WO2016009483A1 - Assembly line organizing system and assembly line organizing method - Google Patents

Assembly line organizing system and assembly line organizing method Download PDF

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Publication number
WO2016009483A1
WO2016009483A1 PCT/JP2014/068732 JP2014068732W WO2016009483A1 WO 2016009483 A1 WO2016009483 A1 WO 2016009483A1 JP 2014068732 W JP2014068732 W JP 2014068732W WO 2016009483 A1 WO2016009483 A1 WO 2016009483A1
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WIPO (PCT)
Prior art keywords
assembly
automation
information
assembly line
cost
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PCT/JP2014/068732
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French (fr)
Japanese (ja)
Inventor
裕美子 上野
大毅 梶田
大輔 堤
雄太 山内
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株式会社日立製作所
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Priority to PCT/JP2014/068732 priority Critical patent/WO2016009483A1/en
Publication of WO2016009483A1 publication Critical patent/WO2016009483A1/en

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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/04—Manufacturing
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/30—Computing systems specially adapted for manufacturing

Definitions

  • the present invention relates to an assembly line knitting system and an assembly line knitting method for determining assembly line knitting using a computer.
  • the production number and production bases by production experts such as production technology Determine the process division and resource type of each process (whether manual assembly or automation, etc.), calculate the number of required workers and the number of necessary equipment, and determine the line organization. There was a way to do it.
  • Patent Document 2 As a method for minimizing the capital investment when an increase in production capacity is required, there are a facility personnel plan planning device and a planning method for realizing a production plan as described in Patent Document 2. This is because the relationship between the amount of investment and production capacity that has been quantitatively expanded and the relationship between the amount of investment and production capacity that has been qualitatively improved are memorized for the production capacity enhancement method that was performed in the past, and the target production For the production capacity of the line, the amount of investment for quantitative expansion and the timing of its investment and the amount of investment for qualitative improvement and its timing of investment are calculated so that the recurring costs required for product production are minimized.
  • the production line planning support apparatus and the production line planning support method described in Patent Document 1 have an effect of reducing capital investment for a predetermined automated process, but include manual / automated judgment of each process. Therefore, there is no effect of reducing the assembly cost and the assembly cost as the sum of the labor cost and the capital investment.
  • the equipment personnel planning device and the planning method for realizing the production plan described in Patent Document 2 is a method for minimizing the total of labor cost and capital investment. Because it is based on (automated judgment), it is not possible to calculate a line organization with the minimum assembly cost including manual / automated judgment of each process.
  • the product in order to solve the above-described problems and reduce the assembly cost as the sum of the labor cost and the capital investment, the product is configured when determining the line organization including the manual / automated judgment of the process.
  • an assembly line knitting system and an assembly line knitting method capable of automatically calculating a line knitting with a minimum assembly cost including manual / automated judgment of each process based on a plurality of parts information.
  • a system for knitting an assembly line for assembling a product to be assembled includes a calculation unit, a storage unit, an input unit, and an output unit.
  • the information acquisition unit that acquires the 3D CAD information and production conditions of the assembly target product stored in the storage unit, and the assembly based on the 3D CAD information of the assembly target product acquired by the information acquisition unit and the production condition of the assembly target product
  • An assembly process generation unit for creating a process an assembly automation determination unit for determining whether automation is possible in the assembly process created by the assembly process generation unit, and an assembly work time of the assembly target product in the assembly process created by the assembly process generation unit Generates multiple automation plans by combining the automatic operation and manual switching for the processes determined as possible by the assembly work time calculation unit and the assembly automation determination unit.
  • An assembly line organization generation unit, and an assembly cost calculation unit that calculates an assembly cost by calculating the number of required workers and the number of necessary facilities in the assembly line for a plurality of automation plans generated by the assembly line organization generation unit,
  • the output unit is configured to output assembly cost information for a plurality of automation plans calculated by the calculation unit.
  • the present invention acquires 3D CAD information and production conditions of an assembly target product in a method of knitting an assembly line for assembling the assembly target product.
  • the assembly cost is calculated, and information on the assembly cost for the plurality of calculated automation plans is output.
  • the present invention creates an assembly process based on 3D CAD information and production conditions of an assembly target product in a method of knitting an assembly line for assembling the assembly target product.
  • a plurality of automation plans in the assembly process are generated, and the assembly cost is calculated by calculating the required number of workers and the required number of facilities in the assembly line for the generated plurality of automation plans.
  • the information of automation rate, labor cost, and equipment depreciation cost when the assembly cost is minimum is output.
  • the present invention it is possible to automatically calculate from process design to line organization determination based on product design information, and the design man-hour can be reduced.
  • assembly line organization is automatically generated based on the assembly work time.
  • design of the layout of workers and equipment assuming parts supply position and equipment trouble recovery. Therefore, a layout design by a manufacturing expert such as a production technique is required for the automatic calculation result of the present invention.
  • the period excluding the layout design can be shortened with respect to the period from the process design to the line organization determination, and can be reduced by approximately 30%.
  • the present invention determines whether or not assembly automation is possible based on assembly information evaluation rules on the basis of information on a plurality of parts constituting a product, and generates an automation plan by a combination of switching the automatable process from automatic to manual. By calculating the assembly cost from the required number of workers and the required number of facilities, the line organization with the minimum assembly cost is calculated.
  • FIG. 1 shows a computer system constituting an assembly line knitting system 1 in this embodiment.
  • the assembly line organization system 1 according to the present embodiment includes an input unit 100, an output unit 200, a control unit 300, a storage unit 400, and a communication unit 500.
  • the assembly line knitting system 1 is connected from a communication unit 500 to a 3D CAD device 600 that is an external three-dimensional (3D: 3D) CAD (Computer Aided Design) device via a network 700.
  • 3D CAD device 600 is an external three-dimensional (3D: 3D) CAD (Computer Aided Design) device via a network 700.
  • the input unit 100 of the assembly line organization system 1 is, for example, a keyboard, a mouse, or a touch panel
  • the output unit 200 is, for example, a display or a printer
  • the control unit 300 is, for example, a processor such as a CPU
  • the storage unit 400 is, for example, an HDD or a semiconductor. It is memory.
  • the control unit 300 includes a 3D CAD model information acquisition unit 310, a production condition acquisition unit 320, an assembly process generation unit 330, an assembly automation determination unit 340, an assembly work time calculation unit 350, an equipment allocation unit 360, an assembly line A knitting generation unit 370 and an assembly cost calculation unit 380 are provided.
  • the storage unit 400 includes a 3D CAD model information storage area 410 that stores 3D CAD model information, a production condition information storage area 420 that stores production condition information, and an assembly process generation condition information storage area 430 that stores assembly process generation condition information.
  • An assembly process information storage area 440 that stores assembly process information, an assembly automation rule storage area 450 that stores assembly automation rules, an assembly work time database storage area 460 that stores an assembly work time database, and an equipment database are stored.
  • An equipment database storage area 470 is provided.
  • the 3D CAD model information acquisition unit 310 is a functional unit that acquires 3D CAD model information.
  • the 3D CAD model information acquisition unit 310 extracts information such as component attributes and component placement of each of a plurality of components constituting the product from the 3D CAD model stored in the 3D CAD device 600 via the communication unit 500 and the network 700. Then, processing to be stored in the 3D CAD model information storage area 410 of the storage unit 400 is performed.
  • the production condition acquisition unit 320 is a functional unit that acquires production condition information such as the number of productions, labor costs, and operation time that the user inputs to the input unit 100 and stores it in the production condition information storage area 420 of the storage unit 400.
  • the assembly process generation unit 330 generates a collection of parts and work contents to be assembled in each process in consideration of the assembly order of the parts and the construction method for each part constituting the product, and stores an assembly process generation condition information storage area in the storage unit 400 430 is a functional unit stored in 430.
  • the assembly automation determination unit 340 is a functional unit that determines whether automation is possible for each assembly process.
  • the assembly automation determination unit 340 uses the assembly information stored in the assembly information storage area 440 of the storage unit 400 to store each of a plurality of parts included in each assembly process stored in the assembly automation rule storage area 450. Processing for determining whether or not automation is possible according to an assembly automation rule corresponding to the component attribute is performed.
  • the assembly work time calculation unit 350 is a functional unit that calculates the assembly work time of each assembly process.
  • the assembly time database stored in the assembly time database storage area 460 of the storage unit 400 is used to classify by the component attribute based on a plurality of pieces of component information included in each assembly process. From the stored assembly work time database, processing for calculating the assembly work time is performed.
  • the equipment allocation unit 360 is a functional unit that assigns an ID (Identification) of a DB (Data Base) of equipment that assembles an automatic process using the equipment database stored in the equipment database storage area 470 of the storage unit 400.
  • the assembly line organization generation unit 370 is a functional unit that generates an automation plan as a combination of switching from automatic to manual for processes determined to be automatic for each assembly process.
  • the assembly cost calculation unit 380 is a functional unit that calculates the number of required workers and the number of necessary facilities for the automation plan generated by the assembly line organization generation unit 370 and calculates the assembly cost.
  • the assembly line organization system since the assembly line organization system is configured as described above, it is possible to automatically calculate from process design to line organization determination based on product design information, and the design man-hours can be reduced.
  • FIG. 2 shows a processing flow of this embodiment.
  • the 3D CAD model information acquisition unit 310 of the control unit 300 first acquires 3D model information (S10).
  • production condition information is obtained by the production condition obtaining unit 320 of the control unit 300 (S20).
  • the assembly process generation unit 330 generates an assembly process (S30).
  • the assembly automation determination unit 340 determines assembly automation (S40).
  • the assembly work time calculator 350 calculates the assembly work time (S50).
  • the equipment allocation unit 360 allocates an equipment database (DB) for an automatic process (S60).
  • the assembly line formation generation unit 370 performs assembly line formation, calculates the assembly cost for each assembly line formed by the assembly cost calculation unit (S70), and finally outputs the result of the assembly line organization plan from the output unit 200.
  • Output (S80) the 3D CAD model information acquisition unit 310 of the control unit 300.
  • the 3D CAD model information acquisition process in step S10 is executed by the 3D CAD model information acquisition unit 310 of the control unit 300.
  • 3D CAD model information acquisition process 3D CAD data obtained from the 3D CAD apparatus 600 is read, and component attribute information such as the product component configuration, the arrangement of each component, the model name, dimensions, the component center position, and the component gravity center position are acquired.
  • 3D CAD model information is created and stored in the 3D CAD model information storage area 410 of the storage unit 400.
  • the evaluation target is an assembly model that is an assembly composed of a plurality of parts.
  • the production condition information acquisition process in step S20 is executed by the production condition acquisition unit 320.
  • production condition information such as the number of productions, labor costs, and operation time that the user inputs to the input unit 100 is acquired, production condition information is created, and the production condition information in the storage unit 400 is obtained.
  • the assembly process generation process of step S30 is executed by the assembly process generation unit 330.
  • This assembly process generation process based on the 3D CAD model information acquired in step S10 and stored in the 3D CAD model information storage area 410 and the assembly process generation condition information stored in the assembly process generation condition information storage area 430 in advance, A group of parts to be assembled in each process and assembly work contents are generated, assembly process information is created, and stored in the assembly process information storage area 440 of the storage unit 400.
  • the assembly automation determination process in step S40 is executed by the assembly automation determination unit 340.
  • this assembly automation determination process based on the assembly process information generated in step S30 and stored in the assembly process information storage area 440, and the assembly automation rules stored in the assembly automation rule storage area 450 stored in advance, For each of a plurality of parts included in the process, if the assembly automation rule corresponding to the part attribute is matched, it is determined that automation is possible, and if it does not match, it is determined that automation is not possible.
  • the additional information is stored in 440.
  • the assembly work time calculation process in step S50 is executed by the assembly work time calculation unit 350.
  • each process is calculated based on the assembly process information generated in step S30 and stored in the assembly process information storage area 440, and the assembly work time database stored in advance in the assembly work time database storage area 460.
  • the assembly work time of each process is calculated from the assembly work time classified by the part attribute, and the assembly process information is stored in the assembly process information storage area 440 as additional information. .
  • the facility DB allocation process in the automatic process in step S60 is executed by the facility allocation unit 360.
  • the assembly line organization generation and assembly cost calculation processing in step S70 are executed by the assembly line organization generation unit 370 and the assembly cost calculation unit 380.
  • the maximum automation plan in which all the automatable processes are automatic processes based on the determination result of the automatability of the assembly process information stored in the assembly process information storage area 440 in step S40.
  • the assembly cost information is calculated, and the calculated assembly cost information is stored in the assembly process information storage area 440 as additional information of the assembly process information.
  • an automation plan is generated with one or more of the automatable processes as manual processes so that it can be produced with one less equipment than the maximum number of equipment required for the automation plan.
  • the assembly cost is calculated from the number and the required number of facilities, and the calculated cost information is stored in the assembly process information storage area 440 as additional information of the assembly process information. This is repeatedly calculated and stored until the number of facilities becomes zero.
  • the result output process of the assembly line organization plan in step S80 outputs a plurality of assembly line organization plans generated in step S70 and the assembly cost calculation result to the output unit 200.
  • 3A is based on “PLATE” 801, “PCB” 802 and 803 are fastened with four screws, “MODULE” 804, 805 and 806 are fastened with four screws, and “TOPCASE” 807 is screwed. It is an example of a 3D CAD assembly model of a product “PRODUCT_A” to be fastened with 8 pieces each. Also, the component configuration information on 3DCAD is shown in FIG. 3B.
  • FIG. 4 shows an example of a data format 4100 of 3D CAD model information stored in the 3D CAD model information storage area 410.
  • FIG. 4 shows the contents of the part attribute information for each part constituting the product.
  • each part ID 411 includes information such as a model name 412, a hierarchical level 413, a part number 414, a part type 415, a mass 416, a rough dimension x417, a rough dimension y418, and a rough dimension z419.
  • the part ID 411 is a unique ID assigned to each part constituting the product. For example, a unique ID is assigned so that a plurality of parts having the same shape such as a screw can be identified.
  • the model name 412 and the part number 414 are information input by the designer at the time of product design.
  • the approximate dimension x417, approximate dimension y418, and approximate dimension z419 are dimension values along the coordinate axis set in advance by the user in the three dimensions in which the product structure is arranged. And the numerical values of the dimension in the Z-axis direction.
  • the part attribute information such as the mass 416 and the approximate dimensions 417 to 419 is not limited to the information shown in the figure, and other information such as volume and main moment of inertia information may be used.
  • FIG. 5 shows an example of a screen 421 for inputting production condition information stored in the production condition information storage area 420.
  • the production condition information input to the production condition information list 4200 displayed on the screen 421 is information necessary for calculating the assembly cost of the assembly line organization plan.
  • items 422 the number of production, the working hours, and the number of shifts
  • information on the setting value 423 for each item is recorded, including information such as the number of working days, break time, equipment operation rate, personnel cost, and equipment depreciation period.
  • the OK button 424 When the OK button 424 is clicked after the entry of the value of each item 422 in the column of the set value 423, the information input on the screen 421 is stored in the production condition information storage area 420. On the other hand, when a predetermined field of the setting value field 423 is selected and the cancel button 425 is clicked, the numerical value set in the selected field of the setting value field 423 is canceled.
  • FIG. 6 shows an example of a data format 4300 of assembly process generation condition information stored in the assembly process generation condition information storage area 430.
  • FIG. 6 shows that the component configuration information obtained from the 3D CAD apparatus 600 in step S10 and stored in the 3D CAD model information storage area 410 is used as the assembly process generation method.
  • the setting value 432 of each condition item is set including information on the assembly order.
  • the parts to be assembled on the assembly line are specified at a hierarchical level, the assembly order is specified in ascending order of the part ID, and if multiple identical parts are consecutive, they are aggregated if the model names match. Generate assembly process.
  • the case where the model name 412 matches the order of the part ID 411 column for the part IDs 2 to 30 corresponding to the hierarchical level 1 described in the hierarchical level 413 column is the same process.
  • the assembly process is generated with the part IDs 3 to 6 and the like as the same process.
  • the method of generating the assembly process is not limited to the method of this embodiment in which the part ID order is the assembly order.
  • parts that can be disassembled are extracted from the adjacent relationship between the parts and the reverse of the disassembly order is assembled.
  • An ordering method may be used.
  • FIG. 7 shows an example of a data format 4400 of assembly process information stored in the assembly process information storage area 440.
  • the data format 4400 of the assembly process information includes the process ID 441 of the assembly process, the part ID 442 to be assembled in each process, the number of parts 443, the assembly work 444 indicating the contents of the assembly work, the assembly work time 445, the assembly automation determination 446, the equipment DB_ID 447, Includes automation plan 1: 448, automation plan 2: 449, and the like. Further, each of the automation plan 1: 448 and the automation plan 2; 449 includes manual / automatic type 4481, equipment ID 4482 and the like as detailed items.
  • a plurality of automation plan information can be stored, such as automation plan 1: 448, automation plan 2: 449, and the number of facilities is set one by one from the maximum automation plan in the generation of assembly line formation and the assembly cost calculation processing in step S70. Store as many automation plans as you have reduced.
  • FIG. 8 shows an example of a data format 4500 of an assembly automation rule stored in the assembly automation rule storage area 450.
  • the assembly automation rule data format 4500 includes a component attribute item 451, an attribute value 452, an attribute condition 453, a rule ID 454, a rule item 455, a determination condition 456, a determination value 457, and the like.
  • a plurality of rule IDs 454 can be set for parts that match in the part attribute item 451, the attribute value 452, and the attribute condition 453.
  • the rule item 455 includes information that can be acquired from the part attribute information in the 3D CAD model information stored in the 3D CAD model information storage area 410 such as mass and dimensions, and the assembly process stored in the assembly process information storage area 440 such as the assembly direction. If the information can be acquired from the information, the assembly automation determination unit 340 can automatically calculate the assembly automation determination. However, if information that cannot be acquired such as the material and some shape characteristics is necessary, the component supplement information of the 3D CAD data or A method in which the user additionally inputs the assembly process information may be used.
  • the determination condition 456 is a character string or numerical value determination condition such as perfect match, forward match, backward match, below, above, less than, range, and the like.
  • the assembly automation determination process in step S40 is determined for each process of the assembly process information in the data format 4400 shown in FIG. 7, and all the rules 455 for the part attribute condition 453 are determined according to the determination condition 456 for all parts included in the process.
  • “1” is stored in the column of the assembly automation possibility determination 446 in the assembly process information storage area 440 as being automatable.
  • the automated determination method includes a method that satisfies all rules and a method that satisfies a certain ratio with respect to all rules, and is not limited to the above determination method.
  • FIG. 9 shows an example of the data format 4600 of the assembly work time database stored in the assembly work time database storage area 460.
  • the assembly work time database includes an ID 461, work contents 462, work time 463, part attribute items 464, attribute values 465, attribute conditions 466, and the like.
  • a plurality of component attribute items 464, attribute values 465, and attribute conditions 466 can be set as 467, 468, and 469, respectively.
  • the component attribute item 464 is the component type as the first condition, the component whose attribute value 465 is exactly the same as “PCB”, and the component attribute item 467 is the mass as the second condition.
  • the data whose ID value is less than 0.5 and the data whose ID 461 is 2 is the same as the data whose ID attribute 461 is 1 as the second condition, and whose component attribute item 467 is the mass as the second condition.
  • the work time 463 is classified by the mass of the part attribute item 467 as a part having an attribute value of 0.5 to 2.0. In this way, detailed assembly work time setting can be performed by using a plurality of component attribute items.
  • the calculation processing of the assembly work time in step S50 is calculated for each process ID 441 in the data format 4400 of the assembly process information shown in FIG. 7, and all parts included in the same process ID 441 are shown in the data format 4600 of FIG.
  • the work time 463 is assigned as the assembly work time from the assembly work time database, and the total value is stored as the assembly work time of the relevant process in the column of the assembly work time 445 of the data format 4400 of the assembly process information.
  • FIG. 10 shows an example of the data format 4700 of the equipment database stored in the equipment database storage area 470.
  • the equipment database includes ID 471, equipment name 472, equipment investment amount 473, component attribute item 474, attribute value 475, attribute condition 476, and the like.
  • a plurality of component attribute items 474, attribute values 475, and attribute conditions 476 can be set as 477, 478, and 479, respectively. If a plurality of conditions are set, a component that meets any of the conditions (OR condition) is assembled. If automation is possible, the equipment of the ID 471 is allocated.
  • the automatic process facility DB allocation process of step S60 allocates for each process ID 441 in the data format 4400 of the assembly process information shown in FIG. 7, and the parts included in the same process ID 441 are shown in the data format 4700 of FIG. ID 471 from the installed equipment database, equipment DB of data format 4400 of assembly process information Stored in the field of ID447.
  • General-purpose equipment that can be assembled with different part attributes can be shared even with different part attributes in the continuous automatic process, leading to a reduction in the number of necessary equipment. Therefore, as shown in FIG. 10, by making it possible to set a plurality of component attribute items 474 and 477 for the equipment ID 471 in the equipment database data format 4700, the same equipment ID 471 can be allocated.
  • FIG. 11 shows a processing flow for the generation of the assembly line organization and the assembly cost calculation process in step S70.
  • step S701 based on the information in the column of the assembly process information automability determination result 446 stored in the assembly process information storage area 440 of the storage unit 400 in step S40, all the automatable processes are set as automatic processes.
  • the number of necessary facilities and the number of necessary workers are calculated for the plan, and the automatic / manual type 4481 and the equipment ID 4482 to be automated are added to the column of the automated plan 1: 448 of the assembly process information stored in the assembly process information storage area 440. Store as information.
  • the calculation method of the required number of facilities and the required number of workers for the automation plan will be described later with reference to FIGS.
  • step S702 the number of required workers calculated in step S71 is set as the target number of workers, and the number obtained by subtracting 1 from the required number of facilities calculated in step S71 is set as the target number of facilities.
  • step S703 a process group of continuous automatic processes is created for the maximum automation plan calculated in step S701, and a process group with a small remainder obtained by dividing the total work time of the automatic processes in the process group by the cycle time is selected.
  • a continuous automatic process may include a manual process, and the automatic process equipment DB_ID is the same and is a continuous automatic process.
  • step S704 an automation plan for creating one or a plurality of automatic processes included in the selected process group as a manual process is created, and the required number of facilities and the required number of workers are calculated.
  • step S705 it is checked whether the required number of facilities of the automation plan created in step S704 matches the target number of facilities (whether the target number of facilities has been achieved), and if it matches the target number of facilities (Yes in S705).
  • step S706 the labor cost is calculated from the number of workers and the equipment depreciation cost is calculated from the number of facilities, and the assembly cost is calculated and stored in the assembly process information storage area 440 as additional information of the assembly process information.
  • the target facility number is set to a value less than 1 and the process proceeds to step S707 to check whether the newly set target facility number is smaller than 0, and when it is not smaller than 0 (in the case of No in step S707). Returns to step S702. On the other hand, if the value is smaller than 0 (Yes in step S707), the process ends.
  • step S705 When the number of necessary facilities of the automation plan does not match (exceeds) the target number of facilities in the check of step S705 (in the case of No in step S705), the process proceeds to step S708 to check whether the creation of the automation plan is finished, If the process in step S704 has not been completed for all the automation combination plans for the process group selected in step S703 (No in step S708), the process proceeds to step S709 to create the next automation plan, and the process returns to step S704. .
  • step S708 determines whether step S74 has been executed for all the automation combination proposals for the process group selected in step S703 (Yes in step S708). If it is determined in the check in step S708 that step S74 has been executed for all the automation combination proposals for the process group selected in step S703 (Yes in step S708), the process proceeds to step S710.
  • step S710 it is checked whether or not all the process groups have been processed in step S703. If the processes for all the process groups have not been completed (No in step S710), the process proceeds to step S711 and continues. A process group having the next smallest remainder obtained by dividing the total work time of the automatic processes to be divided by the cycle time is selected, and the process returns to step S703.
  • step S710 determines that the process has been completed for all process groups in step S703 (Yes in step S710), there is no automation plan that satisfies the target number of facilities with the current number of target workers. Therefore, the process proceeds to step S712, a value obtained by adding 1 to the target worker number is set as the target worker number, and the process returns to step S702.
  • FIG. 12A and 12B show an image in which the number of necessary facilities differs depending on the work order of the manual process in the automation plan.
  • assembly order ID is a numerical value in ()
  • the horizontal length of the figure shows the length of work time.
  • solid lines indicate manual steps 1211, 1221 and dotted lines indicate automatic steps 1212, 1222.
  • the manual steps 1211 and 1221 are assumed to have no waiting time. Therefore, when the automatic steps 1212 and 1222 immediately before the manual steps 1211 and 1221 are not completed at the start of the manual steps 1211 and 1221, the automatic steps 1212 and 1222 following the manual steps 1211 and 1221 cannot be performed with the same equipment. Determine and calculate the required number of facilities.
  • the work order plan 1: 1210 shown in FIG. 12A shows a case where the work order of the manual process 1211 is performed in accordance with the assembly order ID, but at the end of the automatic process 1212 (eg, the end of the process of (2)). Time) and the start time of the next manual process 1211 (for example, the start time of the process (3)) overlap with each other in the assembly order ID order.
  • the work order plan 2: 1220 shown in FIG. 12B shows a case where the work order of the manual process 1221 is performed in a different order from the assembly order ID order.
  • the processes that do not overlap at the start of the next manual process 1221 in order can share equipment, and the number of necessary equipment is two.
  • the minimum equipment considering the work order of the manual process using the processing flow shown in FIG. Calculate the number as the required number of facilities.
  • FIG. 13 shows a processing flow for calculating the required number of facilities and the required number of workers for the automation plan.
  • step S721 the manual process of the automation plan is extracted, and the manual process is divided into workers so as to be close to the leveling cycle time.
  • the leveling cycle time is a value obtained by raising a value obtained by dividing the total work time of all manual processes by the cycle time to an integer and dividing the total work time of all manual processes by the integer.
  • step S722 the automatic process of the automation plan is extracted, and a value obtained by dividing the total work time by the cycle time for each process group of continuous automatic processes is calculated as an integer, and the total is set as the number of ideal facilities. calculate. In consideration of the case where the ideal number of facilities could not be achieved, in order to store the minimum number of facilities, an integer maximum value is set as the minimum number of facilities as an initial value.
  • step S723 a combination of work steps in the manual process is created for each worker divided in step S721.
  • step S724 the start time and end time of each process are calculated for the work order proposal.
  • the end time of the previous process in the work order is set as the start time, and a value obtained by adding the work time of the process to the start time is calculated as the end time.
  • the end time of the previous process in the assembly order ID order is set as the start time, and a value obtained by adding the work time of the process to the start time is calculated as the end time.
  • step S725 the required number of facilities is calculated.
  • the start time of the manual process is divided into process groups after the previous process in the order of assembly order ID and the total time falls within the cycle time, and the number of divisions is determined by the process group.
  • the required number of facilities is calculated, and the total value is calculated as the required number of facilities on the assembly line.
  • step S726 the number of necessary facilities is compared with the minimum number of facilities. If the number of necessary facilities is smaller than the minimum number of facilities (in the case of Yes), the process proceeds to step S727, and the number of necessary facilities is equal to or greater than the minimum number of facilities (No ), The process proceeds to step S729. In step S727, the required number of facilities is set to the minimum number of facilities.
  • step S728 it is determined whether or not the minimum number of facilities matches the number of ideal facilities calculated in step S722. If they match (if Yes), the process proceeds to step S730, where the number of ideal facilities is returned as the required number of facilities on the assembly line. This processing flow ends. If the minimum number of facilities does not match the number of ideal facilities (No in step S728), the process proceeds to step S729.
  • step S729 it is checked whether the creation of the combination of work orders has been completed. If the creation has been completed (in the case of Yes), the process proceeds to step S731, and the processing flow ends with the minimum number of facilities set as the required number of facilities on the assembly line To do. If it is determined in step S729 that the combination of work orders has not ended (in the case of No), the process returns to step S723 to create the next work order plan.
  • FIG. 14A shows an example of an output screen 1400 of the assembly automation rule determination result.
  • FIG. 14A shows the results for the entire assembly process.
  • the list 1410 displays a maximum automation rate 1401 of the entire product, an ID 1412, a component ID 1413, the number of components 1414, an assembly operation 1415, an assembly operation time 1416, an assembly automation availability determination result 1417, and the like for each assembly process.
  • FIG. 14B shows a list 1460 of determination results for each rule as an example of an output screen 1450 of detailed results by assembly process for the assembly process selected from all the assembly processes shown in FIG. 14A.
  • ID 1461, attribute 1462, assembly operation 1463, rule ID 1464, rule item 1465, determination condition 1466, determination value (rule value) 1467, attribute value (value in the target part) 1468, determination result 1469, etc. of the selected process are shown.
  • the determination result 1469 for each rule ID 1464 it is possible to use for the design activity for improving the automation rate, such as improving the product structure of the rule whose determination result is NG, for the process of determining the automation impossible.
  • FIG. 15 shows an example of an output screen 1500 of an assembly line organization plan generation result as an output of the present invention.
  • an automation rate 1511, personnel cost 1512, equipment depreciation cost 1513, assembly cost 1514, and the like are displayed as a table 1510 of the minimum assembly cost result.
  • the result of calculating the assembly cost from a plurality of automation plans, the required number of workers and the required number of facilities is stored. Therefore, a list 1510 of the minimum assembly costs is output, and a graph 1520 indicating the relationship between the automation rate 1521, personnel costs 1522, equipment depreciation costs 1523, and assembly costs 1524 is output as a tendency of the automation plan.
  • the assembly shown in FIG. 14A is performed.
  • the process to be improved is extracted on the display screen 1400 of the automated rule determination result or the detailed result display screen 1450 for each assembly process.
  • the improvement point in the process to be improved is input, and the processing flow as described in FIG. 2 based on the data that has input the improvement point. Can be re-executed to recalculate the assembly cost and the result can be displayed again on the screen of FIG.
  • the line organization with the minimum assembly cost can be calculated.
  • the assembly line organization is automatically generated based on the assembly work time.
  • the arrangement of workers and equipment is assumed assuming parts supply position and equipment trouble recovery.
  • Design is required, and layout design by manufacturing experts such as production technology is required for the automatic calculation result according to the present embodiment.
  • the period excluding the layout design can be shortened with respect to the period from the process design to the line organization determination, and can be reduced by approximately 30%.

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Abstract

In order to reduce assembly cost by optimizing the organization of an assembly line including a combination of manual and automated assembly steps, the present invention provides a method for organizing an assembly line in order to assemble a product to be assembled, wherein: assembly steps are created on the basis of 3D CAD information and production conditions of a product to be assembled; a plurality of automation proposals are generated for the created assembly steps; the required number of workers and required number of pieces of equipment in the assembly line are calculated for the generated plurality of automation proposals to calculate the assembly cost; and information on the automation rate, labor cost, and equipment repayment cost for the automation proposal with the lowest calculated assembly cost among the plurality of automation proposals is outputted.

Description

組立ライン編成システム及び組立ライン編成方法Assembly line knitting system and assembly line knitting method
　本発明は、コンピュータを用いて組立ライン編成を決定する組立ライン編成システム及び組立ライン編成方法に関する。 The present invention relates to an assembly line knitting system and an assembly line knitting method for determining assembly line knitting using a computer.
　従来、複数の部品から構成される組立型製品の組立ライン編成を計画する方法として、構造設計者が想定する部品の組立順序と工法を基に、生産技術など製造有識者によって、生産台数・生産拠点の人件費・設備能力を考慮しながら、工程分割と各工程のリソース種類（人手組立とするか自動化するかなど）を決定し、必要作業者数と必要設備数を算出してライン編成を決定する方法が行われていた。 Conventionally, as a method of planning the assembly line organization of assembly-type products composed of multiple parts, based on the assembly order and construction method of parts assumed by the structural designer, the production number and production bases by production experts such as production technology Determine the process division and resource type of each process (whether manual assembly or automation, etc.), calculate the number of required workers and the number of necessary equipment, and determine the line organization. There was a way to do it.
　このとき、各工程を人手組立とするか自動化するかの判定について、工程に必要な組立精度が人手の組立精度を超えるような工程については自動化が必須となるが、人手組立と自動化のどちらでも対応可能な場合、工程数や生産台数や設備投資上限額などを考慮して、生産技術者によって工程の自動化判断を行う場合が多い。 At this time, regarding the process of determining whether each process is manual assembly or automation, it is essential to automate the process where the assembly accuracy required for the process exceeds the manual assembly accuracy. When it is possible to handle this, there are many cases where a production engineer makes a process automation decision in consideration of the number of processes, the number of units produced, and the upper limit of capital investment.
　また、人件費と設備投資の合計としての組立コストを低減するために、複数の自動化案を想定して、生産能力を満たしながら組立コストが最も低い案を選定するなどを行っているが、全ての工程の手動/自動化の組合せから最も組立コストが低い案を算出するのは困難であった。 In addition, in order to reduce the assembly cost as the sum of labor costs and capital investment, multiple automation plans are assumed, and the plan with the lowest assembly cost is selected while satisfying the production capacity. It was difficult to calculate the proposal with the lowest assembly cost from the combination of manual / automated processes.
　生産能力に対して設備投資を最適化する方法として、特許文献１に記載されているような生産ライン計画支援装置および生産ライン計画支援方法がある。これは、生産ラインに対して、生産能力と投資費用を求めるシミュレーション手段を用いて、目標生産能力および目標投資費用に近くなるように、予め格納した生産能力と投資費用の異なる複数の設備から選択して設備投資費用を最適化する方法である。 As a method for optimizing the capital investment with respect to the production capacity, there is a production line planning support apparatus and a production line planning support method as described in Patent Document 1. This is selected from a plurality of pre-stored facilities with different production capacities and investment costs so as to be close to the target production capacities and target investment costs by using a simulation means for obtaining production capacities and investment costs for the production line. This is a method for optimizing the capital investment cost.
　また、生産能力の増大が求められる場合に設備投資を最小化する方法として、特許文献２に記載されているような生産計画を実現する設備人員計画の立案装置と立案方法がある。これは、過去に行った生産能力増強方法について、量的に拡大した投資額と生産能力の関係、および、質的に改善した投資額と生産能力の関係を記憶しておき、対象とする生産ラインの生産能力について、製品生産に要する経常的費用が最小となるように、量的拡大の投資額とその投資時期および質的改善の投資額とその投資時期を算出する方法である。 Also, as a method for minimizing the capital investment when an increase in production capacity is required, there are a facility personnel plan planning device and a planning method for realizing a production plan as described in Patent Document 2. This is because the relationship between the amount of investment and production capacity that has been quantitatively expanded and the relationship between the amount of investment and production capacity that has been qualitatively improved are memorized for the production capacity enhancement method that was performed in the past, and the target production For the production capacity of the line, the amount of investment for quantitative expansion and the timing of its investment and the amount of investment for qualitative improvement and its timing of investment are calculated so that the recurring costs required for product production are minimized.
特開２００６‐３１３６０号公報JP 2006-31360 A 特開２００３‐３１６８６０号公報JP 2003-316860 A
　特許文献１に記載されている生産ライン計画支援装置および生産ライン計画支援方法は、予め決められた自動化工程に対しての設備投資を低減する効果はあるが、各工程の手動/自動化判断を含めた組立コスト低減や、人件費と設備投資の合計としての組立コストを低減する効果はない。 The production line planning support apparatus and the production line planning support method described in Patent Document 1 have an effect of reducing capital investment for a predetermined automated process, but include manual / automated judgment of each process. Therefore, there is no effect of reducing the assembly cost and the assembly cost as the sum of the labor cost and the capital investment.
　また、特許文献２に記載されている生産計画を実現する設備人員計画の立案装置と立案方法は、人件費と設備投資の合計を最小化する方法だが、過去の生産ラインの自動化率（工程の自動化判断）を基にしているため、各工程の手動/自動化判断を含めた組立コスト最小のライン編成を算出することはできない。 In addition, the equipment personnel planning device and the planning method for realizing the production plan described in Patent Document 2 is a method for minimizing the total of labor cost and capital investment. Because it is based on (automated judgment), it is not possible to calculate a line organization with the minimum assembly cost including manual / automated judgment of each process.
　このように、従来技術においては、人件費と設備投資の合計として組立コストを低減するために、工程の手動/自動化判断を含めたライン編成の決定方法は確立されていない。 Thus, in the prior art, in order to reduce the assembly cost as the sum of the labor cost and the capital investment, a method for determining the line organization including the manual / automated judgment of the process has not been established.
　そこで、本発明では、上記した課題を解決して、人件費と設備投資の合計として組立コストを低減するために、工程の手動/自動化判断を含めたライン編成を決定する場合において、製品を構成する複数の部品情報を基に、各工程の手動/自動化判断を含めた組立コスト最小のライン編成を自動算出することを可能にする組立ライン編成システム及び組立ライン編成方法を提供する。 Therefore, in the present invention, in order to solve the above-described problems and reduce the assembly cost as the sum of the labor cost and the capital investment, the product is configured when determining the line organization including the manual / automated judgment of the process. Provided is an assembly line knitting system and an assembly line knitting method capable of automatically calculating a line knitting with a minimum assembly cost including manual / automated judgment of each process based on a plurality of parts information.
　上記課題を解決するために、本発明では、組立対象製品を組み立てるための組立ラインを編成するシステムを、演算部と、記憶部と、入力部と、出力部とを備えて構成し、演算部は、記憶部に記憶された組立対象製品の３ＤＣＡＤ情報と生産条件とを取得する情報取得部と、この情報取得部で取得した組立対象製品の３ＤＣＡＤ情報と組立対象製品の生産条件に基づいて組立工程を作成する組立工程生成部と、この組立工程生成部で作成した組立工程における自動化の可否を判定する組立自動化判定部と、組立工程生成部で作成した組立工程における組立対象製品の組立作業時間を求める組立作業時間算出部と、組立自動化判定部で自動化の可可能と判定された工程について自動から手動に切り替えた組合せによる複数の自動化案を生成する組立ライン編成生成部と、この組立ライン編成生成部で生成した複数の自動化案について組立ラインにおける必要作業者数と必要設備数とを算出して組立コストを算出する組立コスト計算部とを備え、出力部は、演算部で算出した複数の自動化案に対する組立コストの情報を出力するように構成した。 In order to solve the above-described problem, in the present invention, a system for knitting an assembly line for assembling a product to be assembled includes a calculation unit, a storage unit, an input unit, and an output unit. The information acquisition unit that acquires the 3D CAD information and production conditions of the assembly target product stored in the storage unit, and the assembly based on the 3D CAD information of the assembly target product acquired by the information acquisition unit and the production condition of the assembly target product An assembly process generation unit for creating a process, an assembly automation determination unit for determining whether automation is possible in the assembly process created by the assembly process generation unit, and an assembly work time of the assembly target product in the assembly process created by the assembly process generation unit Generates multiple automation plans by combining the automatic operation and manual switching for the processes determined as possible by the assembly work time calculation unit and the assembly automation determination unit. An assembly line organization generation unit, and an assembly cost calculation unit that calculates an assembly cost by calculating the number of required workers and the number of necessary facilities in the assembly line for a plurality of automation plans generated by the assembly line organization generation unit, The output unit is configured to output assembly cost information for a plurality of automation plans calculated by the calculation unit.
　また、上記課題を解決するために、本発明では、組立対象製品を組み立てるための組立ラインを編成する方法において、組立対象製品の３ＤＣＡＤ情報と生産条件とを取得し、この取得した組立対象製品の３ＤＣＡＤ情報と組立対象製品の生産条件に基づいて組立工程を作成し、この作成した組立工程における自動化の可否を判定し、作成した組立工程における組立対象製品の組立作業時間を求め、自動化の可否の判定において自動化可能と判定された工程について自動から手動に切り替えた組合せによる複数の自動化案を生成し、この生成した複数の自動化案について組立ラインにおける必要作業者数と必要設備数とを算出して組立コストを算出し、この算出した複数の自動化案に対する組立コストの情報を出力するようにした。 In order to solve the above-described problem, the present invention acquires 3D CAD information and production conditions of an assembly target product in a method of knitting an assembly line for assembling the assembly target product. Create an assembly process based on the 3D CAD information and the production conditions of the assembly target product, determine whether automation is possible in the created assembly process, determine the assembly work time of the assembly target product in the created assembly process, and determine whether automation is possible Generate a plurality of automation plans by a combination of switching from automatic to manual for the process determined to be automatable in the determination, and calculate the number of required workers and the number of necessary facilities in the assembly line for the generated plurality of automation plans The assembly cost is calculated, and information on the assembly cost for the plurality of calculated automation plans is output.
　更に、上記課題を解決するために、本発明では、組立対象製品を組み立てるための組立ラインを編成する方法において、組立対象製品の３ＤＣＡＤ情報と生産条件とに基づいて組立工程を作成し、この作成した組立工程における複数の自動化案を生成し、この生成した複数の自動化案について組立ラインにおける必要作業者数と必要設備数とを算出して組立コストを算出し、この算出した複数の自動化案のうちの組立コストが最少となるときの自動化率、人件費、及び設備償却費の情報を出力するようにした。 Furthermore, in order to solve the above-described problems, the present invention creates an assembly process based on 3D CAD information and production conditions of an assembly target product in a method of knitting an assembly line for assembling the assembly target product. A plurality of automation plans in the assembly process are generated, and the assembly cost is calculated by calculating the required number of workers and the required number of facilities in the assembly line for the generated plurality of automation plans. The information of automation rate, labor cost, and equipment depreciation cost when the assembly cost is minimum is output.
　本発明によれば、人件費と設備投資の合計としての組立コストを最小化する組立ライン編成を提供することができる。 According to the present invention, it is possible to provide an assembly line organization that minimizes the assembly cost as the sum of labor costs and capital investment.
　また、本発明によれば、製品設計情報を基に工程設計からライン編成決定までを自動算出することが可能となり、設計工数が削減できる。本発明は、組立作業時間を基に組立ライン編成を自動で生成しているが、実際の組立ライン編成においては、部品供給位置や設備トラブル復旧などを想定した、作業者や設備の配置の設計が必要であり、本発明の自動算出結果に対し、生産技術などの製造有識者によるレイアウト設計が必要となる。本発明によれば、工程設計からライン編成決定までの期間に対し、レイアウト設計を除いた期間を短縮でき、概ね３０％低減することができる。 Further, according to the present invention, it is possible to automatically calculate from process design to line organization determination based on product design information, and the design man-hour can be reduced. In the present invention, assembly line organization is automatically generated based on the assembly work time. However, in actual assembly line organization, design of the layout of workers and equipment assuming parts supply position and equipment trouble recovery. Therefore, a layout design by a manufacturing expert such as a production technique is required for the automatic calculation result of the present invention. According to the present invention, the period excluding the layout design can be shortened with respect to the period from the process design to the line organization determination, and can be reduced by approximately 30%.
本発明の実施例における組立ライン編成システムの構成の一例を示すブロック図である。It is a block diagram which shows an example of a structure of the assembly line organization system in the Example of this invention. 本発明の実施例における組立ライン編成システムの処理の流れの一例を示すフロー図である。It is a flowchart which shows an example of the flow of a process of the assembly line organization system in the Example of this invention. ３ＤＣＡＤ組立品モデルの構成一例を説明する斜視図である。It is a perspective view explaining an example of composition of a 3D CAD assembly model. ３ＤＣＡＤ組立品モデルの構成のリスト一例を説明する構成リスト図である。It is a structure list figure explaining an example of a list of a structure of 3D CAD assembly model. 本発明の実施例における３ＤＣＡＤモデル情報の一例を示すデータ形式の図である。It is a figure of the data format which shows an example of 3D CAD model information in the Example of this invention. 本発明の実施例における生産条件情報を入力する画面の一例を示す画面の正面図である。It is a front view of the screen which shows an example of the screen which inputs the production condition information in the Example of this invention. 本発明の実施例における組立工程生成条件の一例を示すデータ形式の図である。It is a figure of the data format which shows an example of the assembly process production | generation conditions in the Example of this invention. 本発明の実施例における組立工程情報の一例を示すデータ形式の図である。It is a figure of the data format which shows an example of the assembly process information in the Example of this invention. 本発明の実施例における組立自動化ルールの一例を示すデータ形式の図である。It is a figure of the data format which shows an example of the assembly automation rule in the Example of this invention. 本発明の実施例における組立作業時間データベースの一例を示すデータ形式の図である。It is a figure of the data format which shows an example of the assembly work time database in the Example of this invention. 本発明の実施例における設備データベースの一例を示すデータ形式の図である。It is a figure of the data format which shows an example of the equipment database in the Example of this invention. 本発明の実施例における組立ライン編成の生成と組立コスト計算処理の処理フローの一例を示すフロー図である。It is a flowchart which shows an example of the processing flow of the production | generation of assembly line organization in the Example of this invention, and an assembly cost calculation process. 本発明の実施例における作業順序によって必要設備数が異なるイメージを示す図である。It is a figure which shows the image from which the number of required facilities changes with the work orders in the Example of this invention. 本発明の実施例における作業順序によって必要設備数が異なるイメージを示す図である。It is a figure which shows the image from which the number of required facilities changes with the work orders in the Example of this invention. 本発明の実施例における自動化案に対する必要設備数と必要作業者数の算出処理の処理フローの一例を示すフロー図である。It is a flowchart which shows an example of the processing flow of the calculation process of the required equipment number and required worker number with respect to the automation plan in the Example of this invention. 本発明の実施例における組立自動化ルール判定結果の出力画面の一例を示す画面の正面図である。It is a front view of the screen which shows an example of the output screen of the assembly automation rule determination result in the Example of this invention. 本発明の実施例における組立自動化ルール判定結果の組立工程別詳細結果の出力画面の一例を示す画面の正面図である。It is a front view of the screen which shows an example of the output screen of the detailed result according to assembly process of the assembly automation rule determination result in the Example of this invention. 本発明の実施例における組立ライン編成案生成結果の出力画面の一例を示す画面の正面図である。It is a front view of the screen which shows an example of the output screen of the assembly line organization plan production | generation result in the Example of this invention.
　本発明は、製品を構成する複数の部品情報を基に、組立性評価ルールに基づき、組立自動化可否を判定し、組立自動化可能工程を自動から手動に切り替えた組合せによる自動化案生成と、自動化案の必要作業者数と必要設備数から組立コストを計算することで、最小組立コストのライン編成を算出するようにしたものである。　
　以下に、本発明による組み立てライン編成システム及び組立ライン編成方法の実施例を、図を用いて説明する。 The present invention determines whether or not assembly automation is possible based on assembly information evaluation rules on the basis of information on a plurality of parts constituting a product, and generates an automation plan by a combination of switching the automatable process from automatic to manual. By calculating the assembly cost from the required number of workers and the required number of facilities, the line organization with the minimum assembly cost is calculated.
Embodiments of an assembly line knitting system and an assembly line knitting method according to the present invention will be described below with reference to the drawings.
　＜システム構成＞　
　図１に、本実施例における組立ライン編成システム１を構成するコンピュータシステムを示す。本実施例に係る組立ライン編成システム１は、入力部１００、出力部２００、制御部３００、記憶部４００、通信部５００を備えて構成される。この組立ライン編成システム１は、通信部５００から、外部にある３次元（３Ｄｉｍｅｎｓｉｏｎ：３Ｄ）のＣＡＤ（Ｃｏｍｐｕｔｅｒ　Ａｉｄｅｄ　Ｄｅｓｉｇｎ）装置である３ＤＣＡＤ装置６００とネットワーク７００を介して接続されている。 <System configuration>
FIG. 1 shows a computer system constituting an assembly line knitting system 1 in this embodiment. The assembly line organization system 1 according to the present embodiment includes an input unit 100, an output unit 200, a control unit 300, a storage unit 400, and a communication unit 500. The assembly line knitting system 1 is connected from a communication unit 500 to a 3D CAD device 600 that is an external three-dimensional (3D: 3D) CAD (Computer Aided Design) device via a network 700.
　組立ライン編成システム１の入力部１００は例えばキーボードやマウスまたはタッチパネルであり、出力部２００は例えばディスプレイやプリンタであり、制御部３００は例えばＣＰＵなどのプロセッサであり、記憶部４００は例えばＨＤＤや半導体メモリである。 The input unit 100 of the assembly line organization system 1 is, for example, a keyboard, a mouse, or a touch panel, the output unit 200 is, for example, a display or a printer, the control unit 300 is, for example, a processor such as a CPU, and the storage unit 400 is, for example, an HDD or a semiconductor. It is memory.
　制御部３００は、３ＤＣＡＤモデル情報取得部３１０と、生産条件取得部３２０と、組立工程生成部３３０と、組立自動化判定部３４０と、組立作業時間計算部３５０と、設備引当部３６０と、組立ライン編成生成部３７０と、組立コスト計算部３８０とを備えている。 The control unit 300 includes a 3D CAD model information acquisition unit 310, a production condition acquisition unit 320, an assembly process generation unit 330, an assembly automation determination unit 340, an assembly work time calculation unit 350, an equipment allocation unit 360, an assembly line A knitting generation unit 370 and an assembly cost calculation unit 380 are provided.
　記憶部４００は、３ＤＣＡＤモデル情報を記憶する３ＤＣＡＤモデル情報記憶領域４１０と、生産条件情報を記憶する生産条件情報記憶領域４２０と、組立工程生成条件情報を記憶する組立工程生成条件情報記憶領域４３０と、組立工程情報を記憶する組立工程情報記憶領域４４０と、組立自動化ルールを記憶する組立自動化ルール記憶領域４５０と、組立作業時間データベースを記憶する組立作業時間データベース記憶領域４６０と、設備データベースを記憶する設備データベース記憶領域４７０を備える。 The storage unit 400 includes a 3D CAD model information storage area 410 that stores 3D CAD model information, a production condition information storage area 420 that stores production condition information, and an assembly process generation condition information storage area 430 that stores assembly process generation condition information. An assembly process information storage area 440 that stores assembly process information, an assembly automation rule storage area 450 that stores assembly automation rules, an assembly work time database storage area 460 that stores an assembly work time database, and an equipment database are stored. An equipment database storage area 470 is provided.
　３ＤＣＡＤモデル情報取得部３１０は、３ＤＣＡＤモデルの情報を取得する機能部である。この３ＤＣＡＤモデル情報取得部３１０では、製品を構成する複数の部品それぞれの部品属性や部品配置などの情報を、通信部５００及びネットワーク７００を介して３ＤＣＡＤ装置６００に記憶されている３ＤＣＡＤモデルから抽出して記憶部４００の３ＤＣＡＤモデル情報記憶領域４１０に記憶させる処理などを行う。 The 3D CAD model information acquisition unit 310 is a functional unit that acquires 3D CAD model information. The 3D CAD model information acquisition unit 310 extracts information such as component attributes and component placement of each of a plurality of components constituting the product from the 3D CAD model stored in the 3D CAD device 600 via the communication unit 500 and the network 700. Then, processing to be stored in the 3D CAD model information storage area 410 of the storage unit 400 is performed.
　生産条件取得部３２０は、ユーザが入力部１００に入力する生産台数や人件費や稼動時間などの生産条件情報を取得して記憶部４００の生産条件情報記憶領域４２０に記憶する機能部である。 The production condition acquisition unit 320 is a functional unit that acquires production condition information such as the number of productions, labor costs, and operation time that the user inputs to the input unit 100 and stores it in the production condition information storage area 420 of the storage unit 400.
　組立工程生成部３３０は、製品を構成する各部品について、部品の組立順序や工法を考慮して各工程で組立てる部品のまとまりと作業内容を生成して記憶部４００の組立工程生成条件情報記憶領域４３０に記憶する機能部である。 The assembly process generation unit 330 generates a collection of parts and work contents to be assembled in each process in consideration of the assembly order of the parts and the construction method for each part constituting the product, and stores an assembly process generation condition information storage area in the storage unit 400 430 is a functional unit stored in 430.
　組立自動化判定部３４０は、各組立工程について自動化可否を判定する機能部である。この組立自動化判定部３４０では、記憶部４００の組立情報記憶領域４４０に記憶された組立情報を用いて、各組立工程に含まれる複数の部品それぞれについて、組立自動化ルール記憶領域４５０に記憶されたその部品属性に対応した組立自動化ルールに従って自動化可否を判定する処理を行う。 The assembly automation determination unit 340 is a functional unit that determines whether automation is possible for each assembly process. The assembly automation determination unit 340 uses the assembly information stored in the assembly information storage area 440 of the storage unit 400 to store each of a plurality of parts included in each assembly process stored in the assembly automation rule storage area 450. Processing for determining whether or not automation is possible according to an assembly automation rule corresponding to the component attribute is performed.
　組立作業時間計算部３５０は、各組立工程の組立作業時間を計算する機能部である。この組立作業時間計算部３５０では、記憶部４００の組立時間データベース記憶領域４６０に記憶された組立時間データベースを用いて各組立工程に含まれる複数の部品情報を基に、その部品属性などで分類し記憶されている組立作業時間データベースから、組立作業時間を計算する処理を行う。 The assembly work time calculation unit 350 is a functional unit that calculates the assembly work time of each assembly process. In this assembly work time calculation unit 350, the assembly time database stored in the assembly time database storage area 460 of the storage unit 400 is used to classify by the component attribute based on a plurality of pieces of component information included in each assembly process. From the stored assembly work time database, processing for calculating the assembly work time is performed.
　設備引当部３６０は、記憶部４００の設備データベース記憶領域４７０に記憶された設備データベースを用いて自動工程を組立てる設備のＤＢ(Ｄａｔａ　Ｂａｓｅ：データベース）のＩＤ（Iｄｅｎｔｉｆｉｃａｔｉｏｎ）を引き当てる機能部である。 The equipment allocation unit 360 is a functional unit that assigns an ID (Identification) of a DB (Data Base) of equipment that assembles an automatic process using the equipment database stored in the equipment database storage area 470 of the storage unit 400.
　組立ライン編成生成部３７０は、各組立工程について自動化可能と判断された工程について、自動から手動に切り替えた組合せとして自動化案を生成する機能部である。 The assembly line organization generation unit 370 is a functional unit that generates an automation plan as a combination of switching from automatic to manual for processes determined to be automatic for each assembly process.
　組立コスト計算部３８０は、組立ライン編成生成部３７０で生成した自動化案について必要作業者数と必要設備数を算出し、組立コストを計算する機能部である。 The assembly cost calculation unit 380 is a functional unit that calculates the number of required workers and the number of necessary facilities for the automation plan generated by the assembly line organization generation unit 370 and calculates the assembly cost.
　本実施例によれば、組立ライン編成システムを上記構成としたことにより、製品設計情報を基に工程設計からライン編成決定までを自動算出することが可能となり、設計工数を削減することができる。 According to this embodiment, since the assembly line organization system is configured as described above, it is possible to automatically calculate from process design to line organization determination based on product design information, and the design man-hours can be reduced.
　＜全体処理フロー＞　
　図２に、本実施例の処理フローを示す。　
　図２に示した処理フローにおいては、まず制御部３００の３ＤＣＡＤモデル情報取得部３１０で３Ｄモデルの情報を取得する（Ｓ１０）。次に、制御部３００の生産条件取得部３２０で生産条件情報を取得する（Ｓ２０）。次に、組立工程生成部３３０において組立工程を生成する(Ｓ３０)。次に、組立自動化判定部３４０において組立自動化の判定を行う（Ｓ４０）。次に、組立作業時間計算部３５０で組立作業時間の計算を行う(Ｓ５０)。次に、設備引当部３６０において自動工程の設備データベース（ＤＢ）の引き当てを行う（Ｓ６０）。次に、組立ライン編成生成部３７０において組立ラインの編成を行い、組立コスト計算部で編成した組立ラインごとの組立コストを計算し(Ｓ７０)、最後に出力部２００から組み立てライン編成案の結果を出力する（Ｓ８０）。 <Overall processing flow>
FIG. 2 shows a processing flow of this embodiment.
In the processing flow shown in FIG. 2, the 3D CAD model information acquisition unit 310 of the control unit 300 first acquires 3D model information (S10). Next, production condition information is obtained by the production condition obtaining unit 320 of the control unit 300 (S20). Next, the assembly process generation unit 330 generates an assembly process (S30). Next, the assembly automation determination unit 340 determines assembly automation (S40). Next, the assembly work time calculator 350 calculates the assembly work time (S50). Next, the equipment allocation unit 360 allocates an equipment database (DB) for an automatic process (S60). Next, the assembly line formation generation unit 370 performs assembly line formation, calculates the assembly cost for each assembly line formed by the assembly cost calculation unit (S70), and finally outputs the result of the assembly line organization plan from the output unit 200. Output (S80).
　以下に、各ステップについて詳細に説明する。　
　ステップＳ１０の３ＤＣＡＤモデルの情報取得処理は、制御部３００の３ＤＣＡＤモデル情報取得部３１０で実行される。この３ＤＣＡＤモデルの情報取得処理では、３ＤＣＡＤ装置６００より入手した３ＤＣＡＤデータを読み込み、製品の部品構成、各部品の配置、モデル名、寸法、部品中心位置や部品重心位置などの部品属性情報を取得して、３ＤＣＡＤモデル情報を作成して記憶部４００の３ＤＣＡＤモデル情報記憶領域４１０に格納する。ここで、評価対象は、複数の部品から構成される組立品であるアセンブリモデルとする。 Hereinafter, each step will be described in detail.
The 3D CAD model information acquisition process in step S10 is executed by the 3D CAD model information acquisition unit 310 of the control unit 300. In this 3D CAD model information acquisition process, 3D CAD data obtained from the 3D CAD apparatus 600 is read, and component attribute information such as the product component configuration, the arrangement of each component, the model name, dimensions, the component center position, and the component gravity center position are acquired. 3D CAD model information is created and stored in the 3D CAD model information storage area 410 of the storage unit 400. Here, the evaluation target is an assembly model that is an assembly composed of a plurality of parts.
　ステップＳ２０の生産条件情報の取得処理は、生産条件取得部３２０で実行される。この生産条件情報の取得処理では、ユーザが入力部１００に対して入力する生産台数や人件費や稼働時間などの生産条件情報を取得し、生産条件情報を作成して記憶部４００の生産条件情報記憶領域４２０に格納する。 The production condition information acquisition process in step S20 is executed by the production condition acquisition unit 320. In the production condition information acquisition process, production condition information such as the number of productions, labor costs, and operation time that the user inputs to the input unit 100 is acquired, production condition information is created, and the production condition information in the storage unit 400 is obtained. Store in the storage area 420.
　ステップＳ３０の組立工程の生成処理は、組立工程生成部３３０で実行される。この組立工程の生成処理では、ステップＳ１０で取得して３ＤＣＡＤモデル情報記憶領域４１０に格納された３ＤＣＡＤモデル情報と、予め組立工程生成条件情報記憶領域４３０に記憶した組立工程生成条件情報を基に、各工程で組立てる部品のまとまりと組立作業内容を生成し、組立工程情報を作成して記憶部４００の組立工程情報記憶領域４４０に格納する。 The assembly process generation process of step S30 is executed by the assembly process generation unit 330. In this assembly process generation process, based on the 3D CAD model information acquired in step S10 and stored in the 3D CAD model information storage area 410 and the assembly process generation condition information stored in the assembly process generation condition information storage area 430 in advance, A group of parts to be assembled in each process and assembly work contents are generated, assembly process information is created, and stored in the assembly process information storage area 440 of the storage unit 400.
　ステップＳ４０の組立自動化の判定処理は、組立自動化判定部３４０で実行される。この組立自動化の判定処理では、ステップＳ３０で生成して組立工程情報記憶領域４４０に格納された組立工程情報と、予め記憶した組立自動化ルール記憶領域４５０に格納された組立自動化ルールを基に、各工程に含まれる複数の部品それぞれについて、部品属性に対応した組立自動化ルールに合致する場合は自動化可能、合致しない場合は自動化不可と判定し、その判定結果としての組立工程情報を組立工程情報記憶領域４４０に追加情報として格納する。 The assembly automation determination process in step S40 is executed by the assembly automation determination unit 340. In this assembly automation determination process, based on the assembly process information generated in step S30 and stored in the assembly process information storage area 440, and the assembly automation rules stored in the assembly automation rule storage area 450 stored in advance, For each of a plurality of parts included in the process, if the assembly automation rule corresponding to the part attribute is matched, it is determined that automation is possible, and if it does not match, it is determined that automation is not possible. The additional information is stored in 440.
　ステップＳ５０の組立作業時間の計算処理は、組立作業時間計算部３５０で実行される。この組立作業時間の計算処理では、ステップＳ３０で生成して組立工程情報記憶領域４４０に記憶された組立工程情報と、組立作業時間データベース記憶領域４６０に予め記憶した組立作業時間データベースを基に、各工程に含まれる複数の部品情報を基に、部品属性などで分類している組立作業時間から各工程の組立作業時間を計算し、組立工程情報を組立工程情報記憶領域４４０に追加情報として格納する。 The assembly work time calculation process in step S50 is executed by the assembly work time calculation unit 350. In the calculation process of the assembly work time, each process is calculated based on the assembly process information generated in step S30 and stored in the assembly process information storage area 440, and the assembly work time database stored in advance in the assembly work time database storage area 460. Based on a plurality of parts information included in the process, the assembly work time of each process is calculated from the assembly work time classified by the part attribute, and the assembly process information is stored in the assembly process information storage area 440 as additional information. .
　ステップＳ６０の自動工程の設備ＤＢの引当処理は、設備引当部３６０で実行される。この自動工程の設備ＤＢの引当処理では、ステップＳ３０で生成し、ステップＳ４０で行った組立自動化可否の判定結果を追加情報として組立工程情報記憶領域４４０に格納した組立工程情報と、設備データベース記憶領域４７０に予め記憶した設備データベースを基に、自動化可能工程を組立てる設備ＤＢのＩＤを引当てる。そして、この、設備ＤＢのＩＤを引当てた組立工程情報を、組立工程情報記憶領域４４０に追加情報として格納する。 The facility DB allocation process in the automatic process in step S60 is executed by the facility allocation unit 360. In this automatic process facility DB allocation process, assembly process information generated in step S30 and stored in the assembly process information storage area 440 as additional information as to whether or not assembly automation is possible in step S40, and an equipment database storage area Based on the equipment database stored in advance in 470, the ID of the equipment DB for assembling the automatable process is allocated. Then, the assembly process information in which the ID of the equipment DB is allocated is stored as additional information in the assembly process information storage area 440.
　ステップＳ７０における組立ライン編成の生成と組立コスト計算処理は、組立ライン編成生成部３７０および組立コスト計算部３８０で実行される。組立ライン編成の生成と組立コスト計算処理では、ステップＳ４０で組立工程情報記憶領域４４０に格納された組立工程情報の自動化可否判定結果を基に、全ての自動化可能工程を自動工程とした最大自動化案での組立コストを計算し、この計算した組立コスト情報を組立工程情報の追加情報として組立工程情報記憶領域４４０に格納する。 The assembly line organization generation and assembly cost calculation processing in step S70 are executed by the assembly line organization generation unit 370 and the assembly cost calculation unit 380. In the generation of the assembly line organization and the assembly cost calculation process, the maximum automation plan in which all the automatable processes are automatic processes based on the determination result of the automatability of the assembly process information stored in the assembly process information storage area 440 in step S40. The assembly cost information is calculated, and the calculated assembly cost information is stored in the assembly process information storage area 440 as additional information of the assembly process information.
　続いて、最大自動化案の必要設備数より1台少ない設備数で生産できるように、自動化可能工程のうち一つまたは複数の工程を手動工程とした自動化案を生成し、自動化案の必要作業者数と必要設備数から組立コストを計算し、この計算したコスト情報を組立工程情報の追加情報として組立工程情報記憶領域４４０に格納する。これを設備数が０になるまで繰り返し計算し、格納する。 Subsequently, an automation plan is generated with one or more of the automatable processes as manual processes so that it can be produced with one less equipment than the maximum number of equipment required for the automation plan. The assembly cost is calculated from the number and the required number of facilities, and the calculated cost information is stored in the assembly process information storage area 440 as additional information of the assembly process information. This is repeatedly calculated and stored until the number of facilities becomes zero.
　ステップＳ８０の組立ライン編成案の結果出力処理は、ステップＳ７０で生成された複数の組立ライン編成案とその組立コスト計算結果を出力部２００に出力する。 The result output process of the assembly line organization plan in step S80 outputs a plurality of assembly line organization plans generated in step S70 and the assembly cost calculation result to the output unit 200.
　＜データの説明＞　
次に、図３Ａに示すようなアセンブリモデルを例として、各ステップで作成・記憶されるデータ形式の例を図４～図１０に示す。 <Explanation of data>
Next, taking an assembly model as shown in FIG. 3A as an example, examples of data formats created and stored in each step are shown in FIGS.
　図３Ａは、「ＰＬＡＴＥ」８０１をベースとして、「ＰＣＢ」８０２と８０３をネジ各４本で締結し、「ＭＯＤＵＬＥ」８０４，８０５，８０６をネジ各４本で締結し、「ＴＯＰＣＡＳＥ」８０７をネジ各８本で締結する製品「ＰＲＯＤＵＣＴ＿Ａ」の３ＤＣＡＤのアセンブリモデルの例である。また、３ＤＣＡＤ上の部品構成情報を図３Ｂに示す。 3A is based on “PLATE” 801, “PCB” 802 and 803 are fastened with four screws, “MODULE” 804, 805 and 806 are fastened with four screws, and “TOPCASE” 807 is screwed. It is an example of a 3D CAD assembly model of a product “PRODUCT_A” to be fastened with 8 pieces each. Also, the component configuration information on 3DCAD is shown in FIG. 3B.
　図４に、３ＤＣＡＤモデル情報記憶領域４１０に記憶される３ＤＣＡＤモデル情報のデータ形式４１００の例を示す。図４は、製品を構成する各部品についての部品属性情報の内容を示すものである。図に示すように、部品ＩＤ４１１ごとに、モデル名４１２、階層レベル４１３、部品番号４１４、部品種別４１５、質量４１６、概形寸法ｘ４１７、概形寸法ｙ４１８、概形寸法ｚ４１９などの情報を含む。 FIG. 4 shows an example of a data format 4100 of 3D CAD model information stored in the 3D CAD model information storage area 410. FIG. 4 shows the contents of the part attribute information for each part constituting the product. As shown in the figure, each part ID 411 includes information such as a model name 412, a hierarchical level 413, a part number 414, a part type 415, a mass 416, a rough dimension x417, a rough dimension y418, and a rough dimension z419.
　部品ＩＤ４１１は、製品を構成する各部品に付与される固有ＩＤであり、例えばネジのように同形状の複数部品についても、それぞれを特定できるように固有ＩＤを付与するものである。 The part ID 411 is a unique ID assigned to each part constituting the product. For example, a unique ID is assigned so that a plurality of parts having the same shape such as a screw can be identified.
　モデル名４１２、部品番号４１４は、設計者が製品設計時に、それぞれ入力する情報である。 The model name 412 and the part number 414 are information input by the designer at the time of product design.
　概形寸法ｘ４１７、概形寸法ｙ４１８、概形寸法ｚ４１９は、製品構造が配置されている３次元において予めユーザが設定した座標軸に沿っての寸法値であり、Ｘ軸方向の寸法、Ｙ軸方向の寸法、Ｚ軸方向の寸法の各数値である。 The approximate dimension x417, approximate dimension y418, and approximate dimension z419 are dimension values along the coordinate axis set in advance by the user in the three dimensions in which the product structure is arranged. And the numerical values of the dimension in the Z-axis direction.
　質量４１６や概形寸法４１７～４１９などの部品属性情報は、図に示す情報に限定するものではなく、体積、主慣性モーメント情報など他の情報を用いてもよい。 The part attribute information such as the mass 416 and the approximate dimensions 417 to 419 is not limited to the information shown in the figure, and other information such as volume and main moment of inertia information may be used.
　図５に、生産条件情報記憶領域４２０に記憶される生産条件情報を入力する画面４２１の一例を示す。画面４２１上に表示された生産条件情報の一覧表４２００に入力される生産条件情報は、組立ライン編成案の組立コスト計算に必要な情報であり、項目４２２として、生産台数、就労時間、シフト数、就労日数、休憩時間、設備稼働率、人件費、設備償却期間、などの情報を含み、それぞれの項目に対する設定値４２３の情報が記録されている。 FIG. 5 shows an example of a screen 421 for inputting production condition information stored in the production condition information storage area 420. The production condition information input to the production condition information list 4200 displayed on the screen 421 is information necessary for calculating the assembly cost of the assembly line organization plan. As items 422, the number of production, the working hours, and the number of shifts In addition, information on the setting value 423 for each item is recorded, including information such as the number of working days, break time, equipment operation rate, personnel cost, and equipment depreciation period.
　項目４２２の欄の生産台数、就労時間、シフト数、就労日数、休憩時間、設備稼働率の各項目に対応する設定値４２３の欄に記録された数値を用いて、組立ラインのサイクルタイムを計算し、自動化案における必要設備数と必要作業者数の計算に用いる。また、項目４２２の欄の人件費、設備償却期間の各項目に対応する設定値４２３の欄に記録された数値は、自動化案における組立コスト計算に用いる。 Calculate the cycle time of the assembly line using the values recorded in the column of the set value 423 corresponding to the items of production quantity, working hours, shifts, working days, break hours, and equipment availability in the item 422 column. And used to calculate the required number of facilities and the number of workers in the automation plan. Further, the numerical values recorded in the column of the set value 423 corresponding to each item of the labor cost and the equipment depreciation period in the column of the item 422 are used for the assembly cost calculation in the automation plan.
　設定値４２３の欄にそれぞれの項目４２２の値の入力を終えた後、ＯＫボタン４２４をクリックすると、画面４２１上で入力された情報が生産条件情報記憶領域４２０に記憶される。一方、設定値４２３の欄の所定の欄を選んでキャンセルボタン４２５をクリックすると、設定値４２３の欄の選んだ欄に設定された数値がキャンセルされる。 When the OK button 424 is clicked after the entry of the value of each item 422 in the column of the set value 423, the information input on the screen 421 is stored in the production condition information storage area 420. On the other hand, when a predetermined field of the setting value field 423 is selected and the cancel button 425 is clicked, the numerical value set in the selected field of the setting value field 423 is canceled.
　図６に、組立工程生成条件情報記憶領域４３０に記憶される組立工程生成条件情報のデータ形式４３００の一例を示す。図６は、組立工程生成の方法として、ステップＳ１０で３ＤＣＡＤ装置６００より入手して３ＤＣＡＤモデル情報記憶領域４１０に記憶させた部品構成情報を利用することとし、条件項目４３１として階層レベル、部品集約項目、組立順序の情報を含み、それぞれの条件項目の設定値４３２を設定する。３ＤＣＡＤモデル情報に対し、組立ラインで組立てる対象の部品を階層レベルで指定し、組立順序は部品ＩＤの小さい順で指定し、複数の同一部品が連続する場合はモデル名が一致する場合は集約して組立工程を生成する。 FIG. 6 shows an example of a data format 4300 of assembly process generation condition information stored in the assembly process generation condition information storage area 430. FIG. 6 shows that the component configuration information obtained from the 3D CAD apparatus 600 in step S10 and stored in the 3D CAD model information storage area 410 is used as the assembly process generation method. The setting value 432 of each condition item is set including information on the assembly order. For the 3D CAD model information, the parts to be assembled on the assembly line are specified at a hierarchical level, the assembly order is specified in ascending order of the part ID, and if multiple identical parts are consecutive, they are aggregated if the model names match. Generate assembly process.
　図４の３ＤＣＡＤモデル情報の例では、階層レベル４１３の欄に記載された階層レベル1に該当する部品ＩＤ：２～３０に対し、部品ＩＤ４１１の欄の順にモデル名４１２が一致した場合を同一工程とする場合、部品ＩＤ：３～６などを同一工程として組立工程を生成する。 In the example of the 3D CAD model information in FIG. 4, the case where the model name 412 matches the order of the part ID 411 column for the part IDs 2 to 30 corresponding to the hierarchical level 1 described in the hierarchical level 413 column is the same process. In this case, the assembly process is generated with the part IDs 3 to 6 and the like as the same process.
　組立工程生成の方法は、部品ＩＤ順を組立順序とする本実施例の方法に限定するものではなく、例えば、部品と部品の隣接関係から分解可能な部品を抽出し、分解順序の逆を組立順序とする方法を用いてもよい。 The method of generating the assembly process is not limited to the method of this embodiment in which the part ID order is the assembly order. For example, parts that can be disassembled are extracted from the adjacent relationship between the parts and the reverse of the disassembly order is assembled. An ordering method may be used.
　図７に、組立工程情報記憶領域４４０に記憶させる組立工程情報のデータ形式４４００の一例を示す。組立工程情報のデータ形式４４００は、組立工程の工程ＩＤ４４１、各工程で組立てる部品ＩＤ４４２、部品数４４３、組立作業の内容を示す組立作業４４４、組立作業時間４４５、組立自動化可否判定４４６、設備ＤＢ＿ＩＤ４４７、自動化案１：４４８、自動化案２：４４９などを含む。また、自動化案１:４４８、自動化案２；４４９毎に細項目として手動/自動種別４４８１、設備ＩＤ４４８２などを含む。 FIG. 7 shows an example of a data format 4400 of assembly process information stored in the assembly process information storage area 440. The data format 4400 of the assembly process information includes the process ID 441 of the assembly process, the part ID 442 to be assembled in each process, the number of parts 443, the assembly work 444 indicating the contents of the assembly work, the assembly work time 445, the assembly automation determination 446, the equipment DB_ID 447, Includes automation plan 1: 448, automation plan 2: 449, and the like. Further, each of the automation plan 1: 448 and the automation plan 2; 449 includes manual / automatic type 4481, equipment ID 4482 and the like as detailed items.
　自動化案の情報は自動化案１:４４８、自動化案２；４４９のように複数格納可能とし、ステップＳ７０の組立ライン編成の生成と組立コスト計算処理において、最大自動化案から、設備数を1台ずつ減らした自動化案の数だけ格納する。 A plurality of automation plan information can be stored, such as automation plan 1: 448, automation plan 2: 449, and the number of facilities is set one by one from the maximum automation plan in the generation of assembly line formation and the assembly cost calculation processing in step S70. Store as many automation plans as you have reduced.
　図８に、組立自動化ルール記憶領域４５０に記憶させる組立自動化ルールのデータ形式４５００一例を示す。組立自動化ルールのデータ形式４５００は、部品属性項目４５１、属性値４５２、属性条件４５３、ルールＩＤ４５４、ルール項目４５５、判定条件４５６、判定値４５７などを含む。部品属性項目４５１と属性値４５２と属性条件４５３で一致する部品に対して、ルールＩＤ４５４を複数設定可能とする。 FIG. 8 shows an example of a data format 4500 of an assembly automation rule stored in the assembly automation rule storage area 450. The assembly automation rule data format 4500 includes a component attribute item 451, an attribute value 452, an attribute condition 453, a rule ID 454, a rule item 455, a determination condition 456, a determination value 457, and the like. A plurality of rule IDs 454 can be set for parts that match in the part attribute item 451, the attribute value 452, and the attribute condition 453.
　ルール項目４５５は、質量や寸法など３ＤＣＡＤモデル情報記憶領域４１０に記憶された３ＤＣＡＤモデル情報のうちの部品属性情報から取得可能な情報、組付方向など組立工程情報記憶領域４４０に記憶された組立工程情報から取得可能な情報であれば、組立自動化判定部３４０で組立自動化判定を自動計算できるが、材質や一部の形状特徴など取得不可能な情報が必要な場合、３ＤＣＡＤデータの部品補足情報や組立工程情報にユーザが追加入力する方法でもよい。 The rule item 455 includes information that can be acquired from the part attribute information in the 3D CAD model information stored in the 3D CAD model information storage area 410 such as mass and dimensions, and the assembly process stored in the assembly process information storage area 440 such as the assembly direction. If the information can be acquired from the information, the assembly automation determination unit 340 can automatically calculate the assembly automation determination. However, if information that cannot be acquired such as the material and some shape characteristics is necessary, the component supplement information of the 3D CAD data or A method in which the user additionally inputs the assembly process information may be used.
　判定条件４５６は、完全一致、前方一致、後方一致、以下、以上、未満、範囲など、文字列や数値の判定条件とする。 The determination condition 456 is a character string or numerical value determination condition such as perfect match, forward match, backward match, below, above, less than, range, and the like.
　ステップＳ４０の組立自動化の判定処理は、図７に示すデータ形式４４００の組立工程情報の工程毎に判定し、工程に含まれる全ての部品について、部品属性条件４５３に対するルール４５５の全てが判定条件４５６を満たす場合に自動化可能として組立工程情報記憶領域４４０の組立自動化可否判定４４６の欄に「１」を格納する。自動化判定方法は、全ルールを満たす方法の他、全ルールに対して一定割合を満たす方法などもあり、上記判定方法に限定するものではない。 The assembly automation determination process in step S40 is determined for each process of the assembly process information in the data format 4400 shown in FIG. 7, and all the rules 455 for the part attribute condition 453 are determined according to the determination condition 456 for all parts included in the process. When the condition is satisfied, “1” is stored in the column of the assembly automation possibility determination 446 in the assembly process information storage area 440 as being automatable. The automated determination method includes a method that satisfies all rules and a method that satisfies a certain ratio with respect to all rules, and is not limited to the above determination method.
　図９に、組立作業時間データベース記憶領域４６０に記憶する組立作業時間データベースのデータ形式４６００の一例を示す。組立作業時間データベースは、ＩＤ４６１、作業内容４６２、作業時間４６３、部品属性項目４６４、属性値４６５、属性条件４６６などを含む。部品属性項目４６４と属性値４６５と属性条件４６６はそれぞれ４６７，４６８，４６９のように複数設定可能とし、複数条件が設定されている場合、全条件に合致する(ＡＮＤ条件)部品に対して、当該作業内容と作業時間を引き当て、組立工程の作業時間を算出する。 FIG. 9 shows an example of the data format 4600 of the assembly work time database stored in the assembly work time database storage area 460. The assembly work time database includes an ID 461, work contents 462, work time 463, part attribute items 464, attribute values 465, attribute conditions 466, and the like. A plurality of component attribute items 464, attribute values 465, and attribute conditions 466 can be set as 467, 468, and 469, respectively. When a plurality of conditions are set, for parts that match all the conditions (AND condition), The work content and work time are allocated, and the work time of the assembly process is calculated.
　図９の例では、ＩＤ４６１が１のデータは、第１条件として部品属性項目４６４が部品種別であり、属性値４６５が「ＰＣＢ」と完全一致する部品、第２条件として部品属性項目４６７が質量であり、属性値が０．５未満の部品とし、ＩＤ４６１が２のデータは、第１条件の部品属性項目４６４はＩＤ４６１が１のデータと同様で、第２条件として部品属性項目４６７が質量であり、属性値が０．５～２．０の部品として、部品属性項目４６７の質量によって作業時間４６３を分類している。このように、部品属性項目を複数用いることで詳細な組立作業時間設定が可能となる。 In the example of FIG. 9, in the data with ID 461 of 1, the component attribute item 464 is the component type as the first condition, the component whose attribute value 465 is exactly the same as “PCB”, and the component attribute item 467 is the mass as the second condition. The data whose ID value is less than 0.5 and the data whose ID 461 is 2 is the same as the data whose ID attribute 461 is 1 as the second condition, and whose component attribute item 467 is the mass as the second condition. Yes, the work time 463 is classified by the mass of the part attribute item 467 as a part having an attribute value of 0.5 to 2.0. In this way, detailed assembly work time setting can be performed by using a plurality of component attribute items.
　ステップＳ５０の組立作業時間の計算処理は、図７に示す組立工程情報のデータ形式４４００における工程ＩＤ４４１毎に計算し、同一の工程ＩＤ４４１に含まれる全ての部品について、図９のデータ形式４６００に示した組立作業時間データベースより作業時間４６３を組立作業時間として引き当て、その合計値を当該工程の組立作業時間として、組立工程情報のデータ形式４４００の組立作業時間４４５の欄に格納する。 The calculation processing of the assembly work time in step S50 is calculated for each process ID 441 in the data format 4400 of the assembly process information shown in FIG. 7, and all parts included in the same process ID 441 are shown in the data format 4600 of FIG. The work time 463 is assigned as the assembly work time from the assembly work time database, and the total value is stored as the assembly work time of the relevant process in the column of the assembly work time 445 of the data format 4400 of the assembly process information.
　図１０に、設備データベース記憶領域４７０に記憶する設備データベースのデータ形式４７００の一例を示す。設備データベースは、ＩＤ４７１、設備名４７２、設備投資額４７３、部品属性項目４７４、属性値４７５、属性条件４７６、などを含む。部品属性項目４７４と属性値４７５と属性条件４７６はそれぞれ４７７，４７８，４７９のように複数設定可能とし、複数条件が設定されている場合、いずれかの条件に合致する(ＯＲ条件)部品が組立自動化可能な場合、当該ＩＤ４７１の設備を引き当てる。 FIG. 10 shows an example of the data format 4700 of the equipment database stored in the equipment database storage area 470. The equipment database includes ID 471, equipment name 472, equipment investment amount 473, component attribute item 474, attribute value 475, attribute condition 476, and the like. A plurality of component attribute items 474, attribute values 475, and attribute conditions 476 can be set as 477, 478, and 479, respectively. If a plurality of conditions are set, a component that meets any of the conditions (OR condition) is assembled. If automation is possible, the equipment of the ID 471 is allocated.
　ステップＳ６０の自動工程の設備ＤＢの引当処理は、図７に示す組立工程情報のデータ形式４４００における工程ＩＤ４４１毎に引当し、同一の工程ＩＤ４４１に含まれる部品について、図１０のデータ形式４７００に示した設備データベースよりＩＤ４７１を引当、組立工程情報のデータ形式４４００の設備ＤＢ ＩＤ４４７の欄に格納する。 The automatic process facility DB allocation process of step S60 allocates for each process ID 441 in the data format 4400 of the assembly process information shown in FIG. 7, and the parts included in the same process ID 441 are shown in the data format 4700 of FIG. ID 471 from the installed equipment database, equipment DB of data format 4400 of assembly process information   Stored in the field of ID447.
　異なる部品属性でも組立可能な汎用的な設備は、連続する自動工程が異なる部品属性でも共用可能であり、必要設備数の削減につながる。そこで、図１０に示したように、設備データベースのデータ形式４７００の設備ＩＤ４７１について、複数の部品属性項目４７４，４７７を設定可能とすることで、同一の設備ＩＤ４７１の引当ができるようにした。 General-purpose equipment that can be assembled with different part attributes can be shared even with different part attributes in the continuous automatic process, leading to a reduction in the number of necessary equipment. Therefore, as shown in FIG. 10, by making it possible to set a plurality of component attribute items 474 and 477 for the equipment ID 471 in the equipment database data format 4700, the same equipment ID 471 can be allocated.
　図１１に、ステップＳ７０の組立ライン編成の生成と組立コスト計算処理について処理フローを示す。 FIG. 11 shows a processing flow for the generation of the assembly line organization and the assembly cost calculation process in step S70.
　ステップＳ７０１では、ステップＳ４０で記憶部４００の組立工程情報記憶領域４４０に格納された組立工程情報の自動化可否判定結果４４６の欄の情報を基に、全ての自動化可能工程を自動工程とした最大自動化案に対し、必要設備数と必要作業者数を計算し、組立工程情報記憶領域４４０格納された組立工程情報の自動化案１：４４８の欄に自動/手動種別４４８１と自動化する設備ＩＤ４４８２とを追加情報として格納する。自動化案に対する必要設備数と必要作業者数の算出方法は、図１２、図１３にて後述する。 In step S701, based on the information in the column of the assembly process information automability determination result 446 stored in the assembly process information storage area 440 of the storage unit 400 in step S40, all the automatable processes are set as automatic processes. The number of necessary facilities and the number of necessary workers are calculated for the plan, and the automatic / manual type 4481 and the equipment ID 4482 to be automated are added to the column of the automated plan 1: 448 of the assembly process information stored in the assembly process information storage area 440. Store as information. The calculation method of the required number of facilities and the required number of workers for the automation plan will be described later with reference to FIGS.
　ステップＳ７０２では、ステップＳ７１で算出した必要作業者数を目標作業者数に、ステップＳ７１で算出した必要設備数から１減じた数を目標設備数に設定する。 In step S702, the number of required workers calculated in step S71 is set as the target number of workers, and the number obtained by subtracting 1 from the required number of facilities calculated in step S71 is set as the target number of facilities.
　ステップＳ７０３では、ステップＳ７０１で算出した最大自動化案について、連続する自動工程の工程群を作成し、工程群の自動工程の作業時間の合計をサイクルタイムで割った余りが小さい工程群を選択する。連続する自動工程とは、手動工程を間に挟んでもよく、自動工程の設備ＤＢ_ＩＤが一致し、かつ連続する自動工程とする。 In step S703, a process group of continuous automatic processes is created for the maximum automation plan calculated in step S701, and a process group with a small remainder obtained by dividing the total work time of the automatic processes in the process group by the cycle time is selected. A continuous automatic process may include a manual process, and the automatic process equipment DB_ID is the same and is a continuous automatic process.
　ステップＳ７０４では、選択された工程群に含まれる自動工程のうち一つまたは複数を手動工程にする自動化案を作成し、必要設備数と必要作業者数を算出する。 In step S704, an automation plan for creating one or a plurality of automatic processes included in the selected process group as a manual process is created, and the required number of facilities and the required number of workers are calculated.
　ステップＳ７０５では、ステップＳ７０４で作成した自動化案の必要設備数が目標設備数と一致したか(目標設備数を達成したか)をチェックし、目標設備数と一致した場合（Ｓ７０５でＹｅｓの場合）、ステップＳ７０６に進んで作業者数から人件費、設備数から設備償却費をそれぞれ計算して組立コストを計算し組立工程情報記憶領域４４０に組立工程情報の追加情報として格納する。また、目標設備数を１少ない値に設定し、ステップＳ７０７に進んで新たに設定した目標設備数が０よりも小さいかをチェックし、０よりも小さくない場合(ステップＳ７０７でＮｏの場合)にはステップＳ７０２に戻る。一方、０よりも小さくなった場合(ステップＳ７０７でＹｅｓの場合)には、処理を終了する。 In step S705, it is checked whether the required number of facilities of the automation plan created in step S704 matches the target number of facilities (whether the target number of facilities has been achieved), and if it matches the target number of facilities (Yes in S705). In step S706, the labor cost is calculated from the number of workers and the equipment depreciation cost is calculated from the number of facilities, and the assembly cost is calculated and stored in the assembly process information storage area 440 as additional information of the assembly process information. Also, the target facility number is set to a value less than 1 and the process proceeds to step S707 to check whether the newly set target facility number is smaller than 0, and when it is not smaller than 0 (in the case of No in step S707). Returns to step S702. On the other hand, if the value is smaller than 0 (Yes in step S707), the process ends.
　ステップＳ７０５のチェックで自動化案の必要設備数が目標設備数と一致しない（超える）場合(ステップＳ７０５でＮｏの場合)、ステップＳ７０８に進んで自動化案の作成を終了するか否かをチェックし、ステップＳ７０３で選択した工程群について自動化の組合せ案全てについてステップＳ７０４での処理を終えていない場合(ステップＳ７０８でＮｏの場合)、ステップＳ７０９に進んで次の自動化案を作成し、ステップＳ７０４に戻る。 When the number of necessary facilities of the automation plan does not match (exceeds) the target number of facilities in the check of step S705 (in the case of No in step S705), the process proceeds to step S708 to check whether the creation of the automation plan is finished, If the process in step S704 has not been completed for all the automation combination plans for the process group selected in step S703 (No in step S708), the process proceeds to step S709 to create the next automation plan, and the process returns to step S704. .
　一方、ステップＳ７０８におけるチェックで、ステップＳ７０３で選択した工程群について自動化の組合せ案全てについてステップＳ７４を実行したと判断した場合（ステップＳ７０８でＹｅｓの場合)には、ステップＳ７１０に進む。 On the other hand, if it is determined in the check in step S708 that step S74 has been executed for all the automation combination proposals for the process group selected in step S703 (Yes in step S708), the process proceeds to step S710.
　ステップＳ７１０において、ステップＳ７０３で全ての工程群について処理を行ったかをチェックし、全ての工程群についての処理を完了していない場合(ステップＳ７１０でＮｏの場合)には、ステップＳ７１１に進んで連続する自動工程の作業時間の合計をサイクルタイムで割った余りが次に小さい工程群を選択し、ステップＳ７０３に戻る。 In step S710, it is checked whether or not all the process groups have been processed in step S703. If the processes for all the process groups have not been completed (No in step S710), the process proceeds to step S711 and continues. A process group having the next smallest remainder obtained by dividing the total work time of the automatic processes to be divided by the cycle time is selected, and the process returns to step S703.
　一方、ステップＳ７１０において、ステップＳ７０３で全ての工程群について処理を完了したと判断した場合(ステップＳ７１０でＹｅｓの場合)には、現在の目標作業者数で目標設備数を満たす自動化案は無いことがわかるため、ステップＳ７１２に進んで目標作業者数に１加えた値を目標作業者数に設定して、ステップＳ７０２に戻る。 On the other hand, if it is determined in step S710 that the process has been completed for all process groups in step S703 (Yes in step S710), there is no automation plan that satisfies the target number of facilities with the current number of target workers. Therefore, the process proceeds to step S712, a value obtained by adding 1 to the target worker number is set as the target worker number, and the process returns to step S702.
　図１１に示したような処理フローで組立コストを計算することにより、組立ライン編成の生成とこの生成した組立ラインのおける組立コストを計算することができる。 11. By calculating the assembly cost according to the processing flow as shown in FIG. 11, it is possible to calculate the assembly line organization and the assembly cost in the generated assembly line.
　図１２Ａ及び図１２Ｂに、自動化案において、手動工程の作業順序によって必要設備数が異なるイメージを示す。図１２Ａ及び図１２Ｂでは、各工程を長方形図形で示し、組立順序ＩＤを（ ）内の数値で、図形の水平方向長さは作業時間の長さを示す。長方形図形が実線は手動工程１２１１，１２２１、点線は自動工程１２１２，１２２２を示す。 12A and 12B show an image in which the number of necessary facilities differs depending on the work order of the manual process in the automation plan. In FIG. 12A and FIG. 12B, each process is shown by a rectangular figure, assembly order ID is a numerical value in (), and the horizontal length of the figure shows the length of work time. In the rectangular figure, solid lines indicate manual steps 1211, 1221 and dotted lines indicate automatic steps 1212, 1222.
　本実施例では、手動工程１２１１，１２２１は待ち時間を持たない条件を想定する。そのため、手動工程１２１１，１２２１開始時に、組立順序ＩＤ順で直前の自動工程１２１２，１２２２が終了していなければ、当該手動工程１２１１，１２２１に続く自動工程１２１２，１２２２を同一の設備で作業できないと判断し必要設備数を算出する。 In this embodiment, the manual steps 1211 and 1221 are assumed to have no waiting time. Therefore, when the automatic steps 1212 and 1222 immediately before the manual steps 1211 and 1221 are not completed at the start of the manual steps 1211 and 1221, the automatic steps 1212 and 1222 following the manual steps 1211 and 1221 cannot be performed with the same equipment. Determine and calculate the required number of facilities.
　図１２Ａに示した作業順序案１：１２１０に、手動工程１２１１の工程順序を組立順序ＩＤどおりで作業を行った場合を示すが、自動工程１２１２の終了時（例：（２）の工程の終了時）と組立順序ＩＤ順で次となる手動工程１２１１の開始時（例：（３）の工程の開始時）が重なるため、必要設備数が５台となる。 The work order plan 1: 1210 shown in FIG. 12A shows a case where the work order of the manual process 1211 is performed in accordance with the assembly order ID, but at the end of the automatic process 1212 (eg, the end of the process of (2)). Time) and the start time of the next manual process 1211 (for example, the start time of the process (3)) overlap with each other in the assembly order ID order.
　一方、図１２Ｂに示した作業順序案２：１２２０では、手動工程１２２１の工程順序を組立順序ＩＤ順とは異なる順で作業を行った場合を示すが、自動工程１２２２の終了時と組立順序ＩＤ順で次となる手動工程１２２１の開始時が重ならない工程は設備を共用することが可能となり、必要設備数が２台となる。 On the other hand, the work order plan 2: 1220 shown in FIG. 12B shows a case where the work order of the manual process 1221 is performed in a different order from the assembly order ID order. The processes that do not overlap at the start of the next manual process 1221 in order can share equipment, and the number of necessary equipment is two.
　このように、ある自動化案についての必要設備数を計算する場合、手動工程の作業順序によって設備数が異なるため、図１３に示すような処理フローを用いて手動工程の作業順序を考慮した最小設備数を必要設備数として計算する。 Thus, when calculating the required number of facilities for a certain automation plan, the number of facilities differs depending on the work order of the manual process. Therefore, the minimum equipment considering the work order of the manual process using the processing flow shown in FIG. Calculate the number as the required number of facilities.
　図１３に、自動化案に対する必要設備数と必要作業者数の算出処理について処理フローを示す。 FIG. 13 shows a processing flow for calculating the required number of facilities and the required number of workers for the automation plan.
　ステップＳ７２１では、自動化案の手動工程を抽出し、平準化サイクルタイムに近くなるように手動工程を作業者に分割する。平準化サイクルタイムとは、全手動工程の作業時間の合計をサイクルタイムで割った値を整数に繰上げ、全手動工程の作業時間の合計を当該整数で割った値である。 In step S721, the manual process of the automation plan is extracted, and the manual process is divided into workers so as to be close to the leveling cycle time. The leveling cycle time is a value obtained by raising a value obtained by dividing the total work time of all manual processes by the cycle time to an integer and dividing the total work time of all manual processes by the integer.
　ステップＳ７２２では、自動化案の自動工程を抽出し、連続する自動工程の工程群毎に作業時間の合計をサイクルタイムで割った値を整数に繰上げた値を計算し、その合計を理想設備数として計算する。また、理想設備数を達成できなかった場合のことを考慮し、最小設備数を格納するため、初期値として整数最大値を最小設備数に設定する。
ステップＳ７２３では、ステップＳ７２１で分割した作業者毎に、手動工程の作業順序の組合せを作成する。 In step S722, the automatic process of the automation plan is extracted, and a value obtained by dividing the total work time by the cycle time for each process group of continuous automatic processes is calculated as an integer, and the total is set as the number of ideal facilities. calculate. In consideration of the case where the ideal number of facilities could not be achieved, in order to store the minimum number of facilities, an integer maximum value is set as the minimum number of facilities as an initial value.
In step S723, a combination of work steps in the manual process is created for each worker divided in step S721.
　ステップＳ７２４では、作業順序案について、各工程の開始時間と終了時間を計算する。
手動工程は作業順序の前工程の終了時間を開始時間とし、開始時間に当該工程の作業時間を加算した値を終了時間として計算する。自動工程は、組立順序ＩＤ順の前工程の終了時間を開始時間とし、開始時間に当該工程の作業時間を加算した値を終了時間として計算する。 In step S724, the start time and end time of each process are calculated for the work order proposal.
In the manual process, the end time of the previous process in the work order is set as the start time, and a value obtained by adding the work time of the process to the start time is calculated as the end time. In the automatic process, the end time of the previous process in the assembly order ID order is set as the start time, and a value obtained by adding the work time of the process to the start time is calculated as the end time.
　ステップＳ７２５では、必要設備数を計算する。連続する自動工程の工程群毎に、手動工程の開始時間が組立順序ＩＤ順の前工程より後で、かつ、合計時間がサイクルタイム内に入る工程群に分割し、分割数を当該工程群での必要設備数として計算し、その合計値を組立ラインの必要設備数として計算する。 In step S725, the required number of facilities is calculated. For each process group of continuous automatic processes, the start time of the manual process is divided into process groups after the previous process in the order of assembly order ID and the total time falls within the cycle time, and the number of divisions is determined by the process group. The required number of facilities is calculated, and the total value is calculated as the required number of facilities on the assembly line.
　ステップＳ７２６では、必要設備数と最小設備数を比較し、必要設備数が最小設備数よりも少ない場合（Ｙｅｓの場合）ステップＳ７２７に進み、必要設備数が最小設備数と同等以上の場合（Ｎｏの場合）、ステップＳ７２９に進む。
ステップＳ７２７では、必要設備数を最小設備数に設定する。 In step S726, the number of necessary facilities is compared with the minimum number of facilities. If the number of necessary facilities is smaller than the minimum number of facilities (in the case of Yes), the process proceeds to step S727, and the number of necessary facilities is equal to or greater than the minimum number of facilities (No ), The process proceeds to step S729.
In step S727, the required number of facilities is set to the minimum number of facilities.
　ステップＳ７２８では、最小設備数がステップＳ７２２で算出した理想設備数と一致したかを判定し、一致した場合（Ｙｅｓの場合）、ステップＳ７３０に進み、理想設備数を組立ラインの必要設備数として返し、本処理フローを終了する。最小設備数が理想設備数と一致しない場合（ステップＳ７２８でＮｏの場合）、ステップＳ７２９に進む。 In step S728, it is determined whether or not the minimum number of facilities matches the number of ideal facilities calculated in step S722. If they match (if Yes), the process proceeds to step S730, where the number of ideal facilities is returned as the required number of facilities on the assembly line. This processing flow ends. If the minimum number of facilities does not match the number of ideal facilities (No in step S728), the process proceeds to step S729.
　ステップＳ７２９では、作業順序の組合せ作成が終了したかをチェックし、作成が終了した場合（Ｙｅｓの場合）、ステップＳ７３１に進んで最小設備数を組立ラインの必要設備数として、本処理フローを終了する。ステップＳ７２９のチェックで作業順序の組合せが終了していないと判断した場合（Ｎｏの場合）、次の作業順序案を作成するためステップＳ７２３に戻る。 In step S729, it is checked whether the creation of the combination of work orders has been completed. If the creation has been completed (in the case of Yes), the process proceeds to step S731, and the processing flow ends with the minimum number of facilities set as the required number of facilities on the assembly line To do. If it is determined in step S729 that the combination of work orders has not ended (in the case of No), the process returns to step S723 to create the next work order plan.
　図１３に示したフローに沿って処理を進めることにより、自動化案に対する必要設備数と必要作業者数とを算出することができる。 By proceeding along the flow shown in FIG. 13, it is possible to calculate the number of necessary facilities and the number of necessary workers for the automation plan.
　図１４Ａに、組立自動化ルール判定結果の出力画面１４００の一例を示す。図１４Ａは、全組立工程についての結果を示す。製品全体の最大自動化率１４０１や、組立工程毎に、ＩＤ１４１２、部品ＩＤ１４１３、部品数１４１４、組立作業１４１５、組立作業時間１４１６、組立自動化可否判定結果１４１７などが一覧表１４１０に表示される。組立工程毎に自動化可否判定結果を示すことで、製品全体の自動化可能割合や、自動化工程の連続度合いを把握することができる。 FIG. 14A shows an example of an output screen 1400 of the assembly automation rule determination result. FIG. 14A shows the results for the entire assembly process. The list 1410 displays a maximum automation rate 1401 of the entire product, an ID 1412, a component ID 1413, the number of components 1414, an assembly operation 1415, an assembly operation time 1416, an assembly automation availability determination result 1417, and the like for each assembly process. By showing the result of determining whether automation is possible for each assembly process, it is possible to grasp the automatable ratio of the entire product and the degree of continuity of the automation process.
　図１４Ａに示した全組立工程の中から選択した組立工程についての組立工程別詳細結果の出力画面１４５０の一例として、図１４Ｂにルール毎の判定結果の一覧表１４６０を示す。選択した工程のＩＤ１４６１、属性１４６２、組立作業１４６３、ルールＩＤ１４６４、ルール項目１４６５、判定条件１４６６、判定値(ルールの値)１４６７、属性値（対象部品での値）１４６８、判定結果１４６９などを示す。ルールＩＤ１４６４毎に判定結果１４６９を示すことで、自動化不可判定の工程について、判定結果がＮＧのルールの製品構造の改良を行うなど、自動化率を向上する設計活動に役立てることができる。 FIG. 14B shows a list 1460 of determination results for each rule as an example of an output screen 1450 of detailed results by assembly process for the assembly process selected from all the assembly processes shown in FIG. 14A. ID 1461, attribute 1462, assembly operation 1463, rule ID 1464, rule item 1465, determination condition 1466, determination value (rule value) 1467, attribute value (value in the target part) 1468, determination result 1469, etc. of the selected process are shown. . By showing the determination result 1469 for each rule ID 1464, it is possible to use for the design activity for improving the automation rate, such as improving the product structure of the rule whose determination result is NG, for the process of determining the automation impossible.
　図１５に、本発明の出力となる組立ライン編成案生成結果の出力画面１５００の一例を示す。出力画面１５００上には、最小組立コストの結果の表１５１０として、自動化率１５１１、人件費１５１２、設備償却費１５１３、組立コスト１５１４などを表示する。また、本発明では、複数の自動化案とその必要作業者数と必要設備数から組立コストを計算した結果を格納している。そこで、最小の組立コストの一覧１５１０を出力すると共に、自動化案の傾向として、自動化率１５２１と人件費１５２２、設備償却費１５２３、組立コスト１５２４の関係を示すグラフ１５２０を出力する。 FIG. 15 shows an example of an output screen 1500 of an assembly line organization plan generation result as an output of the present invention. On the output screen 1500, an automation rate 1511, personnel cost 1512, equipment depreciation cost 1513, assembly cost 1514, and the like are displayed as a table 1510 of the minimum assembly cost result. In the present invention, the result of calculating the assembly cost from a plurality of automation plans, the required number of workers and the required number of facilities is stored. Therefore, a list 1510 of the minimum assembly costs is output, and a graph 1520 indicating the relationship between the automation rate 1521, personnel costs 1522, equipment depreciation costs 1523, and assembly costs 1524 is output as a tendency of the automation plan.
　図１５に示した出力画面１５００において、最小組立コストの結果の表１５１０における組立コスト１５１４が目標値を上回った場合、または組立コスト１５１４について作業者がＮＧと判断した場合には、図１４Ａの組立自動化ルール判定結果の表示画面１４００または、組立工程別詳細結果表示画面１４５０上で、改善すべき工程を抽出する。 In the output screen 1500 shown in FIG. 15, when the assembly cost 1514 in the table 1510 of the result of the minimum assembly cost exceeds the target value, or when the operator determines that the assembly cost 1514 is NG, the assembly shown in FIG. 14A is performed. The process to be improved is extracted on the display screen 1400 of the automated rule determination result or the detailed result display screen 1450 for each assembly process.
　次に、図３Ａに示したような３ＤＣＡＤモデル８００を表示した画面上で、改善すべき工程における改善点を入力し、この改善点を入力したデータに基づいて図２で説明したような処理フローを再実行して、組立コストを再度計算し直して、その結果を図１５の画面に再表示することができる。 Next, on the screen displaying the 3D CAD model 800 as shown in FIG. 3A, the improvement point in the process to be improved is input, and the processing flow as described in FIG. 2 based on the data that has input the improvement point. Can be re-executed to recalculate the assembly cost and the result can be displayed again on the screen of FIG.
　本実施例によれば、製品を構成する複数の部品情報を基に、組立自動化ルールに基づき組立自動化可否を判定し、自動化可能工程を自動から手動に切り替えた組合せによる自動化案生成と、自動化案の必要作業者数と必要設備数から組立コストを計算することで、最小組立コストのライン編成を算出することができる。 According to the present embodiment, based on a plurality of parts information constituting the product, it is determined whether or not assembly automation is possible based on the assembly automation rule, and the automation plan generation by the combination of switching the automatable process from automatic to manual, and the automation plan By calculating the assembly cost from the required number of workers and the required number of facilities, the line organization with the minimum assembly cost can be calculated.
　また、本実施例によれば、製品設計情報を基に工程設計からライン編成決定までを自動算出することが可能となり、設計工数が削減できる。 Further, according to this embodiment, it is possible to automatically calculate from process design to line organization determination based on product design information, and the design man-hours can be reduced.
　本実施例では、組立作業時間を基に組立ライン編成を自動で生成しているが、実際の組立ライン編成においては、部品供給位置や設備トラブル復旧などを想定した、作業者や設備の配置の設計が必要であり、本実施例による自動算出結果に対し、生産技術などの製造有識者によるレイアウト設計が必要となる。本実施例によれば、工程設計からライン編成決定までの期間に対し、レイアウト設計を除いた期間を短縮でき、概ね３０％低減することができる。 In this embodiment, the assembly line organization is automatically generated based on the assembly work time. However, in the actual assembly line organization, the arrangement of workers and equipment is assumed assuming parts supply position and equipment trouble recovery. Design is required, and layout design by manufacturing experts such as production technology is required for the automatic calculation result according to the present embodiment. According to the present embodiment, the period excluding the layout design can be shortened with respect to the period from the process design to the line organization determination, and can be reduced by approximately 30%.
　１・・・組立ライン編成システム　　１００・・・入力部　　２００・・・出力部　　３００・・・制御部　　４００・・・記憶部　　５００・・・通信部　　６００・・・３ＤＣＡＤ装置　　７００・・・ネットワーク　　３１０・・・３ＤＣＡＤモデル情報取得部　　３２０・・・生産条件取得部　　３３０・・・組立工程生成部　　３４０・・・組立自動化判定部　　３５０・・・組立作業時間計算部　　３６０・・・設備引当部　　３７０・・・組立ライン編成生成部　　３８０・・・組立コスト計算部。 DESCRIPTION OF SYMBOLS 1 ... Assembly line organization system 100 ... Input part 200 ... Output part 300 ... Control part 400 ... Memory | storage part 500 ... Communication part 600 ... 3DCAD apparatus 700 ... Network 310 ... 3DCAD model information acquisition unit 320 ... Production condition acquisition unit 330 ... Assembly process generation unit 340 ... Assembly automation judgment unit 350 ... Assembly work time calculation unit 360 ... Equipment allocation unit 370・ ・ Assembly line organization generation part 380 ・ ・ ・ Assembly cost calculation part.

Claims (13)

  1. 　組立対象製品を組み立てるための組立ラインを編成するシステムであって、演算部と、記憶部と、入力部と、出力部とを備え、
    前記演算部は、
    前記記憶部に記憶された組立対象製品の３ＤＣＡＤ情報と生産条件とを取得する情報取得部と、
    該情報取得部で取得した前記組立対象製品の３ＤＣＡＤ情報と前記組立対象製品の生産条件に基づいて組立工程を作成する組立工程生成部と、
    　該組立工程生成部で作成した組立工程における自動化の可否を判定する組立自動化判定部と、
    前記組立工程生成部で作成した組立工程における前記組立対象製品の組立作業時間を求める組立作業時間算出部と、
    　前記組立自動化判定部で自動化の可可能と判定された工程について自動から手動に切り替えた組合せによる複数の自動化案を生成する組立ライン編成生成部と、
    　該組立ライン編成生成部で生成した複数の自動化案について前記組立ラインにおける必要作業者数と必要設備数とを算出して組立コストを算出する組立コスト計算部と
    を備え、
    　前記出力部は、前記演算部で算出した複数の自動化案に対する組立コストの情報を出力する
    ことを特徴とする組立ライン編成システム。     A system for organizing an assembly line for assembling a product to be assembled, comprising a calculation unit, a storage unit, an input unit, and an output unit,
    The computing unit is
    An information acquisition unit for acquiring 3D CAD information and production conditions of the assembly target product stored in the storage unit;
    An assembly process generation unit that creates an assembly process based on the 3D CAD information of the assembly target product acquired by the information acquisition unit and the production conditions of the assembly target product;
    An assembly automation determination unit that determines whether automation is possible in the assembly process created by the assembly process generation unit;
    An assembly work time calculation unit for obtaining an assembly work time of the product to be assembled in the assembly process created by the assembly process generation unit;
    An assembly line organization generation unit for generating a plurality of automation plans by a combination of switching from automatic to manual for the process determined to be possible by the assembly automation determination unit;
    An assembly cost calculation unit that calculates the assembly cost by calculating the number of required workers and the number of necessary facilities in the assembly line for a plurality of automation plans generated by the assembly line organization generation unit,
    The assembly line knitting system, wherein the output unit outputs assembly cost information for a plurality of automation plans calculated by the calculation unit.
  2. 　請求項１記載の組立ライン編成システムであって、前記出力部は、前記演算部で算出した複数の自動化案に対する組立コストの情報として、組立コストが最少となるときの自動化率、人件費、及び設備償却費の情報を出力することを特徴とする組立ライン編成システム。 2. The assembly line organization system according to claim 1, wherein the output unit includes information on assembly costs for a plurality of automation plans calculated by the calculation unit, an automation rate when the assembly cost is minimized, a labor cost, and An assembly line organization system that outputs information on depreciation of equipment.
  3. 　請求項１又は２に記載の組立ライン編成システムであって、前記出力部は、前記演算部で算出した複数の自動化案に対する組立コストの情報を人件費及び設備償却費と関連付けて出力することを特徴とする組立ライン編成システム。 3. The assembly line organization system according to claim 1, wherein the output unit outputs information on assembly costs for a plurality of automation plans calculated by the arithmetic unit in association with personnel costs and equipment depreciation costs. A featured assembly line organization system.
  4. 　請求項３記載の組立ライン編成システムであって、前記出力部は、前記演算部で算出した複数の自動化案に対する組立コストの情報と人件費及び設備償却費とを画面上にグラフで表示することを特徴とする組立ライン編成システム。 4. The assembly line organization system according to claim 3, wherein the output unit displays information on assembly costs, labor costs, and equipment depreciation costs for a plurality of automation plans calculated by the calculation unit in a graph on a screen. An assembly line organization system characterized by
  5. 　請求項１記載の組立ライン編成システムであって、前記出力部は、前記組立自動化判定部で判定した組立工程における自動化可否の判定結果を出力することを特徴とする組立ライン編成システム。 2. The assembly line knitting system according to claim 1, wherein the output unit outputs a determination result of whether or not automation is possible in the assembly process determined by the assembly automation determination unit.
  6. 　組立対象製品を組み立てるための組立ラインを編成する方法であって、
    組立対象製品の３ＤＣＡＤ情報と生産条件とを取得し、
    該取得した前記組立対象製品の３ＤＣＡＤ情報と前記組立対象製品の生産条件に基づいて組立工程を作成し、
    　該作成した組立工程における自動化の可否を判定し、
    前記作成した組立工程における前記組立対象製品の組立作業時間を求め、
    　前記自動化の可否の判定において自動化可能と判定された工程について自動から手動に切り替えた組合せによる複数の自動化案を生成し、
    　該生成した複数の自動化案について前記組立ラインにおける必要作業者数と必要設備数とを算出して組立コストを算出し、
    該算出した複数の自動化案に対する組立コストの情報を出力する
    ことを特徴とする組立ライン編成方法。     A method of organizing an assembly line for assembling a product to be assembled,
    Obtain 3D CAD information and production conditions for the product to be assembled,
    Creating an assembly process based on the acquired 3D CAD information of the assembly target product and the production conditions of the assembly target product;
    Determine whether automation is possible in the created assembly process,
    Finding the assembly work time of the assembly target product in the created assembly process,
    Generating a plurality of automation plans by a combination of switching from automatic to manual for the process determined to be automatic in the determination of whether automation is possible,
    Calculate the required number of workers and the required number of facilities in the assembly line for the generated plurality of automation plans, calculate the assembly cost,
    An assembly line knitting method, wherein information on assembly costs for the plurality of calculated automation plans is output.
  7. 　請求項６記載の組立ライン編成方法であって、前記算出した複数の自動化案に対する組立コストの情報として、組立コストが最少となるときの自動化率、人件費、及び設備償却費の情報を出力することを特徴とする組立ライン編成方法。 7. The assembly line organization method according to claim 6, wherein information on an automation rate, a labor cost, and a facility depreciation cost when the assembly cost is minimized is output as information on the calculated assembly cost for the plurality of automation plans. The assembly line organization method characterized by the above-mentioned.
  8. 　請求項６又は７に記載の組立ライン編成方法であって、前記算出した複数の自動化案に対する組立コストの情報を人件費及び設備償却費と関連付けて出力することを特徴とする組立ライン編成方法。 8. The assembly line organization method according to claim 6 or 7, wherein information on assembly costs for the plurality of calculated automation plans is output in association with personnel costs and equipment depreciation costs.
  9. 　請求項８記載の組立ライン編成方法であって、前記算出した複数の自動化案に対する組立コストの情報と人件費及び設備償却費とを画面上にグラフで表示することを特徴とする組立ライン編成方法。 9. The assembly line organization method according to claim 8, wherein information on assembly costs, labor costs, and equipment depreciation costs for the plurality of automation plans calculated are displayed in a graph on a screen. .
  10. 　請求項６記載の組立ライン編成方法であって、前記組立工程における自動化可否の判定結果を出力することを特徴とする組立ライン編成方法。 7. The assembly line knitting method according to claim 6, wherein the result of determining whether automation is possible in the assembly process is output.
  11. 　組立対象製品を組み立てるための組立ラインを編成する方法であって、
    組立対象製品の３ＤＣＡＤ情報と生産条件とに基づいて組立工程を作成し、
    　該作成した組立工程における複数の自動化案を生成し、
    　該生成した複数の自動化案について前記組立ラインにおける必要作業者数と必要設備数とを算出して組立コストを算出し、
    該算出した複数の自動化案のうちの組立コストが最少となるときの自動化率、人件費、及び設備償却費の情報を出力することを特徴とする組立ライン編成方法。     A method of organizing an assembly line for assembling a product to be assembled,
    Create an assembly process based on 3D CAD information and production conditions of the product to be assembled,
    Generate a plurality of automation plans in the created assembly process,
    Calculate the required number of workers and the required number of facilities in the assembly line for the generated plurality of automation plans, calculate the assembly cost,
    An assembly line knitting method characterized by outputting information on an automation rate, a labor cost, and an equipment depreciation cost when the assembly cost among the plurality of calculated automation plans is minimized.
  12. 　請求項１１記載の組立ライン編成方法であって、前記算出した複数の自動化案に対する組立コストの情報を人件費及び設備償却費と関連付けて出力することを特徴とする組立ライン編成方法。 12. The assembly line organization method according to claim 11, wherein information on assembly costs for the plurality of calculated automation plans is output in association with personnel costs and equipment depreciation costs.
  13. 　請求項１２記載の組立ライン編成方法であって、前記算出した複数の自動化案に対する組立コストの情報と人件費及び設備償却費とを画面上にグラフで表示することを特徴とする組立ライン編成方法。 13. The assembly line organization method according to claim 12, wherein information on assembly costs, labor costs, and equipment depreciation costs for the plurality of automation plans calculated are displayed in a graph on a screen. .
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