for example, based on supervised machine learning. Figure 3 , we can extract process features from historical data, such as raw material information, standard working hours, difficulty coefficient, etc. We can also split and combine process features and working hours to obtain the working hours of personnel in processes corresponding to more different process features. We can also obtain the personnel's ID, etc. These data can be used as labeled training sets. Among them, the working hours corresponding to the process features can be used as the labels of the process features. In this way, the personnel skill assessment model can be supervised for training.

[0101] After the training of the personnel skill evaluation model is completed, the process characteristics of one or some processes of the production line and the personnel ID can be input into the personnel skill evaluation model, and the personnel skill evaluation model can output the working hours of the personnel in the process.

[0102] The personnel ID, the process characteristics of each process on the production line, and the process characteristics of each possible process combination can be input into the personnel skill evaluation model to obtain the working hours of the personnel in each process and each possible process combination. The working hours of the personnel in each process and each possible process combination belong to the skill information of the personnel corresponding to the production line. The working hours of the personnel in each process and each possible process combination can form a personnel skill matrix.

[0103] Thus, according to the above scheme, the skill information of each assignable personnel of the production line corresponding to the production line can be obtained.

[0104] When allocating processes to a production line, the acquisition module 110 may acquire the skill information of each assignable person to the production line corresponding to the production line.

[0105] Continue reading Figure 2 The user can input the process target of the production line through the input module so that the user can configure the process target. The acquisition module 110 can acquire the process target input by the user from the input module.

[0106] The process target is also called the objective function, which is the target that needs to be optimized in the process of process allocation of the production line. The process target may include one or more targets, for example, at least one of the following: the balance rate of the production line, the duration of the bottleneck cycle, the walking distance when the personnel are in multiple positions, and the cost of using scarce equipment. The one or more targets may be targets based on specific industries, products, and production lines.

[0107] In some embodiments, when the process goal input by the user includes multiple goals, the user can also set the weight of each goal, where the weight of the goal can also be called parameter information of the goal.

[0108] The user inputs the constraint information of the production line through the input module, so that the user configures the constraint information. The acquisition module 110 can acquire the constraint information input by the user from the input module.

[0109] Constraint information is used to constrain the allocation of processes in the production line, and is a constraint that needs to be followed during the process of allocating processes in the production line. Constraint information includes one or more constraints, for example, including: the skill threshold of the personnel who allocate processes, the number of processes and the number of stations assigned to a single person, the type and size of the equipment placed on the station, the rhythm difference limit between personnel, the walking distance limit between multiple stations assigned, the range of personnel assigned to special processes, the association and mutual exclusion restrictions when the process is allocated, the upper limit of the number of equipment at a single station, the upper limit of the number of stations assigned to a single person, the upper limit of the number of times the same process is split, the upper limit of the number of laps that all processes run on the production line rails, the upper and lower limits of the total operation time of the process assigned to a single person, and at least one of the maximum rhythm and minimum rhythm. Among them, the one or more constraints can be constraints based on specific industries, products, and production lines.

[0110] Users can set specific parameters in each constraint according to actual requirements.

[0111] In some embodiments, the acquisition module 110 may also acquire static data, including process information of the production line, information on personnel to be assigned, current position information of equipment, current position information of personnel, and the like.

[0112] Continue reading Figure 2 , the parsing module 120 can execute step 220 to parse the process objectives and constraint information of the production line. Next, the distribution is introduced.

[0113] Parsing process goals specifically refers to identifying personnel allocation goals and station allocation goals from process goals input by users. Personnel allocation goals refer to goals related to personnel allocation in process allocation, such as production balance rate, bottleneck cycle time, and the cost of using scarce equipment. Station allocation goals refer to goals related to station allocation in process allocation, such as walking distance when personnel have multiple stations.

[0114] In one example, a personnel allocation target library may be pre-set based on expert knowledge or experience. The personnel allocation target library includes multiple targets related to personnel allocation. In step 220, the intersection of the process target input by the user and the personnel allocation target library may be taken to identify the personnel allocation target from the process target input by the user. The targets other than the personnel allocation target in the process target input by the user are used as the station allocation targets.

[0115] In one example, a station allocation target library may be pre-set based on expert knowledge or experience. The station allocation target library includes multiple targets related to station allocation. In step 220, the intersection of the process target input by the user and the station allocation target library may be taken to identify the station allocation target from the process target input by the user. The targets other than the station allocation target in the process target input by the user are used as personnel allocation targets.

[0116] Parsing the constraint information may specifically refer to identifying personnel allocation constraints and station allocation constraints from the constraint information input by the user.

[0117] Personnel allocation constraints refer to constraints related to personnel allocation in process allocation, such as the skill threshold of personnel assigned to processes, the number of processes and stations assigned to a single person, the tact difference limit between personnel, the personnel range limit for special process allocation, the maximum tact, minimum tact, and the upper and lower limits of the total operation time of a process assigned to a single person, etc.

[0118] Station allocation constraints refer to the constraint information related to station allocation in process allocation, such as the association and mutual exclusion restrictions when combining process allocations, the upper limit of the number of equipment at a single station, the upper limit of the number of stations allocated to a single person, the upper limit of the number of times the same process is split, and the upper limit of the number of laps that all processes run on the production line rails.

[0119] In one example, a staff allocation constraint library may be pre-set based on expert knowledge or experience. The staff allocation constraint library includes a plurality of constraints related to staff allocation. In step 220, the intersection of the constraint information input by the user and the staff allocation constraint library may be taken, thereby identifying the staff allocation constraints from the constraint information input by the user. The constraints other than the staff allocation constraints in the constraint information input by the user are used as the station allocation constraints.

[0120] In one example, a station allocation constraint library may be pre-set based on expert knowledge or experience. The station allocation constraint library includes a plurality of constraints related to station allocation. In step 220, the intersection of the constraint information input by the user and the station allocation constraint library may be taken, thereby identifying the station allocation constraint from the constraint information input by the user. The constraints other than the station allocation constraint in the constraint information input by the user are used as the personnel allocation constraint.

[0121] The parsing module 120 sends the identified personnel allocation target and personnel allocation constraint to the personnel allocation module 130 , and sends the identified station allocation target and station allocation constraint to the station allocation module 140 .

[0122] Continue reading Figure 2 The personnel allocation module 130 may execute step 230 to allocate personnel to the processes in the production line. Specifically, based on the personnel allocation target, the personnel allocation constraint, and the skill information of the personnel that can be allocated to the production line, personnel are allocated to the processes in the production line.

[0123] The personnel allocation module 130 can extract the process information of the production line from the static data acquired by the acquisition module 110, such as the process characteristics of each process in the production line, the order between the processes, etc. The personnel allocation module 130 can input the process characteristics of the process into the personnel skill evaluation model to obtain the personnel's skill information on the process, such as the working hours, etc.

[0124] When allocating personnel to processes in a production line, the personnel allocation module 130 can keep the order of the processes in the production line different or change the order of the processes.

[0125] The personnel allocation module 130 can use an optimization algorithm (such as a heuristic algorithm) to ensure that the personnel allocation does not violate the personnel allocation constraints (the skill threshold of the personnel assigned to the process, the number of processes and stations assigned to a single person, the beat difference limit between personnel, the range of personnel assigned to special processes, the maximum beat, the minimum beat, the upper and lower limits of the total operation time of the process assigned to a single person, etc.), and allocate personnel to each process in the production line according to the personnel allocation goal and the skill information of the personnel who can be assigned to the production line, so that the personnel allocation result meets the personnel allocation goal, and the production line balance, the cost of using scarce equipment, the bottleneck beat and other goals are optimized. In one example, the personnel suitable for each process can be allocated to each process in turn according to the order of each process in the production line.

[0126] In some embodiments, the personnel allocation result outputted in step 230 may be verified to determine whether the personnel allocation result satisfies the personnel allocation target or the personnel allocation constraint. If the personnel allocation target or the personnel allocation constraint is not satisfied, the user may be prompted to modify the process target and / or constraint information inputted by the user. After the user modifies the process target and / or constraint information, step 220 and step 230 may be performed again. If the personnel allocation result outputted in step 230 satisfies the personnel allocation target and the personnel allocation constraint, the allocation result is sent to the station allocation module 140.

[0127] The staff allocation module 130 sends the staff allocation result of the production line to the station allocation module 140. In step 240, the station allocation module 140 allocates stations to the processes in the production line based on the staff allocation result of the production line and the station allocation target and station allocation constraint of the production line.

[0128] Among them, the station allocation mode of the production line and the optimization parameters of the station allocation can be obtained based on the station allocation target and the station allocation constraint of the production line. Then, according to the station allocation mode and the optimization parameters of the station allocation, for example, an optimization algorithm (such as a heuristic algorithm) is used to allocate stations to the process and the personnel assigned to the process, so that the station allocation target is optimized.

[0129] More specifically, the station allocation mode is divided into a mode that prioritizes reducing personnel changes and a mode that prioritizes maintaining production order. Based on the station allocation target and station allocation constraints of the production line, the station allocation mode of the production line can be determined as a personnel change priority mode or a production order priority mode. In the personnel change priority mode or the production order priority mode, and while ensuring that the station allocation does not violate the station allocation constraints, according to the station allocation target, an optimization algorithm (such as a heuristic algorithm) is used to allocate at least one candidate station to the personnel assigned to the process. Then, a local search algorithm is used to allocate a station to each person. Among them, when a person is assigned multiple stations, the multiple stations should be as close as possible, and the multiple stations should be adjacent to each other in sequence, while ensuring that the number of equipment that meets the fixed station meets the demand, the number of turns during product production, and the number of secondary entry meet the restrictions, so as to reduce the time spent by personnel moving between different stations.

[0130] The personnel allocation result obtained in step 230 and the station allocation result obtained in step 240 may be referred to as the allocation result of the process in the production line. The station allocation module 140 may output the allocation result of the process in the production line in step 250 to provide the allocation result of the process in the production line to the user.

[0131] In some embodiments, the station allocation result outputted in step 240 may be verified to determine whether the station allocation result satisfies the station allocation target or the station allocation constraint. If the station allocation target or the station allocation constraint is not satisfied, the user may be prompted to modify the process target and / or constraint information inputted by the user. After the user modifies the process target and / or constraint information, steps 220, 230, and 240 may be performed again. If the station allocation result outputted in step 240 satisfies the station allocation target and the station allocation constraint, the station allocation result is included in the allocation result of the process in the production line, and the allocation result of the process in the production line is outputted in step 250.

[0132] In some embodiments, the allocation results of the processes in the production line can be output to the manufacturing execution system so that the manufacturing execution system records or updates the allocation results of the processes in the production line, such as the current station information of the equipment, the current station information of the personnel, etc.

[0133] In some embodiments, the allocation results of the processes in the production line may be output to the production management system so that the user can view and adjust the allocation results.

[0134] In addition, the process allocation method provided in the embodiment of the present application can also be used for process allocation in unmanned production lines.

[0135] In some embodiments, when the process is assigned to the unmanned production line, there is no need to perform step 220 and step 230. After obtaining the process goal and constraint information input by the user, in step 240, the station is assigned to the unmanned production line based on the process goal and constraint information to obtain the station assignment result. In step 250, the station assignment result is output.

[0136] In some embodiments, when allocating processes to an unmanned production line, the skill information of the personnel that can be allocated to the production line can be set to be the same. Then, by sequentially executing steps 220, 230, and 250, only the station allocation to the process can be achieved, and the station allocation result of the process can be output.

[0137] Therefore, the process allocation method provided in the embodiment of the present application has relatively high flexibility, and is suitable not only for process allocation of manned production lines, but also for process allocation of unmanned production lines.

[0138] Next, in one embodiment, taking the process allocation of a clothing production line as an example, the process allocation method provided in the embodiment of the present application is introduced.

[0139] The clothing production line adopts the production method of assembly line. The production process of different types of clothing, such as tops, bottoms, and skirts, is broken down into individual assembly-line processes. Usually, the production process of a piece of clothing includes dozens to hundreds of individual processes. For example Figure 4 The production line shown includes multiple processes such as process 410, process 420, process 430, process 440, process 450, and process 460. Different processes are assigned to different personnel and stations. It is necessary to ensure that the rhythm of the combined processes performed by different personnel is as close as possible, and the order of running on the assembly line during the entire process of product production is as consistent as possible with the process production order, so as to reduce the number of running circles on the circular production line rail and improve production efficiency. In addition, when a single person is assigned more than one station, they should be ensured to be in adjacent stations as much as possible; when reassigning stations to personnel and equipment for the current style of clothing, the changes should be as small as possible compared with the current positions of personnel and equipment to reduce the time for transfer and connection.

[0140] The process allocation method provided in the embodiment of the present application can be used to allocate the processes in the clothing production line. Figure 5 As shown, the clothing production system includes a process management system, a production management system, a production planning system and a manufacturing execution system. Among them, the production management system may include a skill evaluation module, and the production planning system may include a process allocation system 100. That is, the skill evaluation module is set in the production management system, and the process allocation system 100 is set in the production planning system.

[0141] The skill evaluation module is used to evaluate the skill information of personnel who can be assigned to the clothing production line, such as the working hours of personnel in at least one process in the clothing production line. Among them, the skill evaluation module can obtain the historical work data of personnel and perform data cleaning on the historical work data. Data cleaning includes: cleaning the abnormal working time, the abnormal grouping of combined work records, and the repair record data to obtain the normal work data of the personnel. After that, through the feature extraction, training, and reasoning process, the personnel skill matrix is ​​obtained, that is, the actual estimated time for each person to do each single process.

[0142] Specifically, the historical work records of personnel in the manufacturing execution system can be imported into the database. The skill assessment module can obtain the historical work records from the database. The historical work records of personnel include the historical time spent by personnel in different single processes or combined processes over a period of time. The combined process refers to a combination of multiple processes.

[0143] Clean the abnormal data in the historical work records due to equipment failure, unreasonable operation time caused by improper operation of personnel, missing basic data, loss of some work records, etc., and obtain the cleaned work records;

[0144] Feature extraction: Extract features from the historical work records of personnel, including personnel ID, raw material information (such as fabric grade), work time, difficulty coefficient and other process features for a single process or combined process, and convert the historical work records into structured data;

[0145] AI training and reasoning: Machine learning training is performed based on the extracted features to obtain a personnel skill evaluation model. When the process characteristics of the corresponding personnel and process are input, the AI ​​model can be used for reasoning to obtain the time required for the person to do the corresponding process, that is, the time the person works on the process.

[0146] For details, please refer to the above Figure 3 The introduction and implementation of , will not be repeated here.

[0147] The process allocation system 100 can obtain the process information of product production: that is, all the processes required to complete a product, including the standard time of each single process, the material grade, difficulty coefficient, equipment type and other information of each process, as well as the sequence constraints of different processes when they are completed;

[0148] Obtain the basic data and current dynamic information of the production line: information such as personnel involved in process allocation (i.e., personnel that can be allocated to the production line), stations, equipment types, and the personnel currently logged in at each station and the types of equipment placed;

[0149] Obtaining personnel skill information: From the personnel skill evaluation model, we can obtain the personnel skill matrix, thereby obtaining the time required for different personnel to complete each single process in the clothing production line;

[0150] Obtain the process allocation constraint information, process goals and corresponding weights configured by the user, including: the upper limit of the number of equipment at a single station, the upper limit of the number of stations assigned to a single person, the upper limit of the number of times the same process is split, the upper limit of the number of circles that all processes run on the assembly line rails, the upper and lower limits of the total operation time of the process assigned to a single person, and other constraints, as well as the weights of each constraint; goals such as beat balance, scarce equipment cost, number of personnel and equipment movements, bottleneck beat, and the weights of each goal;

[0151] Decompose constraint information and process goals: Split constraint information and process goals into constraints and goals related to personnel allocation and station allocation respectively;

[0152] Personnel allocation: Based on the personnel's skill information, candidate personnel are generated for each process; the most suitable personnel are selected for each process in turn using a heuristic algorithm to ensure that the number of stations per person, the number of process splits, the maximum and minimum cycle times, and other constraints are not violated after the process is assigned to personnel. At the same time, the cycle balance, scarce equipment cost, bottleneck cycle, and other targets after the current personnel are selected are ensured to be optimal;

[0153] Allocate stations: Determine the current station allocation mode based on station-related goals, that is, whether to prioritize reducing personnel changes or maintaining production order, and allocate stations under a given station mode. In a given station allocation mode, select candidate stations for each person, and use a local search algorithm to allocate stations for each person, ensuring that the number of equipment that meets fixed stations meets the demand, the number of turns during product production, and the number of secondary entry stations meet the restrictions, and when there are multiple stations, try to stay in adjacent stations;

[0154] Output allocation plan: Output the personnel allocation results and station allocation results of the process to the production management system and display them to the user for selection and adjustment.

[0155] For details, please refer to the above Figure 2 The introduction and implementation of , will not be repeated here.

[0156] In summary, in the process allocation method provided in the embodiment of the present application, the process target of the production line configured by the user is divided into a personnel allocation target and a station allocation target, and the constraint information of the production line configured by the user is divided into a personnel allocation constraint and a station allocation constraint. Then, the personnel allocation target, the personnel allocation constraint and the skill information of the personnel are first used to allocate personnel to the process in the production line; before that, the stations are allocated to the process in the production line based on the personnel allocation result, the station allocation target and the station allocation constraint. In this way, the complex multi-problem optimization problem of process allocation in the production line can be divided into two stages for processing, and suitable personnel and stations can be efficiently allocated to the process. In addition, the personnel are allocated first, and then the stations are allocated, which can ensure that the obtained process allocation result is the optimal solution that satisfies all objectives (personnel allocation target and station allocation target) and constraints (personnel allocation constraints and station allocation constraints) at the same time. And, in the allocation order, the personnel are allocated first, so that the balance rate of the production line can be prioritized, thereby ensuring the production efficiency of the production line.

[0157] Moreover, the process allocation method provided in the embodiment of the present application is a process allocation method that can be suitable for different industries, different products, and different production lines, with high versatility and no need to rely on manual experience. Specifically, process allocation can be performed based on various process goals and constraint information configured by the user. For example, it is possible to support parameter settings for constraints such as the upper and lower limits of the actual beat of personnel, the number of equipment placed at different stations, the use of the same equipment type but different equipment objects in different processes, the upper limit of the number of stations allocated to each personnel, and the upper limit of the number of splits of a single process, and parameter configuration is performed for objective functions such as the balance rate of the production line, personnel movement, and scarce equipment, and output multi-objective optimization allocation results that meet strict constraints. The constraints and targets included are rich in variety, and some constraint information or targets can be removed by parameter selection.

[0158] After experiments, the process allocation method provided in the embodiment of the present application can be successfully applied to the production line process allocation system of different industries such as automobiles, hardware, electronic products, and clothing. In other words, the process allocation method provided in the embodiment of the present application can allocate processes in automobile production lines, hardware production lines, electronic product production lines, and clothing production lines.

[0159] In particular, the embodiment of the present application utilizes the historical work data of personnel to evaluate the personnel's work time and other skill information in each process of the production line, so as to accurately predict or evaluate the efficiency of personnel in each process of the production line. In this way, the most suitable personnel can be selected for each process of the production line, which improves the enthusiasm of the personnel and the production efficiency of the production line.

[0160] In addition, the process allocation method provided in the embodiment of the present application has a relatively high flexibility and is suitable not only for process allocation of manned production lines, but also for process allocation of unmanned production lines.

[0161] Based on the above description, the present application embodiment provides a process allocation method. Figure 6 , the method comprises the following steps.

[0162] Step 601, obtaining the first process allocation target of the first production line input by the first user, the first constraint information of the first production line, and the skill information of the personnel who can be allocated to the first production line; wherein the first production line includes multiple processes, and the first constraint information is used to constrain the allocation of the multiple processes. For details, please refer to the above Figure 1 The functions of the input module and the acquisition module 110 are introduced and implemented.

[0163] Step 602: Based on the first process allocation target, the first constraint information, and the skill information of the personnel that can be allocated to the first production line, the allocation results of the multiple processes are obtained. Figure 1 The functions of the analysis module 120, the personnel allocation module 130 and the station allocation module 140 are introduced and implemented, or the above Figure 2 The introduction and implementation of step 220, step 230 and step 240.

[0164] Step 603: Provide the first user with the allocation results of the multiple processes. Figure 2 The introduction of step 250 is implemented.

[0165] In some embodiments, the allocation results of the multiple processes are obtained based on the first process allocation target, the first constraint information, and the skill information of the personnel who can be allocated to the first production line, including: obtaining a personnel allocation target and a station allocation target from the first process allocation target; and obtaining a personnel allocation constraint and a station allocation constraint from the first constraint information; based on the personnel allocation target, the personnel allocation constraint and the skill information of the personnel who can be allocated to the first production line, personnel are allocated to the multiple processes to obtain a first allocation result; based on the first allocation result, the station allocation target and the station allocation constraint, stations are allocated to the multiple processes to obtain a second allocation result; wherein the allocation results of the multiple processes include the first allocation result and the second allocation result. For details, please refer to the above description of Figure 1 The functions of the analysis module 120, the personnel allocation module 130 and the station allocation module 140 are introduced and implemented, or the above Figure 2 The introduction and implementation of step 220, step 230 and step 240.

[0166] In some embodiments, the skill information of the personnel includes the working time of the personnel in at least one of the multiple processes, and the method further includes: obtaining the historical working data of the personnel who can be assigned to the first production line, wherein the historical working data of each personnel includes multiple working data of the personnel, and each of the multiple working data includes process characteristics and working time; based on the multiple working data of the personnel and the characteristics of the at least one process, obtaining the working time of the personnel in the at least one process. For details, please refer to the skill evaluation module and Figure 2 The introduction and implementation of steps 211 to 213.

[0167] In an example of this embodiment, the obtaining of the working time of the personnel on the at least one process based on the multiple working data of the personnel and the characteristics of the at least one process includes: training a personnel skill evaluation model using the multiple working data of the personnel as a training set; inputting the characteristics of the at least one process into the personnel skill evaluation model, so that the personnel skill evaluation model outputs the working time of the personnel on the at least one process. For details, please refer to the above Figure 3 The illustrated embodiment is described in detail.

[0168] In some embodiments, the method also includes: obtaining a second process allocation target for the second production line input by a second user and second constraint information of the second production line, wherein the second constraint information is used to constrain the allocation of processes in the second production line; based on the second process allocation target and the second constraint information, allocating stations to the processes in the second production line to obtain a third allocation result; and providing the third allocation result to the second user.

[0169] This method can allocate the processes of the production line based on the process allocation goals and constraint information configured by the user, as well as the skill information of the personnel who can be assigned to the production line. When the allocation goals and constraints are met, appropriate personnel can be allocated to the processes on the production line, thereby achieving efficient and reasonable allocation of processes.

[0170] The present application embodiment also provides a process allocation device 700. Figure 7 As shown, the apparatus 700 includes:

[0171] The acquisition module 710 is used to acquire a first process allocation target of a first production line input by a first user, first constraint information of the first production line, and skill information of personnel that can be allocated to the first production line; wherein the first production line includes a plurality of processes, and the first constraint information is used to constrain the allocation of the plurality of processes;

[0172] An obtaining module 720, configured to obtain the allocation results of the plurality of processes based on the first process allocation target, the first constraint information, and the skill information of the personnel that can be allocated to the first production line;

[0173] The providing module 730 is used to provide the first user with the allocation results of the multiple processes.

[0174] In some embodiments, the obtaining module 720 is used to: obtain personnel allocation targets and station allocation targets from the first process allocation targets; and obtain personnel allocation constraints and station allocation constraints from the first constraint information; based on the personnel allocation targets, the personnel allocation constraints and the skill information of the personnel that can be assigned to the first production line, allocate personnel to the multiple processes to obtain a first allocation result; based on the first allocation result, the station allocation targets and the station allocation constraints, allocate stations to the multiple processes to obtain a second allocation result; wherein the allocation results of multiple processes include the first allocation result and the second allocation result.

[0175] In some embodiments, the skill information of the personnel includes the working time of the personnel in at least one of the multiple processes; the acquisition module 710 is also used to obtain the historical work data of the personnel who can be assigned to the first production line, wherein the historical work data of each personnel includes multiple work data of the personnel, and each of the multiple work data includes process characteristics and working time; the acquisition module 710 is also used to obtain the working time of the personnel in the at least one process based on the multiple work data of the personnel and the characteristics of the at least one process.

[0176] In some embodiments, module 720 is used to: train a personnel skill assessment model using the personnel's multiple work data as a training set; input the characteristics of the at least one process into the personnel skill assessment model, so that the personnel skill assessment model outputs the personnel's working time on the at least one process.

[0177] In some embodiments, the acquisition module 710 is also used to obtain the second process allocation target of the second production line and the second constraint information of the second production line input by the second user, and the second constraint information is used to constrain the allocation of processes in the second production line; the acquisition module 720 is also used to allocate stations to the processes in the second production line based on the second process allocation target and the second constraint information to obtain a third allocation result; the provision module 730 is also used to provide the third allocation result to the second user.

[0178] Among them, the acquisition module 710, the obtaining module 720 and the providing module 730 can all be implemented by software, or can be implemented by hardware. Exemplarily, the following takes the acquisition module 710 as an example to introduce the implementation of the acquisition module 710. Similarly, the implementation of the obtaining module 720 and the providing module 730 can refer to the implementation of the acquisition module 710.

[0179] As an example of a software functional unit, the acquisition module 710 may include code running on a computing instance. Among them, the computing instance may include at least one of a physical host (computing device), a virtual machine, and a container. Further, the above-mentioned computing instance may be one or more. For example, the acquisition module 710 may include code running on multiple hosts / virtual machines / containers. It should be noted that the multiple hosts / virtual machines / containers used to run the code may be distributed in the same region (region) or in different regions. Furthermore, the multiple hosts / virtual machines / containers used to run the code may be distributed in the same availability zone (AZ) or in different AZs, each AZ including a data center or multiple data centers with close geographical locations. Among them, usually a region may include multiple AZs.

[0180] Similarly, multiple hosts / virtual machines / containers used to run the code can be distributed in the same virtual private cloud (VPC) or in multiple VPCs. Usually, a VPC is set up in a region. For cross-region communication between two VPCs in the same region and between VPCs in different regions, a communication gateway needs to be set up in each VPC to achieve interconnection between VPCs through the communication gateway.

[0181] As an example of a hardware functional unit, the acquisition module 710 may include at least one computing device, such as a server, etc. Alternatively, the acquisition module 710 may also be a device implemented using an application-specific integrated circuit (ASIC) or a programmable logic device (PLD). The PLD may be a complex programmable logical device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL) or any combination thereof.

[0182] The multiple computing devices included in the acquisition module 710 can be distributed in the same region or in different regions. The multiple computing devices included in the acquisition module 710 can be distributed in the same AZ or in different AZs. Similarly, the multiple computing devices included in the acquisition module 710 can be distributed in the same VPC or in multiple VPCs. The multiple computing devices can be any combination of computing devices such as servers, ASICs, PLDs, CPLDs, FPGAs, and GALs.

[0183] It should be noted that, in other embodiments, the acquisition module 710 may be used to execute Figure 6 Any step in the method shown, the module 720 can be used to perform Figure 6 Any step in the method shown in the figure can be performed by providing module 730 Figure 6 The steps implemented by the acquisition module 710, the obtaining module 720 and the providing module 730 can be specified as needed, and the steps implemented by the acquisition module 710, the obtaining module 720 and the providing module 730 can be specified as needed. Figure 6 The different steps in the method shown implement the full functionality of the cloud management platform 700 .

[0184] The present application also provides a computing device 800. Figure 8 As shown, the computing device 800 includes: a bus 802, a processor 804, a memory 806, and a communication interface 808. The processor 804, the memory 806, and the communication interface 808 communicate through the bus 802. The computing device 800 can be a server or a terminal device. It should be understood that the present application does not limit the number of processors and memories in the computing device 800.

[0185] The bus 802 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 8 The bus 802 is represented by only one line, but it does not mean that there is only one bus or one type of bus. The bus 802 may include a path for transmitting information between various components of the computing device 800 (eg, the memory 806, the processor 804, and the communication interface 808).

[0186] The processor 804 may include any one or more of a central processing unit (CPU), a graphics processing unit (GPU), a microprocessor (MP), or a digital signal processor (DSP).

[0187] The memory 806 may include a volatile memory, such as a random access memory (RAM). The memory 806 may also include a non-volatile memory, such as a read-only memory (ROM), a flash memory, a hard disk drive (HDD), or a solid state drive (SSD).

[0188] The memory 806 stores executable program codes, and the processor 804 executes the executable program codes to respectively implement the functions of the aforementioned acquisition module 710, the obtaining module 720, and the providing module 730, thereby implementing Figure 6 That is, the memory 806 stores the method for executing Figure 6 Instructions for the method shown.

[0189] The communication interface 808 uses a transceiver module such as, but not limited to, a network interface card or a transceiver to implement communication between the computing device 800 and other devices or communication networks.

[0190] The embodiment of the present application also provides a computing device cluster. The computing device cluster includes at least one computing device. The computing device can be a server, such as a central server, an edge server, or a local server in a local data center. In some embodiments, the computing device can also be a terminal device such as a desktop computer, a laptop computer, or a smart phone.

[0191] like Fig. 9 As shown, the computing device cluster includes at least one computing device 800. The memory 806 in one or more computing devices 800 in the computing device cluster may store the same Figure 6 Instructions for the method shown.

[0192] In some possible implementations, the memory 806 of one or more computing devices 800 in the computing device cluster may also store a program for executing Figure 6In other words, the combination of one or more computing devices 800 can jointly execute instructions for executing Figure 6 Instructions for the method shown.

[0193] It should be noted that the memory 806 in different computing devices 800 in the computing device cluster may store different instructions, which are respectively used to execute part of the functions of the cloud management platform 800. That is, the instructions stored in the memory 806 in different computing devices 800 may implement the functions of one or more modules among the acquisition module 710, the obtaining module 720 and the providing module 730.

[0194] In some possible implementations, one or more computing devices in the computing device cluster may be connected via a network, which may be a wide area network or a local area network. Fig.10 A possible implementation is shown. Fig.10 As shown, two computing devices 800A and 800B are connected via a network. Specifically, the network is connected via a communication interface in each computing device. In this type of possible implementation, the memory 806 in the computing device 800A stores instructions for executing the functions of the acquisition module 710 and the acquisition module 720. At the same time, the memory 806 in the computing device 800B stores instructions for executing the functions of the providing module 730.

[0195] It should be understood that Fig.10 The functions of the computing device 800A shown in FIG. 8 may also be completed by multiple computing devices 800. Similarly, the functions of the computing device 800B may also be completed by multiple computing devices 800.

[0196] The present application embodiment also provides another computing device cluster. The connection relationship between the computing devices in the computing device cluster can be similar to that of Fig. 9 and Fig.10 The difference is that the memory 806 in one or more computing devices 800 in the computing device cluster may store the same memory for executing Figure 6 Instructions for the method shown.

[0197] In some possible implementations, the memory 806 of one or more computing devices 800 in the computing device cluster may also store a program for executing Figure 6 In other words, the combination of one or more computing devices 800 can jointly execute instructions for executing Figure 6 Instructions for the method shown.

[0198] The present application also provides a computer program product including instructions. The computer program product may be software or a program product including instructions that can be run on a computing device or stored in any available medium. When the computer program product is run on at least one computing device, the at least one computing device executes Figure 6 The method shown.

[0199] The present application also provides a computer-readable storage medium. The computer-readable storage medium may be any available medium that can be stored by a computing device or a host migration device such as a data center that includes one or more available media. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state hard disk). The computer-readable storage medium includes instructions that instruct the computing device to execute Figure 6 The method shown.

[0200] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the protection scope of the technical solutions of the embodiments of the present application.

Claims

1. A process allocation method, characterized in that: The method comprises: Acquire a first process allocation target of a first production line input by a first user, first constraint information of the first production line, and skill information of personnel that can be allocated to the first production line; wherein the first production line includes a plurality of processes, and the first constraint information is used to constrain allocation of the plurality of processes; Obtaining allocation results of the plurality of processes based on the first process allocation target, the first constraint information, and the skill information of the personnel that can be allocated to the first production line; The allocation results of the plurality of processes are provided to the first user.

2. The method according to claim 1, characterized in that The obtaining the allocation results of the plurality of processes based on the first process allocation target, the first constraint information, and the skill information of the personnel that can be allocated to the first production line includes: Obtaining a personnel allocation target and a station allocation target from the first process allocation target; and obtaining a personnel allocation constraint and a station allocation constraint from the first constraint information; Based on the personnel allocation target, the personnel allocation constraint and the skill information of the personnel that can be allocated to the first production line, allocate personnel to the multiple processes to obtain a first allocation result; Based on the first allocation result, the station allocation target and the station allocation constraint, allocate stations to the multiple processes to obtain a second allocation result; The allocation results of the multiple processes include the first allocation result and the second allocation result.

3. The method according to claim 1 or 2, characterized in that: The skill information of the personnel includes the working time of the personnel in at least one process among the multiple processes, and the method further includes: Acquire historical work data of the personnel who can be assigned to the first production line, wherein the historical work data of each personnel includes a plurality of work data of the personnel, and each of the plurality of work data includes process characteristics and work duration; Based on the multiple work data of the personnel and the characteristics of the at least one process, the working time of the personnel on the at least one process is obtained.

4. The method according to claim 3, characterized in that: The obtaining the working time of the personnel in the at least one process based on the multiple working data of the personnel and the characteristics of the at least one process includes: Using the multiple work data of the personnel as a training set, training a personnel skill assessment model; The characteristics of the at least one process are input into the personnel skill assessment model, so that the personnel skill assessment model outputs the working time of the personnel on the at least one process.

5. The method according to any one of claims 1 to 4, characterized in that The method further comprises: Acquire a second process allocation target of a second production line input by a second user and second constraint information of the second production line, where the second constraint information is used to constrain the allocation of processes in the second production line; Based on the second process allocation target and the second constraint information, allocate stations to the processes in the second production line to obtain a third allocation result; The third allocation result is provided to the second user.

6. A process allocation device, characterized in that: The device comprises: an acquisition module, configured to acquire a first process allocation target of a first production line input by a first user, first constraint information of the first production line, and skill information of personnel that can be allocated to the first production line; wherein the first production line includes a plurality of processes, and the first constraint information is used to constrain the allocation of the plurality of processes; an obtaining module, configured to obtain the allocation results of the plurality of processes based on the first process allocation target, the first constraint information, and the skill information of the personnel that can be allocated to the first production line; A providing module is used to provide the first user with the allocation results of the plurality of processes.

7. The device according to claim 6, characterized in that The module is used to: Obtaining a personnel allocation target and a station allocation target from the first process allocation target; and obtaining a personnel allocation constraint and a station allocation constraint from the first constraint information; Based on the personnel allocation target, the personnel allocation constraint and the skill information of the personnel that can be allocated to the first production line, allocate personnel to the multiple processes to obtain a first allocation result; Based on the first allocation result, the station allocation target and the station allocation constraint, allocate stations to the multiple processes to obtain a second allocation result; The allocation results of the multiple processes include the first allocation result and the second allocation result.

8. The device according to claim 6 or 7, characterized in that The skill information of the personnel includes the working hours of the personnel in at least one process among the multiple processes; The acquisition module is further used to acquire the historical work data of the personnel who can be assigned to the first production line, wherein the historical work data of each personnel includes a plurality of work data of the personnel, and each of the plurality of work data includes process characteristics and work duration; The obtaining module is further used to obtain the working time of the personnel on the at least one process based on the multiple working data of the personnel and the characteristics of the at least one process.

9. The device according to claim 8, characterized in that: The module is used to: Using the multiple work data of the personnel as a training set, training a personnel skill assessment model; The characteristics of the at least one process are input into the personnel skill assessment model, so that the personnel skill assessment model outputs the working time of the personnel on the at least one process.

10. The device according to any one of claims 6 to 9, characterized in that: The acquisition module is further used for obtaining the second process allocation target of the second production line and the second constraint information of the second production line input by the second user, wherein the second constraint information is used for constraining the allocation of processes in the second production line; The obtaining module is further used to allocate stations to the processes in the second production line based on the second process allocation target and the second constraint information to obtain a third allocation result; The providing module is further configured to provide the third allocation result to the second user.

11. A computing device cluster, characterized in that: comprising at least one computing device, each computing device comprising a processor and a memory; The processor of the at least one computing device is configured to execute instructions stored in the memory of the at least one computing device, so that the computing device cluster executes the method according to any one of claims 1 to 5.

12. A computer-readable storage medium, characterized in that: The method comprises computer program instructions, and when the computer program instructions are executed by a computing device cluster, the computing device cluster performs the method as claimed in any one of claims 1 to 5.

13. A computer program product comprising instructions, characterized in that When the instructions are executed by a computer device cluster, the computer device cluster is caused to perform the method according to any one of claims 1 to 5.

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