Process organizing device and process organizing method

Abstract

The present invention proposes a process organizing device that calculates, on the basis of worker skill evaluation information for each element work and work order information of an element work group, a work order of the element work group together with a worker allocation for each element work from evaluation of productivity and quality of a production line, and in order to optimize process organizing, the process organizing device executes: processing of accepting information of a relevant product regarding which a process organization is to be generated; processing for identifying, on the basis of process information for the overall product, a plurality of components corresponding to the relevant product, and a plurality of types of element work for the plurality of components; processing for generating preceding order information indicating order of work for the plurality of types of element work that are identified; processing for generating consolidated preceding order information by consolidating work for a plurality of second components that is performed on a first component in the preceding order information; and processing for creating a process organization by allocating each worker to the production process on the basis of the consolidated preceding order information and the skill evaluation information (Fig. 9B).

Description

Process organization device and process organization method

[0001] The present invention relates to a process organization device and a process organization method.

[0002] Currently, manufacturing sites face the risk of fluctuations in production volume, making it difficult to secure new personnel. Furthermore, the skills (abilities) of workers working in each area of ​​the manufacturing site are managed according to standards specific to that area. Under these circumstances, it is desirable to respond to flexible production, manage the skills of each manufacturing area according to a unified standard, and visualize the skills of each worker. To address these needs, the following technologies have been proposed: Patent Documents 1 to 3, for example.

[0003] Patent Document 1 proposes "a personnel management system that supports the allocation of personnel to perform specified tasks, comprising: a database that stores master information on personnel skills that indicate the proficiency of the personnel and task skills that indicate the difficulty of the task, as basic information for executing the personnel allocation process; a personnel planning function unit that refers to the master information stored in the database and plans personnel allocation to the task based on required skill information required by the task and supplied skill information that determines the supply status of the personnel based on the attendance status of the personnel; a performance acquisition and accumulation function unit that records and tallys up the work performance of the personnel performed based on the personnel allocation planned by the personnel planning function unit; and a performance evaluation function unit that evaluates the work performance of the personnel recorded and accumulated by the performance acquisition and accumulation function unit, and reflects the evaluation results of each of the personnel in the master information stored in the database."

[0004] Furthermore, Patent Document 2 discloses a system including: "a work performance storage means for storing the work performance of a plurality of workers in a plurality of processes on a production line where a plurality of workers perform relay production; a process-by-process work time variation calculation means for calculating the variation in work time for each of the processes; a worker process aptitude calculation means for calculating the process aptitude of each of the workers, which is the aptitude of each of the workers for each of the processes; and a worker assignment priority setting means for setting a high worker assignment priority for a process with a large variation in the work time to assign the worker to a process with a high worker assignment priority, and assigning a high assignment priority to a worker with a high aptitude for the process, the process aptitude calculation means ranks the process aptitude of the worker by work proficiency, which indicates the speed of the work, and when there are workers with the same rank for the process with high worker allocation priority, calculates the rank of the work proficiency for each of the workers with the next highest priority for the process, and increases the priority of the worker with lower work proficiency for the process with next highest priority, and the worker allocation priority setting means, when there are processes with the same variation in work time, calculates the difficulty of each of the processes based on the work performance, and when there are processes with the same difficulty, assigns a higher allocation priority to the process to be performed first.

[0005] Furthermore, Patent Document 3 discloses "a method for optimizing the organization of production processes divided and organized as a production line while managing the production processes with computer support, the method comprising determining the transition of quality in each of the production processes, evaluating the suitability of each of the production processes based on the determined quality transition, and reorganizing the production processes in a manner that reflects the evaluations."

[0006] JP 2014-211766 A Japanese Patent No. 7427867 A JP 2002-304210 A

[0007] The aforementioned Patent Document 1 describes an allocation support technology for appropriately allocating part-time workers with irregular work schedules to work on each line. However, this technology judges the required skills of each line based on the predetermined skills, and does not reorganize each line, i.e., each process, which can result in cases where workers with insufficient skills must be allocated.

[0008] Furthermore, the aforementioned Patent Document 2 describes a technology in which, in the step of calculating process suitability, each process is ranked by its work proficiency, which indicates the speed at which the work is performed, and the difficulty level is calculated from the variance in work time, thereby determining the allocation priority of the processes. However, the technology evaluates the work proficiency and difficulty level for each predetermined process, and does not evaluate the elemental work that makes up the process, but rather requires evaluation based on the actual performance values ​​for each process. Furthermore, unlike Patent Document 1, it does not reorganize processes taking into account the skills of the workers to be assigned.

[0009] Furthermore, the above-mentioned Patent Document 3 describes a technique for appropriately evaluating a production process based on quality trends such as the number of defects, the defect rate, the number of line stops, etc., as a method for appropriately managing an organized production process. However, this technique involves allocating personnel based on the process organization, and does not evaluate the suitability of the process organization based on the skills of the personnel.

[0010] In light of this situation, the present invention proposes a technology for optimizing process organization by calculating the work sequence of element work groups along with the worker assignment for each element work based on an evaluation of the productivity and quality of the production line, using worker skill evaluation information for each element work and work sequence information for the element work groups.

[0011] In order to solve the above-mentioned problems, the present invention proposes a process organization device that performs a process of assigning workers to a production process of a product, the process including: a storage device that stores overall product process information that associates and manages information on a plurality of parts that make up the product with information on a plurality of types of elemental work included in the production process; skill evaluation information that defines the skills of each worker with respect to the plurality of types of elemental work; and a process organization program; and a processor that reads the process organization program from the storage device and executes it, wherein the processor performs the following processes: receives information on a product for which a process organization is to be generated; identifies a plurality of parts that correspond to the target product and the plurality of types of elemental work for the plurality of parts based on the overall product process information; generates precedence ranking information that indicates the work order of the identified plurality of types of elemental work; generates aggregated precedence ranking information by aggregating, from the precedence ranking information, operations for a plurality of second parts that are performed on a first part; and creates a process organization by assigning each of the workers to the production process based on the aggregated precedence ranking information and the skill evaluation information.

[0012] According to the present invention, it is possible to provide a technology for optimizing process scheduling by deriving process scheduling based on worker skill information for each elemental task type. Problems, configurations, and effects other than those described above will become clear from the description of the following embodiments.

[0013] 9B is a diagram showing an example of the configuration of a process organization system 10 according to an embodiment of the present invention. FIG. 9C is a diagram showing an example of the hardware configuration of a process organization device 100. FIG. 9D is a diagram showing an example of the data structure of overall product process information 121. FIG. 9E is a diagram showing an example of the data structure of element task classification information 122. FIG. 9F is a diagram showing an example of the data structure of element task information 123 that defines the element task IDs of the element task classification information 122. FIG. 9G is a diagram showing an example of the data structure of skill evaluation information 124. FIG. 9H is a diagram showing an example of a skill evaluation information graph 125. FIG. 9H is a flowchart for explaining process organization processing according to an embodiment of the present invention. FIG. 9I is a diagram showing an example of a predecessor ranking diagram 131. FIG. 9I is a diagram showing an example of a predecessor ranking diagram 132 in which the same element tasks are aggregated and consolidated based on the predecessor ranking diagram 131 of FIG. 7. FIG. 9I is a diagram showing an example of the results of clustering component placement information of component IDs that are worked on by element task IDs based on the predecessor ranking diagram 132 of FIG. 9B. FIG. 9I is a diagram showing a directed graph in which task groups summarized by clustering are regarded as large nodes based on the predecessor ranking diagram 133 that is the clustering result. FIG. 9I is a diagram showing a list of the results of sorting the predecessor ranking diagram of FIG. 9B. 10. FIG. 11 is a diagram showing an example of the work time for each element work of available workers in response to the sorting result of the precedence chart shown in FIG. 10. FIG. 12 is a diagram showing an example of the output of the calculation result of process organization. FIG. 13 is a diagram showing an example of the configuration of a calculation screen of the process organization device 100. FIG. 14 is a diagram showing an example of the configuration of a work instruction screen generated based on the process organization result (FIG. 13) of the process organization device 100.

[0014] Hereinafter, embodiments of the present invention will be described with reference to the drawings. In all drawings used to describe the embodiments, the same components are generally designated by the same reference numerals, and repeated description thereof may be omitted. In the following embodiments, it goes without saying that components are not necessarily essential unless otherwise specified or considered to be fundamentally essential. Furthermore, when the terms "consisting of A," "made of A," "having A," or "including A" are used, it goes without saying that they do not exclude other elements, unless otherwise specified to include only the relevant element. Similarly, in the following embodiments, when referring to the shape, positional relationship, etc. of components, etc., it is intended to include those that are substantially similar or similar to the shape, etc., unless otherwise specified or considered to be fundamentally essential.

[0015] <Configuration Example of Process Organization System> Fig. 1 is a diagram showing a configuration example of a process organization system 10 according to an embodiment of the present invention. The process organization system 10 includes a process organization device 100 and an external device 145 that can communicate with the process organization device 100 via a network 144 such as a local area network (LAN) or the Internet. The process organization device 100 and the external device 145 are configured to be able to operate in cooperation with each other. The process organization device 100 can also function as, for example, a server device. The external device 145 is, for example, a device (which can be configured as a computer) used when a user instructs the process organization device 100 to perform worker allocation processing.

[0016] The network 144 is a communication path such as a LAN, a wireless LAN, etc. Note that the communication between the external device 145 and the process orchestration device 100 is not limited to that via the network 144, and may be a wired communication path such as a USB (Universal Serial Bus) or a wireless communication path such as Bluetooth.

[0017] The process orchestration device 100 is, for example, an independently operable general-purpose computer. The process orchestration device 100 includes a calculation unit (processor) 110, a storage unit 120, an input unit 141, a display unit 142, and a communication unit 143.

[0018] The calculation unit 110 includes a precedence order generation unit 111 and a process organization unit 112. The storage unit 120 includes overall product process information 121, element work classification information 122, skill evaluation information 124, an analysis calculation program 128, and calculation condition information 129.

[0019] The analytical calculation program 128 and the calculation condition information 129 store the analytical calculation program and the calculation condition information, respectively, used by the calculation unit 110. The calculation condition information 129 stores calculation condition information set based on the component type, component size, component placement order, and adjacent relationships between components. The calculation condition information includes, for example, conditions for determining whether a task can be assigned to a worker or not.

[0020] 2 is a diagram showing an example of the hardware configuration of the process organization device 100. The process organization device 100 includes a display device 171 such as a display, a ROM 172 that performs read / write processing on a CD (Compact Disc)-ROM (Read Only Memory) or a DVD (Digital Versatile Disk)-ROM, an operation device 173 such as a keyboard, a mouse, or a touch panel, a RAM (Random Access Memory) 174, an auxiliary storage device 175 such as an HDD (Hard Disk Drive) or an SSD (Solid State Drive), a communication device 176 such as a network card, and a CPU (Central Processing Unit) 177.

[0021] The display device 171 is a display device such as a liquid crystal display or an organic EL (Electro-Luminescence) display, and displays the results of processing by the CPU 177. The operation device 173 is a touch panel, keyboard, mouse, etc., and accepts instructions from a user. The RAM 174 is a storage device into which programs stored in the auxiliary storage device 175 are loaded. The RAM 174 also temporarily stores data. The auxiliary storage device 175 is a storage device that stores various data used by the programs. The communication device 176 is connected to a network 144 such as the Internet, and exchanges various data with other devices connected to the network 144. The CPU 177 is a control unit that performs calculations in accordance with the programs loaded on the RAM 174.

[0022] <Overall Product Process Information> FIG. 3 is a diagram showing an example of the data structure of the overall product process information 121. The overall product process information 121 includes an identifier 121a, a classification 121b, an item 121c, and a value 121d. For simplicity's sake, FIG. 3 shows only example values ​​for two parts, but in reality, the information includes information on the parts necessary to produce the corresponding product. The overall product process information includes information identifying the component parts and their structure, as well as a series of information related to the work involved, for an assembled finished product, which is a product manufactured by assembling parts. In this embodiment, a product does not refer to the processing of a single part, but includes assembly work consisting of multiple parts.

[0023] The identifier 121a is information for identifying the configuration information of the overall product process information. The classification 121b is information indicating items related to the overall product process information. In this embodiment, the classification 121b includes classifications such as product information, part attributes, shape characteristics, part placement, part configuration, part adjacency relationships, and work attributes, but is not limited to these, and stores information related to the assembly work of parts.

[0024] The item 121c is information indicating items related to the overall product process information. In this embodiment, the item 121c includes various items related to product information such as a product ID, and part attributes such as a part ID, a layer number, a model name, a model shape file path, a part drawing number, and part type information.

[0025] Here, a product ID is product information that is uniquely identified based on product design information and work constraints such as production base, and is information that is generally managed as design information and production management information, such as serial number, drawing number, and product number.

[0026] The part attributes include information about the attributes of all parts that make up a product. Part IDs are also assigned to hierarchical levels consisting of multiple parts, such as top assemblies and sub-assemblies.

[0027] The model shape file path indicates the storage location of a file that stores 3D model information that indicates the shapes of parts that make up the product. For example, the file may be converted from product design information into STL (Standard Triangulated Language), or other 3D shape data file formats that can be converted by the 3D CAD device 200, such as STEP, obj, and gltf. This model shape file is used as output information from the process orchestration unit 112 when checking the 3D model shape as needed.

[0028] The part type information is a character string that classifies the part type according to predefined part type classification rules based on the model name and part shape. Specifically, if the model name contains "BOLT", the part type is classified as "bolt", and if the model name contains "SCREW", the part type is classified as "screw". Also, based on the shape information obtained from the 3D model information, classification may be performed according to predefined part type classification rules based on the similarity of shape characteristics. If no corresponding definition exists, "- (meaning NA)" is assigned.

[0029] Similarly, item 121c includes various items such as items related to shape characteristics such as volume, surface area, and center of gravity; various items related to part configuration such as parent part ID and child part ID; various items related to part placement such as part coordinate system and part origin; various items related to part configuration such as parent part ID; items related to part adjacency relationships such as adjacency relationships; and items related to work attributes such as work ID, part ID, tools used, equipment used, work content, and previous work ID. Items with identifiers 0 to 11 (from product ID to part origin) are information related to the attributes of the corresponding parts. Furthermore, items with identifiers 12 to 19 (from parent part ID to previous work ID) are information related to the relationship between the corresponding part and other parts.

[0030] Here, the part placement indicates the position and orientation of the part in the final position of the assembled product. The part configuration stores the parent part ID, which is the parent level of the part itself, such as a subassembly, and defines the part configuration information.

[0031] The inter-part adjacency relationship refers to the relationship between parts in an assembly model. For example, one method of clearance analysis involves searching for other models within a clearance distance from each face of a modeled part based on a set threshold, and creating position and orientation information for the faces (planes, cylindrical surfaces, conical surfaces, etc.) of the adjacent parts obtained as a result of the search. In addition to clearance analysis, assembly constraint information modeled when creating an assembly model using 3D CAD may also be used. For planes, the constraint surface information obtained from this information is preferably obtained by obtaining a point on the surface as the constraint surface origin using a constraint surface normal vector pointing outward from the model. For cylindrical surfaces, it is desirable to obtain a point on the axis of the cylinder as the constraint surface normal vector and create the constraint surface origin using a point on the axis.

[0032] The value 121d shows two examples of specific values ​​for each item related to the part represented in the overall product process information.

[0033] The task attributes are various pieces of information related to task attributes when assembling the part. In this example table, task attributes are shown in the same column as the part information, but the information is not information only about the part ID, but values ​​for each task ID. The task attributes include information about the part ID to be worked on for each task ID. The task attributes also include the tools and equipment used in the task, as well as the task priority as the preceding task ID, for example, if task ID = 13, tasks with task IDs 4 and 6 must be done first. The task details store specific task details and precautions for each task ID.

[0034] <Example Data Structure of Component Task Classification Information> Figure 4A is a diagram showing an example data structure of component task classification information 122. The component task classification information 122 includes a product ID 122a, a task ID 122b, and an element task ID 122c as its constituent items. Figure 4B is a diagram showing an example data structure of component task information 123, which defines the component task IDs of the component task classification information 122. The component task information 123 includes a No. 123a, a major category 123b, an element task ID 123c, an element task name 123d, and a consecutive task ID 123e as its constituent items. While Figures 4A and 4B show an example in which the component task information 123 is used as separate data to define the element task ID 122c used in the component task classification information 122, a single data structure may also be used. Here, the consecutive task ID 123e defines that, for example, in the case of screw tightening work, this is an element task that is performed immediately after part installation work or wiring connection work.

[0035] 4A and 4B, the element work classification information 122 stores element work IDs for the product IDs and work IDs of the product information in the overall product process information in Fig. 3. The element work information also defines the content of the element work ID.

[0036] <Example of Data Structure of Skill Information> Fig. 5A is a diagram showing an example of the data structure of skill evaluation information 124. The skill evaluation information 124 includes a worker ID 124a, an element task ID 124b, an operation time (average) 124c, and an operation time (standard deviation) 124d. The skill evaluation information 124 holds information on the average operation time and standard deviation of element tasks for each worker. Note that element tasks may require qualifications or may be difficult tasks that are difficult to master. Therefore, a flag indicating "unassignable" is also stored so that workers who have not yet acquired the necessary skills cannot be assigned to the task.

[0037] 5B is a diagram showing an example of the skill evaluation information graph 125. The skill evaluation information graph 125 shows an example in which the work time for each element work is displayed as a bar graph for three selected worker IDs based on the work time (average) of the skill evaluation information 124.

[0038] The overall product process information 121 in Fig. 3, the element work classification information 122 and element work information 123 in Fig. 4, and the skill evaluation information 124 in Fig. 5 may be configured as a database, or as a file in XML (eXtensible Markup Language) format or a file in JSON (JavaScript Object Notation) format. The same applies to the data structures described below.

[0039] 6 is a flowchart illustrating the process organization process according to an embodiment of the present invention. The process organization process is executed by the process organization device 100. The process organization process is a process that extracts workers who can handle each element task based on the overall process information of the product to be calculated, the worker information of the calculation conditions, and the target KPI specified by the input unit 141, derives a process organization plan that satisfies the target KPI, outputs the process organization results and KPI evaluation results, and further outputs work instruction information based on the process organization results.

[0040] (i) Step S10 The calculation unit 110 acquires the overall product process information 121 (see FIG. 3) of the calculation target specified by the input unit 141. Specifically, when the user inputs the product ID of the product information to be calculated from the external device 145, the calculation unit 110 acquires the overall product process information 121 including the corresponding part attributes, shape characteristics, part placement, part placement, part adjacency relationships, and operation attributes. Note that the flowchart in FIG. 6 omits detailed descriptions of the 3D model modeling operation and the operation of specifying the model to be analyzed, but it is assumed that processing related to general operations is performed.

[0041] (ii) Step S20: The calculation unit 110 acquires the task ID and the element task ID related to the input product ID from the element task classification information 122 (see FIGS. 4A and 4B). Specifically, the CPU 177 acquires the element task ID using the product ID and task ID in the overall product process information 121 as keys.

[0042] (iii) Step S30: The precedence ranking generation unit 111 generates a precedence chart. Specifically, the precedence ranking generation unit 111 converts the task IDs and predecessor task IDs into precedence rankings based on the task attribute task IDs and their predecessor task IDs in the overall product process information 121 acquired in step S10 and the element task classification information 122 acquired in step S20. (The precedence ranking chart is generated by checking the parent-child relationships and layout relationships of each component using information indicated by the parent component ID, adjacent relationship information, and component ID information in the task attribute, as shown in FIG. 3 .) Here, the task content listed for each task ID in the overall product process information 121 stores specific task instructions. The element task information 123 stores element task information in which major categories and element task names are pre-classified. The element task classification information 122 converts the specific task content for each product into the classified element tasks using the classified element task IDs.

[0043] FIG. 7 is a diagram showing an example of the precedence chart 131. In FIG. 7, the process up to step S30 involves acquiring task IDs and preceding task IDs from the overall product process information 121, converting those task IDs into element task IDs based on the element task classification information 122, and then using a directed graph to represent the result of grasping the precedence order based on the element task IDs, with the element tasks as nodes and the precedence orders as directed edges. In FIG. 7, the character strings written within the nodes indicate the type and sequential number of the element task name listed in the element task information 123. The initial character S represents part attachment, F represents screw tightening, W represents wiring routing, C represents wiring connection, and T represents high-coupling. The shape of each node represents the type of element task name. For example, the shape shown in the lower row is used as a legend for the bar graph 125 of the skill evaluation information in FIG. 5.

[0044] As shown in Figure 7, if each task, such as a screw tightening operation, were represented as a single node, the graph structure would become complicated. However, since this is a task in which one part is attached using multiple screw tightening operations and these operations are performed simultaneously, they are considered as a single task when organizing the process. Therefore, when a combination of element tasks with the same element task name and the same precedence order is performed, the nodes are aggregated by tallying the number of workers involved, which is done when generating the element task precedence order diagram (step S30).

[0045] Figure 8 is a diagram showing an example of a predecessor order diagram 132 in which the same element operations are aggregated and consolidated based on the predecessor order diagram 131 of Figure 7. The n in the "xn" written to the lower right of a node indicates the aggregate value of the same element operations (the total number of the same elements). In this way, by converting the directed graph of Figure 7 into an aggregated data structure (reducing the number of nodes), it is possible to reduce problems such as complex processing due to a large number of nodes and slow calculation processing speed.

[0046] Furthermore, even though some tasks are defined as separate element tasks, they must be performed as a continuous flow without any intermediate separation. For example, a screw tightening task is not complete until the part is aligned and the screw that secures the part in its designated position is tightened. Similarly, for example, fastening a wire using a screw is also a continuous task. Specifically, as shown by the continuous task IDs in the element task information 123 in FIG. 4 , the continuous task IDs for the screw tightening element task are stored as the element task IDs for part installation and wire connection. In the case of screw tightening, the calculation condition information 129 of the process orchestration device 100 specifies that such tasks, including part installation and wire connection, are to be calculated as a continuous task and that the connections between adjacent nodes and edges are to be set strong. While edges are shown in bold in FIG. 8 , in the process orchestration process, edges with strong connections (that cannot be divided) are to be treated as a continuous task and calculated. By adding constraints such as strong connections to edges, it is possible to constrain the problem of complex directed graph processing.

[0047] (iv) Step S40: The calculation unit 110 acquires the worker information and target KPIs that are the calculation conditions input from the external device 145. Specifically, the calculation unit 110 acquires information on the IDs of available workers (workers who are at work and not assigned other tasks) to determine which workers can be assigned to the production of this product. In addition, the calculation unit 110 acquires the target value of the takt time per worker calculated from the number of units produced, as an example of the target KPI.

[0048] (v) Step S50: The calculation unit 110 acquires the skill evaluation information 124 related to the worker information acquired in step S40. For example, when the worker IDs AAA, BBB, and CCC are input, the operation time for each element task ID is determined from the skill evaluation information 124 for each worker ID.

[0049] (vi) Step S60: The process orchestration unit 112 extracts available workers and skill evaluation information for each element work in the precedence order diagram 132. Available workers here differ from the meaning of "available" in step S40, and there may be cases where the available workers have no experience with the skills defined in the element work or do not have the qualifications. Therefore, the process narrows down and selects workers who do not have the "unassignable" flag in the skill evaluation information 124.

[0050] Furthermore, if the calculation condition information 129 is set to determine that a worker capable of performing each element task is "difficult to assign" if the task time is greater than 1.5 times the average task time of all workers, then in the bar graph 125 of skill evaluation information in Figure 5, "wiring connection" for worker ID: CCC is determined to be "difficult to assign." This determination method may be based on the average task time, or on the standard deviation or coefficient of variation (standard deviation / average value), which is the variance in task time. In this way, the element task ID of a worker ID determined to be "difficult to assign" is given a lower priority for assignment to that element task in the process organization process.

[0051] Furthermore, the process orchestration unit 112 refers to the skill evaluation information 124 for available workers, and extracts the work time of each worker ID for the element work ID included in the precedence order diagram.

[0052] (vii) Steps S70 and S80: The process orchestration unit 112 generates a process orchestration plan for available workers (skilled workers) that satisfies the target KPI. Line balancing, a method for designing a process orchestration by allocating resource information, such as workers, to a precedence diagram, which is a network of work processes, to satisfy the target cycle time and takt time based on a production plan, is typically performed using mathematical programming or heuristic solutions. However, when a precedence diagram with a large number of parts and operations, which is a large directed graph, is used as input, mathematical programming requires a significant amount of computation time to derive an optimal solution for a large-scale problem. Furthermore, while heuristic solutions can provide an approximate optimal solution, the selection of a method for deriving the solution and the addition of constraints are important. As a solution method for this process orchestration, for example, mathematical programming such as 0-1 integer programming, multi-objective optimization problem solving, or the use of a linear programming solver, or heuristic solutions such as positional weighting, may be used.

[0053] (viii) Step S90: The process orchestration unit 112 outputs the process orchestration results and the KPI evaluation results. The process orchestration unit 112 transmits the results to the external device 145, for example, via the communication unit 143 and the network 144. The external device 145 receives these results and displays them on a display screen.

[0054] (ix) Step S100 The process orchestration unit 112 generates and outputs work instruction information (see FIG. 14) based on the process orchestration result.

[0055] <Example of generating a process organization plan> Figure 8 shows the result of converting the initial precedence chart 131 of Figure 7 into a precedence chart 132 in which adjacent element task nodes are treated as edges that represent consecutive tasks by aggregating and consolidating the same element tasks and extracting consecutive task IDs for specific element tasks from the element task information 123. This conversion makes it possible to reduce the size of a precedence chart consisting of a large number of nodes.

[0056] 9A is a diagram showing an example of the results of clustering the component placement information of the component IDs of components performed by the element task IDs based on the predecessor order diagram 132 of FIG. 8. Here, because the continuous tasks related to "screw tightening" shown in FIG. 8 are element tasks performed collectively, the bold edges shown in FIG. 8 have been deleted and the nodes are depicted as being arranged with the nodes joined. The dotted frame lines indicate the clusters resulting from the clustering. Specifically, the component IDs to be worked on for each task ID, which is the basis for the element task IDs in the predecessor order diagram 132, were identified from the component placement information in the overall product process information 121, and the component placements and centers of gravity of those component IDs were referenced, and clustering was performed using their coordinate values ​​as feature quantities. For example, for a part ID corresponding to a task ID based on an element task ID, the system extracts the centroid (gx1, gy1, gz1) of the part itself and all associated components at the end of the edge of the predecessor diagram from the overall product process information 121. Clustering is performed using six features: the centroid (gx2, gy2, gz2) of the largest component among the associated components. Many clustering methods are possible. For example, DBSCAN (Density-Based Spatial Clustering of Applications with Noise) is density-based, allowing for an arbitrary number of clusters without a predefined number of clusters. It also allows for clustering of components with similar features within a set range of conditions. Furthermore, because it allows for outliers, it can accommodate components that fall outside the specified range and do not belong to any cluster. This makes it useful for clustering in this method, which groups tasks based on component location, i.e., task position. In the example of Figure 9A, the results of this clustering based on component location are represented as nodes for the element task ID.

[0057] For example, in assembly work, it is necessary to perform work in groups according to the work positions of the parts to be assembled on a large stand, such as work from the left side, work from the right side, work on the ceiling, work inside the stand, etc. Therefore, by clustering in consideration of the part to be assembled and the part positions of the parts to be assembled that are grasped according to the precedence chart, it is possible to perform grouping that takes into account the work to be performed in groups.

[0058] 9B shows, as a directed graph, the results of clustering work groups into large nodes based on the clustering result of the predecessor diagram 133. When there are a large number of parts and operations, the process network diagram defining the work processes, i.e., the predecessor diagram, becomes large in scale, and the scale of the problem (such as a problem of complex processing) in the calculation of process organization increases, which can result in a significant amount of processing time required to derive a solution.

[0059] Therefore, the directed graph representing the precedence diagram to be calculated can be made smaller by aggregating task nodes when the combination of assembled parts is the same for the same element task ID as shown in FIG. 8, aggregating task nodes of consecutive task IDs set in advance for a specified element task ID, and aggregating task nodes by grouping through clustering of element task IDs with close component arrangements, i.e., task positions.

[0060] <Sorting Results of Precedence Order Diagram> Figure 10 is a diagram showing a list of the results of sorting the precedence order diagram of Figure 9B. Specifically, in the precedence order diagram 134 shown in Figure 9B, element task S1 is defined as the first task to be performed, and then topological sorting is performed. The list shows the results of arranging the nodes in a row so that all the arrows of the directed edges are unidirectional (in Figure 10, the arrows always point from right to left). In this example, the four orders shown in the list were obtained. For example, to explain the work procedure using the precedence order diagram of 135a, after element task S1, element task S2 and the subsequent element task F1 are performed, followed by work in the work group of cluster 1, followed by element task S3 and the subsequent element task F2, followed by work in the work group of cluster 2, followed by element task W2, followed by work in the work group of cluster 3.

[0061] In the case of the predecessor diagram 134 shown in Figure 9B, the node with the most inputs from edge arrows and no output arrows is the starting point, i.e., the first task. Conversely, a node with no inputs from edge arrows is a candidate for the end point. In the example of the predecessor diagram 134, cluster 1 and cluster 3 are the task nodes that will be last in the order.

[0062] In topological sorting, after selecting one end node, the extracted end node and edge are removed, and the next end node candidate is selected in the directed graph, and the same operation is repeated to sort the nodes. Even when searching for an order from a directed graph in this way, if there are a large number of nodes and edges, it takes a long time to derive all the orders or the optimal order. Therefore, reducing the directed graph by aggregating and clustering the precedence graph shown in Figure 8, Figure 9A, and Figure 9B is useful.

[0063] In this embodiment, an example of rearranging the work order by topological sorting has been shown, but a graph search algorithm such as breadth-first search may also be used.

[0064] Based on the sorting results of the precedence order shown in FIG. 10, the process orchestration unit 112 calculates the workers who can handle each element work in the precedence order diagram identified in step S60 and their skill evaluation information.

[0065] <Example of Determining an Optimal Worker> Figure 11 is a diagram showing an example of the task times for each element task of available workers, based on the sorting results of the precedence chart shown in Figure 10. Specifically, Figure 11 shows the results of calculation based on the example of skill evaluation information shown in Figure 5, as an example when worker IDs AAA, BBB, and CCC are entered as worker information in the calculation conditions in step S40 of Figure 6.

[0066] Here, assuming that the target KPI input for the calculation conditions in step S40 is, for example, a takt time per worker of 20 seconds or less, the process orchestration unit 112 derives a process division that satisfies this condition, has good line balance, and minimizes the total value of all task times from the task times 136 in the list of sorted results of the precedence chart. Each table in FIG. 11 shows an example of a process division that satisfies the takt time target of 20 seconds per worker, outlined in bold. For each sorting result, the worker IDs and total task times for 136a and 136b are AAA: 19.8 seconds, BBB: 18 seconds, and CCC: 16.7 seconds, while for 136c and 136d, they are AAA: 19.5 seconds, BBB: 18 seconds, and CCC: 17.0 seconds. As a result, the process orchestration unit 112 selects 136a and 136b as the process division and task assignment that minimizes all total values. Furthermore, when there are multiple process divisions with the same total work time, the process division with the least variation in work time may be selected by referring to the work time (standard deviation) 124d in FIG. 5A.

[0067] The same calculation can be performed when there is an increase or decrease in the number of workers, or when the target takt time is changed. However, if the total value of the work time at a node combined into one due to aggregation or clustering of the precedence diagram becomes larger than the target takt time, it is necessary to divide the aggregation node by performing clustering within the aggregation node.

[0068] <Example of output of calculation results for process organization> Figure 12 is a diagram showing an example of the output of the calculation results for process organization. As the calculation results of the process organization plan in steps S70 and S80, the target takt time is displayed, along with the process division plan and the calculation results of the work time for each assigned worker. When multiple process division plans are selected as described above, the user can switch between them using the "process division plan" pull-down menu as shown in the figure and check the results.

[0069] <Example of Screen Configuration in Process Scheduling> FIG. 13 is a diagram showing an example of the configuration of the calculation screen of the process orchestration device 100. As shown in the overall product process information 121 in FIG. 3 , when information on the product model shape exists, specifically, when the process orchestration device 100 performs calculations using 3D CAD data as input, 3D model data can be utilized. The left side of FIG. 13 is a screen showing the 3D model shape and an area displaying 3D model information for a selected 3D model component. The center of FIG. 13 is an area for displaying and manipulating hierarchical information showing the parent-child relationships of the components constituting the product as an EBOM tree. For example, by checking or unchecking a checkbox, the display of the 3D model shape of the selected component can be switched. Furthermore, the right side of FIG. 13 is an area for viewing and manipulating the directed graph of the precedence diagram, such as the precedence diagrams shown in FIGS. 7 , 8 , 9A , and 9B , by displaying by component ID, by displaying by task ID, by displaying the results converted to element task IDs, by displaying by aggregated element task nodes, and by displaying the results of clustering based on component placement information. This directed graph, EBOM tree, and 3D model are linked in both directions, and when a node in the precedence diagram is selected, the node in the EBOM tree and the corresponding part in the 3D model are highlighted.

[0070] Furthermore, when classifying elemental work, classification is performed according to the part type on the 3D CAD, such as fastening screws or wiring work, but if the part type classification on the 3D CAD is insufficient (parts indicated by [?] in FIG. 13), the user can set or update the part type on the screen using the "part type setting menu 1301" shown in the lower right.

[0071] <Configuration Example of Work Instruction Screen> Figure 14 is a diagram showing a configuration example of a work instruction screen generated based on the process organization result (Figure 13) of the process organization device 100. The center of the figure shows the result of process organization, which is the conversion of an EBOM tree showing the 3D CAD part configuration, which is the input product design information, into an MBOM (work process) showing the work process. For example, the generated process division result is shown in the MBOM tree with hierarchical levels such as Step No. 1 and Step No. 2. The work content is displayed on the work instruction information screen in the lower right according to the content of the selected process based on the design information. These display contents are displayed based on, for example, the product ID, part ID, and part placement information from the overall product process information 121, and the work attribute information such as the tools used, equipment used, and work content.

[0072] <Others> The process orchestration device according to this embodiment has been described in detail above. However, the present invention is not limited to the above-described examples and includes various modifications. For example, the above-described examples have been described in detail to clearly explain the present invention, and the present invention is not necessarily limited to those including all of the described configurations. It is possible to replace part of the configuration of the examples with other configurations, and it is also possible to add other configurations to the configuration of the examples. It is also possible to delete part of the configuration of the examples.

[0073] It should be noted that the control lines and information lines in the above-described embodiments are those considered necessary for the explanation, and do not necessarily show all the control lines and information lines in the product. In reality, it can be considered that almost all components are interconnected. The present invention has been described above, focusing on the embodiments.

[0074] 10 Process organization system 100 Process organization device 110 Calculation unit 111 Priority generation unit 112 Process organization unit 120 Storage unit 121 Overall product process information 122 Element work classification information 124 Skill evaluation information 128 Analysis calculation program 129 Calculation condition information 141 Input unit 142 Display unit 143 Communication unit 144 Network 145 External device

Claims

1. A process orchestration device that performs a process of assigning workers to a product's production process, comprising: a storage device that stores overall product process information that associates and manages information on a plurality of parts that make up the product with information on a plurality of types of elemental work included in the production process; skill evaluation information that defines the skills of each worker with respect to the plurality of types of elemental work; and a process orchestration program; and a processor that reads and executes the process orchestration program from the storage device, wherein the processor performs the following processes: a process of receiving information on a product for which a process orchestration is to be generated; a process of identifying a plurality of parts that correspond to the target product and the plurality of types of elemental work for the plurality of parts based on the overall product process information; a process of generating precedence ranking information that indicates the order of work for the identified plurality of types of elemental work; a process of generating aggregated precedence ranking information by aggregating work performed on a single part for a plurality of other parts within the precedence ranking information; and a process of creating a process orchestration by assigning each worker to the production process based on the aggregated precedence ranking information and the skill evaluation information.

2. A process orchestration device as claimed in claim 1, wherein the overall product process information includes the product, the multiple parts, geometric information of the multiple parts, adjacency relationship information of the multiple parts, part placement information of the multiple parts, parent part information to which the target part is attached, task attribute information related to the tasks of assembling the multiple parts, and task priority information; the information on the multiple types of element tasks includes element task classification information that classifies the tasks of assembling the multiple parts; and the processor represents the precedence information and the aggregated precedence information as directed graphs according to the task priority information, divides the multiple tasks included in the aggregated precedence information expressed in the directed graph, and assigns each of the workers to the divided tasks.

3. A process orchestration device according to claim 1, wherein the processor represents at least the aggregated precedence information as a directed graph, with the element operations as nodes and the precedence orders between parts as directed edges.

4. A process organization device according to claim 1, wherein the overall product process information includes type information of the plurality of parts, and the processor classifies the plurality of types of element work in accordance with the type information of the plurality of parts corresponding to the target product.

5. A process organization device according to claim 1, wherein the skill evaluation information includes information on the working time of each of the workers for each of the plurality of elemental industries, and the process of creating the process organization includes: a process of identifying, in the aggregate precedence information, a plurality of work groups that do not affect each other's work order; a process of generating combinations of the process organization by rearranging the plurality of work groups; a process of calculating a total process working time by adding up the working time of each of the workers for each combination of the process organization; and a process of outputting information on the process organization with the shortest total process working time.

6. A process organization device according to claim 5, wherein the processor calculates the work time of each worker for the plurality of work groups, and calculates the total process work time for each of the process organization combinations based on the calculated work time.

7. A process organization device according to claim 5, wherein the processor outputs information on the process organization that minimizes the total process work time, as well as information on the 3D model of the product and the aggregated precedence information.

8. A process organization device as claimed in claim 2, wherein the processor performs at least one of aggregation processing when the combination of adjacent parts is the same in the precedence order information expressed in the directed graph, aggregation processing when continuous operations exist, or aggregation processing by clustering based on part placement information.

9. A process organization method for assigning workers to a product production process using a computer, comprising: providing a storage device for storing overall product process information that associates and manages information on a plurality of parts that make up the product with information on a plurality of elemental operations included in the production process, skill evaluation information that defines the skills of each worker with respect to the plurality of elemental operations, and a process organization program; reading the process organization program from the storage device; accepting information on a product for which a process organization is to be generated; identifying a plurality of parts that correspond to the target product and the plurality of elemental operations for the plurality of parts based on the overall product process information; generating precedence ranking information that indicates the operation order of the identified plurality of elemental operations; generating aggregated precedence ranking information by aggregating operations for a plurality of other parts that are performed on one part; and creating a process organization by assigning each of the workers to the production process based on the aggregated precedence ranking information and the skill evaluation information.

10. A process organization method as set forth in claim 9, wherein the overall product process information includes the product, the multiple parts, geometric information of the multiple parts, adjacency relationship information of the multiple parts, part placement information of the multiple parts, parent part information to which the target part is attached, task attribute information related to the tasks of assembling the multiple parts, and task priority information; the information on the multiple types of element tasks includes element task classification information that classifies the tasks of assembling the multiple parts; and the computer represents the precedence information and the aggregated precedence information as directed graphs according to the task priority information, divides the multiple tasks included in the aggregated precedence information represented by the directed graph, and assigns each of the workers to the divided tasks.

11. A process organization method according to claim 9, comprising representing at least the aggregated precedence information as a directed graph, with the element operations as nodes and the precedence orders between parts as directed edges.

12. A process organization method according to claim 9, wherein the overall product process information includes type information of the plurality of parts, and the method includes classifying the plurality of types of element work in accordance with the type information of the plurality of parts corresponding to the target product.

13. A process organization method according to claim 9, wherein the skill evaluation information includes information on the working time of each of the workers for each of the plurality of elemental industries, and creating the process organization includes: identifying, in the aggregate precedence information, a plurality of work groups that do not affect each other's work order; generating combinations of the process organization by rearranging the plurality of work groups; calculating a total process working time by adding up the working time of each of the workers for each combination of the process organization; and outputting information on the process organization with the shortest total process working time.

14. A process organization method according to claim 13, comprising calculating the work time of each worker for the plurality of work groups, and calculating the total process work time for each of the process organization combinations based on the calculated work time.

15. A process organization method according to claim 13, comprising outputting information on the process organization that minimizes the total process work time, as well as outputting information on a 3D model of the product and the aggregated precedence information.

16. A process organization method as set forth in claim 10, comprising performing at least one of aggregation processing when the combinations of adjacent parts are the same in the precedence order information expressed in the directed graph, aggregation processing when continuous operations exist, or aggregation processing by clustering based on part placement information.

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