Process planning device, production line system, and process planning method

Abstract

To provide a technology of readily devising a process plan that suppresses operation cost.SOLUTION: A process planning device includes: a memory unit that stores product information on an assembly product, resource information on resources employed in production, and component / resource combination information containing a restriction and ability of a combination of components included in the assembly product and resources; an assembling order candidate generation unit that generates a candidate draft for an assembling order of components according to a priority criterion which meets restriction and corresponding to the resources; a line balancing unit that generates candidates for process design information by performing process division and resource allocation using the candidate draft; and an optimal solution selection unit that selects an optimal candidate using a predetermined evaluation index for each candidate of process design information.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a process planning device, a production line system, and a process planning method. [Background technology]

[0002] Patent Document 1 describes a design information generating device that generates process design information for a production system that manufactures products by machining target parts, the device comprising: a required operation information generating unit that generates required operation information indicating operations to be performed on the target parts to reach a target state based on geometric information, assembly information, and work process information of the product; a work constraint generating unit that determines at least one constraint condition of a position or an acting force of the target parts based on the geometric information, assembly information, and work process information to generate work constraint information; a work entity selecting unit that selects a plurality of work entities that satisfy both the required operation ability and the constraint condition for realizing the required operation information based on the required operation information, the work constraint information, and work entity information, and generates process design information including information of the selected plurality of work entities; and an evaluation unit that outputs evaluation information including information evaluating times related to target processes of the plurality of work entities based on the process design information, and the work entity selecting unit reselects a work entity based on the evaluation information and a request from user information. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] International Publication No. 2019 / 021938 Summary of the Invention [Problem to be solved by the invention]

[0004] The technology described in the above-mentioned Patent Document 1 is premised on the assumption that assembly information is given, and the optimal solution for process design depends on the assembly information and, in turn, on the equipment and workers that determine it, so it is difficult to reuse process information in an outsourcing environment, where equipment and workers tend to be diverse. In other words, in an outsourcing environment, finding an optimal solution requires data analysis and simulation calculations for a huge number of combinations, which is not practical.

[0005] An object of the present invention is to easily create a process plan that reduces operational costs. [Means for solving the problem]

[0006] In order to solve the above problem, the present application employs, for example, the means described in the claims. The present invention includes a plurality of means for solving the above problem, and an example thereof is a process planning device, characterized by comprising: a storage unit for storing product information of an assembly product, resource information of resources used in production, and part-resource combination information including constraints and capabilities of combinations of parts and the resources constituting the assembly product, an assembly sequence candidate generation unit for generating candidate proposals for the assembly sequence of the parts that satisfy the constraints and in accordance with priority criteria according to the resources, a line balancing unit for generating candidates for process design information by dividing processes and allocating resources using the candidate proposals, and an optimal solution selection unit for selecting an optimal candidate for each candidate for the process design information using a predetermined evaluation index. Effect of the Invention

[0007] According to the present invention, it is possible to provide a technique for easily creating a process plan with reduced operational costs.

[0008] Problems, configurations and effects other than those described above will become apparent from the following description of the embodiments. [Brief description of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram illustrating an example of the configuration of a production line system. [Diagram 2] FIG. 1 is a diagram showing an example of a product overview. [Diagram 3] FIG. 11 is a diagram illustrating an example of part adjacency information. [Figure 4] FIG. 11 is a diagram illustrating an example of part specification information. [Diagram 5] FIG. 13 is a diagram illustrating an example of a main resource specification. [Figure 6] FIG. 13 is a diagram illustrating an example of a sub-resource specification. [Figure 7] FIG. 13 illustrates an example of resource combination constraints. [Figure 8] FIG. 11 is a diagram illustrating an example of work time information. [Figure 9] FIG. 13 is a diagram illustrating an example of combination constraints. [Figure 10] FIG. 2 is a diagram illustrating an example of a hardware configuration of a process planning apparatus. [Figure 11] FIG. 13 is a diagram illustrating an example of a flow of a process design process. [Figure 12] FIG. 13 illustrates an example of a flow of a process for generating group order candidates for each resource. [Figure 13] FIG. 13 is a diagram showing an example of output of group order candidates. [Figure 14] FIG. 13 is a diagram illustrating an example of a flow of a group order candidate expansion process. [Figure 15] FIG. 13 is a diagram illustrating an example of expanding group order candidates. [Figure 16] FIG. 13 is a diagram showing an example of an assembly sequence candidate display screen. [Figure 17] FIG. 13 is a diagram showing an example of a comparative display screen of process design results. [Figure 18] FIG. 13 is a diagram showing an example of a detailed display screen of a process design result. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] In the following embodiments, for convenience, when necessary, the description will be divided into multiple sections or embodiments, but unless otherwise expressly stated, they are not unrelated to each other and one is a partial or complete variation, detail, supplementary explanation, etc. of the other.

[0011] In addition, in the following embodiments, when referring to the number of elements (including the number, numerical values, amounts, ranges, etc.), unless specifically stated or clearly limited to a specific number in principle, the number is not limited to that specific number and may be more than or less than the specific number.

[0012] Furthermore, it goes without saying that in the following embodiments, the components (including element steps, etc.) are not necessarily essential unless specifically stated otherwise or unless they are clearly considered essential in principle.

[0013] Similarly, in the following embodiments, when referring to the shapes, positional relationships, etc. of components, etc., unless otherwise specified or considered to be obviously different in principle, it includes those that are substantially similar or similar to the shapes, etc. The same applies to the above numerical values ​​and ranges.

[0014] In addition, in all the drawings for explaining the embodiments, the same components are generally given the same reference numerals, and the repeated explanations are omitted. However, when there is a high possibility of confusion occurring if the same components share the same names as the components before the change due to an environmental change, etc., different reference numerals or names may be given to the same components. Each embodiment of the present invention will be explained below with reference to the drawings.

[0015] Generally, the process design of an assembly line goes through the design processes of assembly sequence generation and line balancing. In the assembly sequence generation process, the process designer determines the sequence of work to assemble the parts that make up the target assembly product, taking into account the assembly information and, in turn, the equipment and workers that determine it. In line balancing, the process designer determines the process division that divides the assembly work into multiple processes and the resource configuration that determines the production resources that will be in charge of the processes.

[0016] The number of possible assembly sequences is up to the factorial of the number of parts. However, it is necessary to satisfy the geometric constraints of the parts based on the part adjacency relationships. For example, when assembling a fastening part such as a screw, the part to be fastened must be assembled first.

[0017] In process division, the process designer groups one or more tasks into a unit called a process in accordance with the assembly sequence. Since each process is performed in parallel by different production resources, the process with the longest operation time determines the takt time of the entire assembly line. In addition, non-operating time is minimized by reducing the variation in operation time of each process. However, the operation time of each process depends on the capacity of the production resource in charge of the process.

[0018] In resource configuration, the process designer determines the main resources, such as people and robots, who will be in charge of the work in each process. In addition, they determine sub-resources (dependent resources), such as jigs and tools and robot hands, depending on the work content. Using a main resource with high capabilities is expected to shorten the work time, but since the investment and operating costs are generally higher for a main resource with high capabilities, it is necessary to compare the operating costs of the entire process when planning the process.

[0019] In this embodiment, a process design device that realizes the generation of a process design for an assembly line that satisfies the target takt time of the assembly line and minimizes the operation cost will be described.

[0020] In addition, JP 2019-16165 A states that "the design support device includes a receiving unit that receives the sequence constraints for each task, the working time for each task, and whether or not the task can be performed by a robot for a product that requires multiple tasks for assembly; a first index calculation unit that calculates, for each task that cannot be performed by a robot, the number of consecutive tasks that can be performed by a robot when the task can be performed by a robot based on the sequence constraints and whether or not the task can be performed by a robot as a first index; a second index calculation unit that calculates, for each task that cannot be performed by a robot, the degree of freedom of placement when the task can be performed by a robot based on the sequence constraints, the working time, and whether or not the task can be performed by a robot as a second index; and a presentation unit that presents information based on the first index and the second index in association with the target tasks of the first index and the second index."

[0021] However, although the above-mentioned technology describes a technique for determining a work sequence based on the number of consecutive tasks performed by a robot and for allocating tasks to multiple robots, it does not take into account the hand replacement of a robot, which depends on the shape of the parts, or human workability, and therefore cannot generate an optimal work sequence assuming a mixed production line of humans and robots.

[0022] In an embodiment according to the present invention, when various resources are included in an assembly line, process design information is generated that reduces operational costs by combining a plurality of production resources such as people and robots.

[0023] In the following embodiments, the "input unit", "output unit", and "communication unit" may be one or more interface devices. The one or more interface devices may be at least one of the following: One or more I / O (Input / Output) interface devices. The I / O interface device is an interface device to at least one of the I / O device and a remote display computer. The I / O interface device to the display computer may be a communications interface device. The at least one I / O device may be a user interface device, e.g., either an input device such as a keyboard and a pointing device, or an output device such as a display device. One or more communication interface devices. The one or more communication interface devices may be one or more homogeneous communication interface devices (e.g., one or more NICs (Network Interface Cards)) or two or more heterogeneous communication interface devices (e.g., a NIC and an HBA (Host Bus Adapter)).

[0024] In the following description, a "memory" refers to one or more memory devices, which are an example of one or more storage devices, and may typically be a primary storage device. At least one memory device in the memory may be a volatile memory device or a non-volatile memory device.

[0025] In the following description, an "external storage device" may be one or more persistent storage devices, which are an example of one or more storage devices. The persistent storage device may typically be a non-volatile storage device (e.g., an auxiliary storage device), and more specifically, may be, for example, a hard disk drive (HDD), a solid state drive (SSD), a non-volatile memory express (NVME) drive, or a storage class memory (SCM).

[0026] In the following description, a "storage unit" or an "external storage device" may refer to either a memory or a persistent storage device, or both.

[0027] Also, in the following description, a "processing unit" or a "processor" may be one or more processor devices. The at least one processor device may typically be a microprocessor device such as a CPU (Central Processing Unit), but may also be other types of processor devices such as a GPU (Graphics Processing Unit). The at least one processor device may be a single-core or multi-core. The at least one processor device may be a processor core. The at least one processor device may also be a broader processor device such as a circuit that is a collection of gate arrays written in a hardware description language that performs part or all of the processing (e.g., a Field-Programmable Gate Array (FPGA), a Complex Programmable Logic Device (CPLD), or an Application Specific Integrated Circuit (ASIC)).

[0028] In the following description, functions may be described using the expression "yyy unit", but the functions may be realized by one or more computer programs being executed by a processor, or by one or more hardware circuits (e.g., FPGA or ASIC), or by a combination thereof. When a function is realized by a program being executed by a processor, the function may be at least a part of the processor, since the specified processing is performed using a storage device and / or an interface device, etc., as appropriate. Processing described with a function as the subject may be processing performed by a processor or a device having the processor. A program may be installed from a program source. The program source may be, for example, a program distribution computer or a computer-readable recording medium (e.g., a non-transitory recording medium). The description of each function is an example, and multiple functions may be combined into one function, or one function may be divided into multiple functions.

[0029] In the following description, a process may be described using a "program" or a "processing unit" as the subject, but a process described using a program as the subject may be a process performed by a processor or a device having the processor. Two or more programs may be realized as one program, and one program may be realized as two or more programs.

[0030] In the following description, information that provides an output for an input may be described using expressions such as "xxx table," but the information may be a table of any structure, or may be a neural network that generates an output for an input, or a learning model such as a genetic algorithm or random forest. Therefore, the "xxx table" may be referred to as "xxx information." In the following description, the structure of each table is an example, and one table may be divided into two or more tables, or all or part of two or more tables may be one table.

[0031] In the following description, a "production line system" may be a system composed of one or more physical computers, or may be a system (e.g., a cloud computing system) realized on a group of physical computing resources (e.g., a cloud platform). When the production line system "displays" display information, it may mean displaying the display information on a display device possessed by the computer, or the computer may transmit the display information to a display computer (in the latter case, the display information is displayed by the display computer).

[0032] 1 is a diagram showing an example of the configuration of a production line system. The production line system 1 is installed in a manufacturing site (area) or in a facility outside the manufacturing site. The production line system 1 includes a group of devices according to the usage environment, such as a display computer, which is communicatively connected via a network (not shown).

[0033] Although not shown, the network may be, for example, a local area network (LAN), a wide area network (WAN), a virtual private network (VPN), a communication network using a general public line such as the Internet in part or in whole, a mobile phone communication network, etc., or a combination of these. Note that the network may be a wireless communication network such as Wi-Fi (registered trademark) or 5G (Generation).

[0034] The process planning device 100 allocates work steps relating to the assembly of an assembly product on a production facility basis, or on a production resource basis in a work area that does not use production facilities.

[0035] 2 is a diagram showing an example of a product overview. The assembly product 200 is a product that is created by assembling a total of 10 parts onto a plate-shaped base part. In the assembly product 200, the parts are classified into two types: flat plates (P: Plate) and cylinders (C: Cylinder).

[0036] The process planning apparatus 100 includes a storage unit 110, a processing unit 120, a communication unit 130, an input unit 140, and an output unit 150. The storage unit 110 includes product information 111, resource information 112, part / resource combination information 113, and process design information 114. The product information 111 also includes part adjacency information 1111 and part specification information 1112.

[0037] FIG. 3 is a diagram showing an example of part adjacency information. The part adjacency information 1111 is an example of holding the part adjacency of the assembly product 200 as a precedence graph. The circles in the precedence graph represent parts and nodes, and the arrows connecting the nodes are edges that determine the assembly order of parts from the adjacency of the parts. The precedence graph is one of the methods of expressing constraints when determining the assembly order of parts. Nodes that are not in contact with the arrows of edges are disassembly parts. In the example of the part adjacency information 1111, parts with part IDs 5, 7, 9, and 10 are nodes that are disassembly possible in the initial state. For example, when the part 205C with part ID 5 is disassembled, there is no arrow in contact with the part with part ID 4, so the part with part ID 4 is also added to the candidates for disassembly.

[0038] After the disassembly order is determined, the reverse order can be used as the assembly order. The precedence graph information may be stored in a data structure using the DOT language. By having part adjacency relationships as product information 111, constraints in generating an assembly order can be expressed as data, and candidates for the assembly order can be narrowed down.

[0039] FIG. 4 is a diagram showing an example of part specification information. The part specification information 1112 is an example of holding the part configuration, part specifications, and part positional relationships of the assembly product 200 in a table format. As the part configuration, a part ID 1112a and the number 1112b of each part are stored. As the part specifications, a classification based on the shape of each part, that is, a part type 1112c, and a part weight 1112d are stored. As the part positional relationship, an attachment position 1112e of each part is stored. The attachment position 1112e represents the center position of each part in coordinates in the three axial directions of x, y, and z from the origin provided on the assembly product 200 as a reference point. Therefore, it is possible to calculate the distance between the parts.

[0040] The resource information 112 includes a main resource specification 1121 , a sub-resource specification 1122 , and a resource combination constraint 1123 .

[0041] 5 is a diagram showing an example of a main resource specification. The main resource specification 1121 is an example that defines candidates for a main resource that is responsible for the main assembly work in an assembly line and their specifications. The main resource specification 1121 includes a resource type 1121a, a resource name 1121b, a resource ID 1121c, a load capacity 1121d, an initial investment cost 1121e, a depreciation period 1121f, and a labor cost 1121g.

[0042] The resource type 1121a stores a predetermined type of main resource. When the resource type is a robot, the initial investment cost 1121e and the depreciation period 1121f can be set to calculate the depreciation cost during the usage period as part of the operation cost of the assembly line. When the resource type 1121a is a person, the labor cost 1121g can be set to calculate the labor cost according to the working time of the person as part of the operation cost of the assembly line.

[0043] The resource name 1121b is the name of the resource, but does not need to be a name that can identify an individual resource among resources with the same specifications. The resource ID 1121c is an identifier of the resource, and needs to be able to identify an individual resource. The load capacity 1121d is information that specifies the load that can be held when connecting to a sub-resource.

[0044] 6 is a diagram showing an example of a sub-resource specification. The sub-resource specification 1122 is an example that defines candidates for sub-resources that assist a main resource that is the main body of assembly work in an assembly line, and their specifications. The sub-resource specification 1122 includes a resource type 1122a, a resource name 1122b, a resource ID 1122c, a load capacity 1122d, an initial investment cost 1122e, and a weight 1122f.

[0045] A predetermined type of sub-resource is stored in the resource type 1122a. When the resource type is a robot hand, a load capacity 1122d, an initial investment cost 1122e, and a weight 1122f are set as indicators of the capability.

[0046] The resource name 1122b is the name of the resource, but does not need to be a name that can identify an individual resource among resources with the same specifications. Or, even if the resource type is a hand, if there are two types of hands with different specifications, the resource name must be able to identify both. The resource ID 1122c is an identifier of the resource and must be able to identify an individual resource. The load capacity 1122d is information that specifies the load that can be held when handling a part. The weight 1122f is the weight of the sub-resource itself that is required from the perspective of load capacity when connected to the main resource.

[0047] The relationship between the hand and the robot (i.e., the main resource connectable to the sub-resource) is defined separately by the resource combination constraint 1123 described later. Also, the relationship between the hand and the part handled by the hand is defined separately by the part-resource combination information 113 described later.

[0048] 7 is a diagram showing an example of a resource combination constraint. The resource combination constraint 1123 defines a main resource (combinable main resource 1123b) to which each hand can be connected, with a hand, which is a sub-resource, as a primary key (resource ID 1123a).

[0049] The parts and resource combination information 113 includes operation time information 1131, a combination constraint 1132, and combination constraint expressions (1) and (2) described below.

[0050] 8 is a diagram showing an example of operation time information. The operation time information 1131 is an example that defines the processing time when each main resource performs assembly for each part that constitutes an assembly product. The operation time information 1131 includes a part ID 1131a, a processing time (MR_Hu_01) 1131b, a processing time (MR_Ro_01) 1131c, a processing time (MR_Ro_04) 1131d, and a processing time (MR_Ro_05) 1131e.

[0051] For example, it is defined that a part with a part ID of 1 takes 12.0 seconds as defined in processing time (MR_Hu_01) 1131b when a human (MR_Hu_01) is in charge of the assembly work as a main resource, and takes 30.0 seconds as defined in processing time (MR_Ro_05) 1131e when a robot (MR_Ro_05) is in charge of the assembly work. Note that the operation time information 1131 may define an operation time for each candidate main resource as in the example shown in the figure, or may define a predetermined coefficient for a reference main resource (e.g., a human).

[0052] 9 is a diagram showing an example of a combination constraint. The combination constraint 1132 is an example of a combination constraint between part specifications and sub-resource specifications. The combination constraint 1132 defines the sub-resources that can handle each part (handleable sub-resources 1132b) using the part type 1132a as a primary key. Since the robot's hands that can handle the part differ depending on the shape of the part, the combination constraint needs to be satisfied. For example, a P-type part and a C-type part have different shapes of hands that can be grasped, so restrictions arise on the sub-resources that can be used depending on the part.

[0053] The relationship between parts and sub-resources may be defined individually for each part. Also, multiple sub-resources may be defined as combination candidates for one part or shape. As in the example of Fig. 9, if combination constraints can be defined for part attributes such as part types, rather than for parts specific to the target product, it is possible to store them in advance in the storage unit 110 of the process planning apparatus 100 as information common to process design.

[0054] In addition to these, combination constraints are held in the form of mathematical expressions in the part / resource combination information 113. Such combination constraint expressions (1) and (2) will be described below.

[0055] MR WC > (SR W +P W ) ×α MR ...Equation (1)

[0056] The above formula (1) is an example of a combination constraint of parts and main resources. In formula (1), MR WC The main resource has a load capacity of 1121d, SR W is the weight of the sub-resource 1122f, P W is the weight of the part 1112d, α MR is the safety factor of the main resource.

[0057] In the above formula (1), in a task in which a sub-resource hand is attached to a robot (main resource) and a part with a shape that the hand can handle is to be grasped, the constraint formula is defined as the sum of the hand weight and the part weight multiplied by the safety factor of the main resource being equal to or less than the load capacity of the main resource. When selecting a main resource for this task, it is necessary to select a main resource that satisfies the constraint of formula (1).

[0058] S.R. WC > P W ×α SR ...Equation (2)

[0059] The above formula (2) is an example of a combination constraint of parts and sub-resources. In formula (2), SR WC The load capacity of the sub-resource is 1122d, P W is the weight of the part 1112d, α SR is the safety factor of the sub-resource.

[0060] In the above formula (2), in a task in which a sub-resource hand is attached to a robot that is a main resource and the hand needs to grip a part with a shape that the hand can handle, the constraint formula is defined such that the part weight multiplied by the safety factor of the sub-resource is equal to or less than the load capacity of the sub-resource. In selecting a sub-resource for the task, it is necessary to select a sub-resource that satisfies the constraint of formula (2) in addition to the constraint of the combination constraint 1132.

[0061] The process design information 114 stores an assembly sequence, information on the process that divides the assembly sequence, main resources and sub-resources used in each process, and the operation costs incurred by the processes, in association with each other.

[0062] Returning to the explanation of Fig. 1, the processing unit 120 includes an assembly sequence candidate generating unit 121, an assembly sequence candidate expanding unit 122, a line balancing unit 123, and an optimal solution selecting unit .

[0063] The assembly sequence candidate generating unit 121 generates candidate proposals for the assembly sequence of parts, satisfying various constraints and in accordance with priority criteria according to resources. Note that the assembly sequence candidate generating unit 121 prioritizes maintaining the quality of assembly work by workers as a priority criterion related to a worker resource, and prioritizes reducing the number of times hand members are replaced as a priority criterion related to a robot, which is a main resource that can replace hand members, which are sub-resources.

[0064] For example, the assembly sequence candidate generating unit 121 may assemble parts in order of proximity to the installation positions as a priority criterion according to the resource, that is, the worker.

[0065] The assembly order candidate expansion unit 122 generates new candidate proposals for the assembly order of the parts by combining the generated candidates for the assembly order of the parts. Specifically, the assembly order candidate expansion unit 122 divides each of the generated candidates for the assembly order of the parts into processes so that the total of the work time included in each process is equalized, and generates new candidate proposals for the assembly order of the parts by combining the divided processes among the candidates for the assembly order of the parts.

[0066] A specific example of leveling is that the assembly sequence candidate expansion unit 122 divides the parts into processes based on the part working time and the target takt time, and combines the divided processes among the part assembly sequence candidates to generate new part assembly sequence candidates. Alternatively, the assembly sequence candidate expansion unit 122 may determine the maximum and minimum number of process divisions using the target takt time for each of the multiple part assembly sequence candidates generated, divide the parts into processes so that the process divisions fall between the maximum and minimum numbers, and combine the divided processes among the part assembly sequence candidates to generate new part assembly sequence candidates.

[0067] The line balancing unit 123 performs process division and resource allocation using the candidate plans to generate candidates for process design information.

[0068] The optimum solution selection unit 124 selects the optimum candidate for each candidate of the process design information by using a predetermined evaluation index.

[0069] The communication unit 130 transmits and receives various types of information to and from other devices via the network.

[0070] The input unit 140 receives input information that is displayed and operated on a screen, for example, and is input by operating a keyboard or a mouse.

[0071] The output unit 150 creates screen information including information to be output as a result of performing a predetermined process, for example, and outputs the screen information to the display computer via the communication unit 130.

[0072] 10 is a diagram showing an example of the hardware configuration of the process planning apparatus. The process planning apparatus 100 can be realized by a general computer 900 including a processor (e.g., a CPU or a GPU) 901, a memory 902 such as a RAM (Random Access Memory), an external storage device 903 such as a hard disk drive (HDD) or SSD, a reading device 905 for reading information from a portable storage medium 904 such as a CD or a DVD, an input device 906 such as a keyboard, a mouse, a barcode reader, or a touch panel, an output device 907 such as a display, and a communication device 908 for communicating with other computers via a communication network such as a LAN or the Internet, or a network system including a plurality of such computers 900. It goes without saying that the reading device 905 may be capable of not only reading but also writing to the portable storage medium 904.

[0073] For example, the assembly sequence candidate generating unit 121, the assembly sequence candidate expanding unit 122, the line balancing unit 123, and the optimal solution selecting unit 124 included in the processing unit 120 can be realized by loading a predetermined program stored in an external storage device 903 into the memory 902 and executing it by the processor 901, the input unit 140 can be realized by the processor 901 using the input device 906, the output unit 150 can be realized by the processor 901 using the output device 907 or the communication device 908, the communication unit 130 can be realized by the processor 901 using the communication device 908, and the storage unit 110 can be realized by the processor 901 using the memory 902 or the external storage device 903.

[0074] This predetermined program may be downloaded to the external storage device 903 from the portable storage medium 904 via the reading device 905 or from a network via the communication device 908, and then loaded onto the memory 902 and executed by the processor 901. Alternatively, the program may be directly loaded onto the memory 902 from the portable storage medium 904 via the reading device 905 or from a network via the communication device 908, and then executed by the processor 901.

[0075] 11 is a diagram showing an example of the flow of the process design process. The process design process is started when a start instruction is received from a user via an interface device.

[0076] First, the input unit 140 accepts input of the target takt time of the assembly line for which process design is to be performed (step S001). All subsequent processes are executed to meet the target takt time set here. If the assembly line is made up of multiple processes, the maximum value of the takt time of each process becomes the takt time of the entire assembly line. In other words, the takt time of the assembly line coincides with the takt time of the bottleneck process.

[0077] Then, the input unit 140 receives an input of product information (step S002). The received product information is stored in the product information 111. The product information 111 is defined and stored for each assembled product that is the subject of the process design.

[0078] Then, the input unit 140 accepts the input of resource information (step S003). The accepted resource information is stored in the resource information 112. The resource information 112 is defined and stored for each assembly product that is the subject of the process design. Alternatively, the resource information 112 may be stored in advance in the storage unit 110 of the process planning apparatus 100 as information common to the process design regardless of the subject of the process design. Furthermore, a selection input may be accepted as the specified resource information from the pre-stored information.

[0079] Then, the input unit 140 accepts an input of parts and resource combination information (step S004). The accepted parts and resource combination information is stored in the parts and resource combination information 113. The parts and resource combination information 113 is defined and stored for each process design target. Alternatively, the parts and resource combination information 113 may be stored in advance in the storage unit 110 of the process planning apparatus 100 as information common to process design regardless of the process design target. Furthermore, a selection input may be accepted as specified resource information from the pre-stored information.

[0080] Then, the assembly order candidate generating unit 121 generates assembly order candidates using each piece of information that has been received as input (step S005). The generation of assembly order candidates is roughly divided into a process of generating candidate assembly orders for each resource (step S0051) and a process of expanding candidate assembly orders (step S0052).

[0081] First, the process of generating candidate assembly sequences for each resource (step S0051) will be described. Since there are a maximum of factorial number of candidate assembly sequence solutions for the number of parts, if subsequent line balancing is calculated for all candidate assembly sequence solutions, the number of combinations will be enormous, making it difficult to realize. Therefore, the process designer defines assembly sequence generation rules for each resource based on the impact that the shape and arrangement of parts have on assembly time and quality. These rules are incorporated as algorithms into the process of generating candidate assembly sequences (step S0051). Alternatively, when the process of generating candidate assembly sequences (step S0051) is implemented on a rule-based basis, they are implemented as rules. Here, an example is shown in which a rule that uses robots and people as resources is incorporated as an algorithm.

[0082] Robots need to change hands to grip parts according to their shape, and in addition to the assembly work time, additional setup time is required, including the time to change hands. On the other hand, for part placement, if it is within the robot's operating range, the precision of the repetitive motion is high and the impact on quality is small. Therefore, as an assembly sequence generation rule when using robots as the main resource, the number of times that hands need to be changed due to differences in the shapes of parts handled in the previous and next sequences is measured and minimized.

[0083] Humans can flexibly respond to changes in part shapes. On the other hand, working continuously on parts that are spatially close allows people to maintain their concentration and maintain high quality. Therefore, the assembly sequence generation rule when humans are the main resource is to measure and minimize the amount of change in part positions.

[0084] Alternatively, assembly sequence generation rules may be established by further subdividing people and robots as types of candidate resources. For example, since it is believed that the characteristics of people change depending on age and experience, the assembly sequence generation rules may also be subdivided accordingly. Also, for robots, the assembly sequence generation rules may be subdivided according to the number of controlled axes and size. Furthermore, when there are candidate resources other than people and robots (such as dedicated machines), the assembly sequence generation rules may be defined individually.

[0085] In the process of generating candidate assembly sequences for each resource, the assembly sequence candidate generating unit 121 generates candidate assembly sequences for each resource using such assembly sequence generation rules. Note that, when there are multiple assembly sequence candidates that satisfy the assembly sequence generation rules, the assembly sequence candidate generating unit 121 may compare the candidates and select them based on another index.

[0086] For example, as an assembly sequence generation rule when a robot is used as the main resource, the number of times that hand exchanges are required due to different shapes of parts handled in the previous and next sequences is measured and minimized. When an assembly sequence that results in the same number of hand exchanges is derived, the assembly sequence candidate generation unit 121 may measure the amount of change in the positions of parts between the assembly sequences and select the one that minimizes the amount of change as a candidate assembly sequence. Alternatively, a rule for narrowing down the assembly sequence candidates using such multiple evaluation indexes may be provided in advance. Details of the assembly sequence candidate generation process will be described later.

[0087] Next, we will explain the assembly sequence candidate expansion process. Assembly sequence candidates optimized for humans and robots are not necessarily optimal in an environment that requires multiple resource combinations. Therefore, it is possible to generate assembly sequence candidates that assume a mixed human and robot production line environment based on assembly sequence candidates optimized for humans and robots.

[0088] As an example of the process for expanding the candidate assembly orders (step S0052), a process for expanding the candidate assembly orders by crossing the candidates for the assembly orders for each resource will be described. This process divides the candidate assembly orders generated in the process for generating candidate assembly orders for each resource into multiple subelements, crosses and combines the divided elements, and removes overlapping work, thereby generating additional candidate assembly orders that assume combinations of multiple resources. Note that the process for expanding the candidate assembly orders by crossing is just one example, and new candidates may be added by using a genetic algorithm or the like.

[0089] In the process of extending the assembly order candidates by crossover, for example, when there are assembly order candidates X, Y, and Z for each resource, one additional candidate is generated by making the first process of X a successor to the process of Y and then making the process of Z a successor, and removing the second and subsequent identical operations. Similarly, an additional candidate can be generated by making the first process of X a successor to the process of Y and removing the second and subsequent identical operations (without using the candidate of Z). Alternatively, an additional candidate can be generated by making the first process of Y a successor to the process of Z and then making the process of X a successor, and removing the second and subsequent identical operations. The assembly order candidate extension unit 122 generates variations by combining X, Y, and Z in this way. Details of the assembly order candidate extension process will be described later.

[0090] Then, the line balancing unit 123 initializes a variable N (N is an integer) for selecting a candidate for the generated assembly sequence, and sets N=1 (step S006).

[0091] Then, the line balancing unit 123 selects the Nth candidate from the generated assembly sequence candidates (step S007).

[0092] Then, the line balancing unit 123 inputs the selected assembly order candidate N and generates a line balancing solution that satisfies the target takt time set in step S001 (step S008). Line balancing is roughly divided into a process division process for the assembly order candidate N (step S0081) and a resource allocation process (step S0082).

[0093] First, the process division process (step S0081) will be described. The line balancing unit 123 divides the selected assembly sequence candidate N into a plurality of processes. At this time, the number of process divisions is set to the maximum process division number C max and the minimum value C min The maximum number of divisions of the process is C. max and the minimum value C min are calculated using equations (3) and (4) based on the takt time, which will be described later.

[0094] Each process requires its own main resource, and since the cost of the main resource dominates the line operation cost, it is required to divide the process into as few processes as possible. Therefore, the line balancing unit 123 divides the processes by giving priority to the smallest number of divisions. The division may be performed using the equalization of the time for each process as an evaluation index. However, the exact working time for each process can be calculated only after the resources are allocated.

[0095] Next, the resource allocation process (step S0082) will be described. The line balancing unit 123 allocates a main resource suitable for each divided process. Furthermore, based on the part-resource combination information 113, a sub-resource is allocated to each part as necessary. For example, when a robot is allocated as a main resource, a hand according to the shape of the part needs to be allocated as a sub-resource.

[0096] The work time of each process is calculated based on the work time and setup time of each part. The line balancing unit 123 calculates the work time of each part according to the main resource assigned to each part. In addition, the line balancing unit 123 calculates the setup time as the required additional time when a sub-resource needs to be replaced within a process.

[0097] If the process design solution does not satisfy the target takt time, the line balancing unit 123 repeatedly executes different process division processes and resource allocation processes until a process design solution that satisfies the target takt time is generated. As an example of regenerating the process division, the line balancing unit 123 may regenerate the process division by maintaining the division number and moving some of the parts of the process that exceeds the target takt time to an adjacent process. The line balancing unit 123 may also change the process division number to generate a new division plan.

[0098] When a process design solution that satisfies the target takt time is generated, the line balancing unit 123 stores the process design solution in the process design information 114. By generating all process division plans for the selected assembly sequence candidate and performing optimal resource allocation for each process division plan, it is possible to derive an optimal process design solution for the selected assembly sequence candidate N. In addition, the calculation time may be set as a threshold value, and the line balancing unit 123 may derive the best solution that can be reached within the time as the process design solution.

[0099] Once the resource allocation for each process has been determined, the operating costs of the assembly line can be calculated. For robots as main resources and sub-resources, the line balancing unit 123 calculates the operating costs for the relevant work period for each process design solution using the initial investment cost and depreciation period. For people as main resources, the line balancing unit 123 calculates the operating costs using labor costs.

[0100] Then, the line balancing unit 123 judges whether or not all the generated assembly sequence candidates have been processed (step S009). If unprocessed candidates remain (step S009: No), the line balancing unit 123 adds 1 to the variable N (step S010), returns control to step S007, and selects the next assembly sequence candidate.

[0101] When all grouping order candidates have been processed ("Yes" in step S009), the optimal solution selection unit 124 selects a process design solution with the smallest operating cost (step S011) and ends the process design process. In step S011, the optimal solution selection unit 124 may select a solution using an evaluation formula other than the operating cost (for example, the initial investment cost). In addition, the optimal solution selection unit 124 may display a list of the results and accept a user's input to select a solution.

[0102] The above is an example of the flow of the process design process. According to the process design process, a process plan that can reduce operation costs can be easily created.

[0103] 12 is a diagram showing an example of a flow of a process for generating group order candidates for each resource. The process for generating group order candidates for each resource is performed in step S0051 of the process design process.

[0104] First, the assembly order candidate generating unit 121 selects one (resource candidate R) from the main resource candidates included in the resource information 112 (step S0511). For example, in the case of the main resource specification 1121, the assembly order candidate generating unit 121 selects a resource whose resource ID 1121c, which is data at the beginning of the line, is MR_Ro_01 as the resource candidate R.

[0105] Then, the assembly sequence candidate generating unit 121 determines whether or not the type of the selected resource candidate R is a robot (step S0512). Specifically, the assembly sequence candidate generating unit 121 determines whether or not the resource type 1121a of the selected resource candidate R is a robot.

[0106] If the type of the selected resource candidate R is a robot (Yes in step S0512), the assembly sequence candidate generating unit 121 generates an assembly sequence that minimizes the number of hand exchanges defined as an assembly sequence generation rule for a robot (step S0513). The necessity of hand exchange can be determined using the combination constraint 1132 for each timing when the part type in the assembly sequence of parts is changed.

[0107] If the type of the selected resource candidate R is not a robot (No in step S0512), the assembly sequence candidate generating unit 121 generates an assembly sequence that minimizes the amount of part position change defined as a manual assembly sequence generation rule (step S0514). The amount of part position change can be calculated using the part specification information 1112 and the distance of the mounting position 1112e.

[0108] Then, the assembly sequence candidate generating unit 121 stores the assembly sequence generated in step S0513 or step S0514 as a candidate in the process design information 114 (step S0515).

[0109] Then, the assembly sequence candidate generating unit 121 judges whether all main resource candidates in the resource information 112 have been processed (step S0516). If unprocessed candidates remain ("No" in step S0516), the assembly sequence candidate generating unit 121 returns control to step S0511 and selects the next resource candidate. If all candidates have been processed ("Yes" in step S0516), the assembly sequence candidate generating unit 121 ends the assembly sequence candidate generation process for each resource.

[0110] The above is an example of the flow of the processing for generating group order candidates for each resource. According to the processing for generating group order candidates for each resource, it is possible to generate group order candidates suitable for the resources.

[0111] 13 is a diagram showing an example of an output of an assembly sequence candidate. The figure shows an example of an assembly sequence generated by applying a human assembly sequence generation rule that minimizes the amount of change in part position to an assembly product 200, and an example of an assembly sequence generated by applying a robot assembly sequence generation rule that minimizes the number of hand exchanges. It can be said that the assembly sequence generated by applying the human assembly sequence generation rule is efficient by focusing on the positions of the parts, while the assembly sequence generated by applying the robot assembly sequence generation rule is efficient by focusing on the consecutive handling of parts of the same type, rather than the positions of the parts.

[0112] 14 is a diagram showing an example of the flow of the grouping order candidate expansion process, which is performed in step S0052 of the process design process.

[0113] First, the assembly sequence candidate expansion unit 122 calculates the maximum number of process divisions (C max ), minimum value (C min ) is calculated (step S0521). Here, an example is shown in which the calculation is performed using the work time of each part and the target takt time.

[0114] Maximum number of process divisions (C max) can be calculated using the following formula (3), assuming that hand changes occur for all parts using the slowest resource for each part.

[0115] C max =Roundup(Σ(OT(max)i+CT) / T)...Equation (3)

[0116] The minimum number of process divisions (C min ) is the fastest resource for each part, and can be calculated using the following formula (4) assuming that there is no hand change.

[0117] C min =Roundup(Σ(OT(min)i / T)...Equation (4)

[0118] In the above equations (3) and (4), Roundup() is a function that rounds up the decimal points of the parameters to integers, OT(max)i is the operation time (longest operation time) when the slowest resource is selected for part i, OT(min)i is the operation time (shortest operation time) when the fastest resource is selected for part i, CT is the tool change time, and T is the target takt time.

[0119] Then, the assembly sequence candidate expanding unit 122 selects one of the assembly sequence candidates generated by the assembly sequence candidate generating unit 121 and stored in the process design information 114 (step S0522). The assembly sequence candidate selected here is set as an assembly sequence candidate I.

[0120] Then, the assembly sequence candidate expansion unit 122 calculates the maximum process division value (C max ) to the minimum value (C min ), and divides the selected assembly sequence candidate I into the selected process division number C (step S0523). Here, the assembly sequence candidate expansion unit 122 may divide the processes so that the total of the operation times included in each process is equalized.

[0121] Then, the assembly sequence candidate expansion unit 122 combines the first process of the assembly sequence candidate I with other assembly sequence candidates, and deletes the operations of overlapping parts (step S0524). That is, after combining other assembly sequence candidates with the divided partial solution of the assembly sequence candidate I, the parts included in the first partial solution overlap with the latter assembly sequence candidates, so by deleting the overlaps, crossover is established, and a new assembly sequence candidate is generated.

[0122] In expanding the assembly order candidates by crossover, the assembly order candidate expanding unit 122 may randomly combine and cross over partial solutions. Also, the assembly order candidate expanding unit 122 may generate new assembly order candidates by randomly combining partial solutions of not only two assembly order candidates but also three or more assembly order candidates.

[0123] If the generated assembly sequence candidate is different from the assembly sequence candidates generated so far, the assembly sequence candidate expanding unit 122 registers it as an additional candidate in the process design information 114 (step S0525).

[0124] Then, the assembly sequence candidate expanding unit 122 judges whether or not candidates for all process division numbers C have been processed (step S0526). If unprocessed candidates for the process division number C remain ("No" in step S0526), ​​the assembly sequence candidate expanding unit 122 returns the control to step S0523 and selects another process division number C to divide the assembly sequence candidate I.

[0125] If all process division numbers C have been processed ("Yes" in step S0526), ​​the assembly order candidate expansion unit 122 judges whether all assembling order candidates I have been processed (step S0527). If unprocessed assembling order candidates remain ("No" in step S0527), the assembly order candidate expansion unit 122 returns control to step S0522 and selects another assembling order candidate I. If all assembling order candidates have been processed ("Yes" in step S0527), the assembly order candidate expansion unit 122 ends the assembling order candidate expansion process.

[0126] The above is an example of the flow of the candidate grouping order extension process. The candidate grouping order extension process makes it possible to generate candidate grouping orders suitable for combinations of resources.

[0127] 15 is a diagram showing an example of extending the assembly order candidates. For the assembly product 200, an example of process division in step S0523 is candidate X when humans are used as resources, and candidate Y when robots are used as resources. The assembly order candidates for humans and robots are each divided into three processes. Here, the candidate for the assembly order for humans is candidate X, and the candidate for the assembly order for robots is candidate Y.

[0128] In extended candidate X×Y, the beginning of the partial solution of candidate X is combined with the entire candidate Y, and because the parts (1P, 2C, 3P, 4P) included in the beginning of the partial solution of candidate X overlap with candidate Y, the overlapping operations are deleted from candidate Y to generate a new assembly sequence candidate. In addition, in extended candidate Y×X, the beginning of the partial solution of candidate Y is combined with the entire candidate X, and because the parts (1P, 6P, 8P) included in the beginning of the partial solution of candidate Y overlap with candidate X, the overlapping operations are deleted from candidate X to generate a new assembly sequence candidate.

[0129] In this way, by crossing the subelements of the candidate orderings generated for each resource candidate, it is possible to generate additional candidate orderings that assume combinations of multiple resources. This increases the number of candidates for subsequent line balancing near the optimal solution, making it possible to derive a more optimal solution.

[0130] 16 is a diagram showing an example of an assembly sequence candidate display screen. An example 1200 of the assembly sequence candidate display screen shows that a plurality of assembly sequence candidates have been generated. Specifically, the example 1200 of the assembly sequence candidate display screen shows that, for each assembly sequence candidate, the assembly sequence, the calculation unit that generated it, and the selected resource are associated and displayed. Note that, for the selected resource candidates generated by the assembly sequence candidate generating unit 121 for each resource candidate, the resource candidate selected during the calculation, i.e., the assembly sequence generation rule used, is displayed.

[0131] FIG. 17 is a diagram showing an example of a comparative display screen of process design results. The comparative display screen example 1300 of process design results includes a pull-down menu 1301 for selecting the display order of the results, an evaluation index graph 1302, and a process detail display button 1303. The pull-down menu 1301 accepts the selection of a predetermined criterion for the display order of process design results. The evaluation index graph 1302 is a graph with an evaluation index selected in the pull-down menu 1301 such as operation cost on the vertical axis and an assembly sequence ID on the horizontal axis, and a graph such as a bar graph of index value is displayed so that the process design results can be compared for each assembly sequence of the process design. In the evaluation index graph 1302, when the evaluation index is operation cost, the bar graph also displays the breakdown such as labor cost and cost depreciation. When the process detail display button 1303 accepts an input, it transitions to an example of a detailed display screen 1400 of process design results described later for the assembly sequence ID selected in the evaluation index graph 1302.

[0132] 18 is a diagram showing an example of a detailed display screen of the process design result. An example 1400 of the detailed display screen of the process design result includes a group sequence ID display 1401 of the target for which details are displayed, a process design information display 1402 of the process division and resource configuration, i.e., the result of line balancing, and an operation cost display 1403.

[0133] The process design information display 1402 displays, for example, process design information with a group sequence ID of 3. The process is divided into three, and a person (MR_Hu_01) is assigned as the main resource to the first process, and a robot (MR_Ro_01) is assigned to the second and third processes. In addition, the parts (part IDs are 6, 8, and 9, respectively) in the second process are all of type P (flat plate: Plate), so a flat plate compatible hand (SR_Ha_02) is assigned as the corresponding sub-resource. Similarly, the parts (part IDs are 7, 10, and 5, respectively) in the third process are all of type C (cylinder: Cylinder), so a cylinder compatible hand (SR_Ha_01) is assigned as the corresponding sub-resource.

[0134] In the operation cost display 1403, depreciation costs and labor costs in a predetermined period (for example, one month) when the processes are carried out according to the grouping order are displayed.

[0135] The above is the configuration of the production line system 1 according to this embodiment. The production line system 1 makes it possible to create a process design that minimizes operational costs in a short time without relying on the know-how of engineers and eliminating rework. In other words, it is possible to easily create a process plan that reduces operational costs.

[0136] In the above technology, an example is shown in which a person, who is a main resource, does not have a sub-resource, but this is not limited to the above. For example, by setting a jig as a sub-resource and setting the load capacity of the person, it becomes possible to allocate resources including sub-resources in the same way as the robot in this example.

[0137] The above-described embodiment has been described in detail to clearly explain the present invention, and is not necessarily limited to having all of the configurations described. It is possible to replace a part of the configuration of the embodiment with another configuration. It is also possible to delete a part of the configuration of the embodiment.

[0138] In addition, the above-mentioned units, configurations, functions, processing units, etc. may be realized in part or in whole by hardware, for example, by designing them as integrated circuits. In addition, the above-mentioned units, configurations, functions, etc. may be realized in software by a processor interpreting and executing a program that realizes each function. Information such as the program, table, file, etc. that realizes each function can be stored in a memory, a recording device such as a hard disk, or a storage medium such as an IC card, an SD card, or a DVD.

[0139] The control lines and information lines in the above-described embodiment 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 may be considered that almost all the components are connected to each other. The present invention has been described above with a focus on the embodiment. [Explanation of symbols]

[0140] 1: production line system, 100: process planning device, 110: memory unit, 111: product information, 112: resource information, 113: part / resource combination information, 114: process design information, 120: processing unit, 121: assembly sequence candidate generation unit, 122: assembly sequence candidate expansion unit, 123: line balancing unit, 124: optimal solution selection unit, 130: communication unit, 140: input unit, 150: output unit, 1111: part adjacency information, 1112: part specification information, 1121: main resource specification, 1122: sub-resource specification, 1123: resource combination constraint, 1131: work time information, 1132: combination constraint.

Claims

1. a storage unit that stores product information of an assembly product, resource information of resources used in production, and part / resource combination information including constraints and capabilities of combinations of parts and the resources that constitute the assembly product; an assembly sequence candidate generating unit that generates a candidate proposal for an assembly sequence of the parts according to a priority criterion that satisfies the constraints and corresponds to the resources; a line balancing unit that performs process division and resource allocation using the candidate plan to generate candidates for process design information; an optimal solution selection unit that selects an optimal candidate for each candidate of the process design information by using a predetermined evaluation index; A process planning device comprising:

2. 2. The process planning apparatus according to claim 1, the assembly sequence candidate generation unit sets the priority criterion for the resource being a worker to prioritize maintaining quality of assembly work by the worker; A process planning device comprising:

3. 2. The process planning apparatus according to claim 1, the assembly sequence candidate generation unit prioritizes reducing the number of times the hand member is replaced as the priority criterion according to the robot capable of replacing the hand member as the resource; A process planning device comprising:

4. 2. The process planning apparatus according to claim 1, the product information includes an installation position for each part of the assembly product; the assembly sequence candidate generation unit determines, as the priority criterion according to the resource being a worker, that the parts are assembled in order of proximity to each other in the installation position of the parts; A process planning device comprising:

5. 2. The process planning apparatus according to claim 1, The part-resource combination information includes the constraints modeled by a table and a constraint expression. A process planning device comprising:

6. 2. The process planning apparatus according to claim 1, an assembly sequence candidate expansion unit that divides each of the generated candidate plans for the assembly sequence of the parts into processes so as to equalize the total working time included in each process, and combines the divided processes among the candidate plans for the assembly sequence of the parts to generate new candidate plans for the assembly sequence of the parts; A process planning device comprising:

7. 2. The process planning apparatus according to claim 1, an assembly sequence candidate expansion unit that divides each of the generated candidate plans for the assembly sequence of the parts into processes based on the work time of each part and the target takt time so as to equalize the total work time included in each process, and combines the divided processes among the candidate plans for the assembly sequence of the parts to generate new candidate plans for the assembly sequence of the parts; A process planning device comprising:

8. 2. The process planning apparatus according to claim 1, an assembly sequence candidate expansion unit that uses a target takt time to determine a maximum number and a minimum number of process divisions for each of the generated assembly sequence candidates for the parts, divides the process into processes so that the process divisions fall between the maximum number and the minimum number, and combines the divided processes among the assembly sequence candidates for the parts to generate new assembly sequence candidates for the parts; A process planning device comprising:

9. 2. The process planning apparatus according to claim 1, an assembly sequence candidate expansion unit that generates a new candidate for the assembly sequence of the parts by combining the generated candidate for the assembly sequence of the parts; A process planning device comprising:

10. A production line system using a process planning device, The process planning device includes: a storage unit that stores product information of an assembly product, resource information of resources used in production, and part / resource combination information including constraints and capabilities of combinations of parts constituting the assembly product and the resources; and a processor; The processor, an assembly sequence candidate generating step of generating a candidate for an assembly sequence of the parts according to a priority criterion that satisfies the constraints and corresponds to the resources; a line balancing step of dividing processes and allocating resources using the candidate plans to generate candidates for process design information; an optimal solution selection step of selecting an optimal candidate for each candidate of the process design information by using a predetermined evaluation index; A production line system comprising:

11. A process planning method using a process planning device, The process planning device includes: a storage unit that stores product information of an assembly product, resource information of resources used in production, and part / resource combination information including constraints and capabilities of combinations of parts of the assembly product and the resources; and a processor; The processor, an assembly sequence candidate generating step of generating a candidate for an assembly sequence of the parts according to a priority criterion that satisfies the constraints and corresponds to the resources; a line balancing step of dividing processes and allocating resources using the candidate plans to generate candidates for process design information; an optimal solution selection step of selecting an optimal candidate for each candidate of the process design information by using a predetermined evaluation index; A process planning method comprising the steps of:

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