JP2007072754A - Method for supporting efficiency of production process - Google Patents

Method for supporting efficiency of production process Download PDF

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JP2007072754A
JP2007072754A JP2005259072A JP2005259072A JP2007072754A JP 2007072754 A JP2007072754 A JP 2007072754A JP 2005259072 A JP2005259072 A JP 2005259072A JP 2005259072 A JP2005259072 A JP 2005259072A JP 2007072754 A JP2007072754 A JP 2007072754A
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production process
worker
simulation
production
simulator
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Mitsuru Nagasaki
充 長崎
Shinichi Daiba
信一 台場
Makoto Saito
誠 齋藤
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Konica Minolta Inc
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Konica Minolta Inc
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    • 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
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    • Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

Abstract

<P>PROBLEM TO BE SOLVED: To optimize personnel arrangement in a production process including manual work in consideration of the fatigue level of a worker and skill level of the worker. <P>SOLUTION: The working circumstance data of a utilization ratio, working hours, a cycle time and efficiency percentage in the work of a production process including manual work are fetched in a production process simulator, so that the database of each working process and each worker are prepared, and the optimization of the personnel arrangement of a production process in consideration of the fatigue level of a worker and the skill level of the worker by performing the simulation of the production process by the production process simulator based on the database. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

本発明は、人手作業を含む生産工程の効率化に関し、生産工程の稼働状況を取り込み生産工程のシミュレーションを行う生産工程シミュレーターを用い、生産工程の人員配置の最適化を行う生産工程効率化支援方法に関する。   The present invention relates to efficiency of a production process including manual work, and a production process efficiency support method for optimizing the personnel allocation of the production process using a production process simulator that captures the operation status of the production process and simulates the production process About.

人手作業を含む複数の生産工程で生産される製品は、複数の作業者による複数の作業により生産される。このような生産工程の効率化を図る手法として、生産工程シミュレーターを用い生産工程のシミュレートを行い、生産工程を最適化する方法が知られている。   A product produced in a plurality of production processes including manual work is produced by a plurality of operations by a plurality of workers. As a method for improving the efficiency of such a production process, a method of simulating a production process using a production process simulator and optimizing the production process is known.

前記生産工程を最適化する方法として、複数の作業者が従事する生産ラインにおける作業負荷のバランスを考慮して組み立て作業の配分を最適化するため、作業者の作業時間と作業者のエネルギー消費量とを考慮して生産工程を設計するシステムが開示されている（例えば、特許文献１参照）。   As a method of optimizing the production process, the work time of the worker and the energy consumption of the worker are optimized in order to optimize the distribution of the assembly work in consideration of the work load balance in the production line where a plurality of workers are engaged. A system for designing a production process in consideration of the above is disclosed (for example, see Patent Document 1).

特許文献１は、作業者の作業時間、エネルギー消費量及び習熟度等の作業者毎の特性データを考慮して生産工程を設計するシステムであるが、一旦作業者の作業時間及びエネルギー消費量等のデータを入力してシミュレートすることで、作業者毎の習熟度は算出されるが、時間の経過に伴う作業者の疲労度及び習熟度の変化が考慮されないため、実稼働工程に対してシミュレーションの最適化結果が乖離する恐れがある。   Patent Document 1 is a system for designing a production process in consideration of characteristic data for each worker such as a worker's working time, energy consumption, and proficiency level. By inputting the above data and simulating, the proficiency level for each worker is calculated, but since changes in worker fatigue level and proficiency level over time are not taken into account, There is a risk that the optimization results of the simulation will be different.

また、生産ラインにおいて、シミュレーターを用いてライン能力を評価し、ボトルネックを割り出し、改善案と改善効果を自動的に提示するシステムが開示されている（例えば、特許文献２参照）。   In addition, a system is disclosed that evaluates line capability using a simulator in a production line, determines bottlenecks, and automatically presents an improvement plan and an improvement effect (for example, see Patent Document 2).

特許文献２に記載のシステムは、一旦作業者の作業時間及びエネルギー消費量等のデータを入力すると作業時間、エネルギー消費量等のパラメータが固定されるため、生産装置及び設備のように時間の経過により生産能力が変化しない生産工程には適用できたが、人手作業を含む生産工程のように人特有の作業による疲労度、習熟度が生じる生産工程の時間的変化が考慮されずシミュレーションが行われるため、時間の経過とともに実稼働工程に対してボトルネックとなる位置にずれが生じ、シミュレーションの最適化結果が乖離する恐れがある。   In the system described in Patent Document 2, parameters such as work time and energy consumption are fixed once data such as the work time and energy consumption of the worker is input. Although it could be applied to production processes where the production capacity does not change due to the above, simulation is performed without taking into account the temporal changes in the production process that cause fatigue and proficiency due to human-specific work such as production processes including manual work Therefore, there is a possibility that the position that becomes a bottleneck with respect to the actual operation process is shifted with time, and the optimization result of the simulation is deviated.

更に、生産ラインの作業工程中の疲労度を評点化し、改善が必要とする場合には疲労度評価点に応じた改善策を行う生産ラインの製造方法が開示されている（例えば、特許文献３参照）。   Furthermore, a manufacturing method for a production line is disclosed in which the degree of fatigue during the work process of the production line is scored, and when improvement is required, an improvement measure corresponding to the fatigue degree evaluation point is taken (for example, Patent Document 3). reference).

特許文献３では、作業者の疲労度は考慮されているが、作業者の習熟度及び時間の経過に伴う作業者の疲労度が考慮されずシミュレーションが行われるため、時間の経過とともに実稼働工程に対してシミュレーションの最適化結果が乖離する恐れがある。   In Patent Literature 3, although the fatigue level of the worker is taken into consideration, the simulation is performed without considering the worker's proficiency level and the worker's fatigue level with the passage of time. However, there is a risk that the optimization results of the simulation will be different.

このように従来は作業者の疲労度及び習熟度の双方を考慮したシミュレーションは存在していないため、人手を含む生産工程でシミュレーションの乖離を防止するのは困難であった。
特開２００４−４６７１３号公報 特開２００２−２４４７１６号公報 特許第３０５９２６４号公報 Thus, conventionally, there is no simulation that takes into consideration both the fatigue level and the proficiency level of the worker, and thus it has been difficult to prevent the divergence of the simulation in the production process including manpower.
JP 2004-46713 A JP 2002-244716 A Japanese Patent No. 3059264

本発明は、上記状況に鑑みなされたもので、人手作業を含む生産工程の効率化において、生産工程のシミュレーションを行う生産工程シミュレーターに稼働状況データを取り込み、生産工程シミュレーターで作業工程及び作業者毎のデータベースを作成するとともに、作業者の疲労度及び作業者の習熟度を評価し、かつ作業者の疲労度及び作業者の習熟度を考慮した生産工程の最適な人員配置を算出し生産工程を最適化する生産工程効率化支援方法を提供することを目的とする。   The present invention has been made in view of the above situation, and in order to improve the efficiency of the production process including manual work, the operation state data is taken into the production process simulator for performing the simulation of the production process. A database for the production process, assessing the fatigue level of the worker and the proficiency level of the worker, and calculating the optimal personnel assignment for the production process considering the fatigue level of the worker and the proficiency level of the worker. An object is to provide a production process efficiency support method to be optimized.

上記目的は、下記の構成により達成される。
（１）
人手作業を含む生産工程の稼働状況を示す稼働状況データを取り込み生産工程のシミュレーションを行う生産工程シミュレーターを有し、前記生産工程シミュレーターを用いて生産工程の効率化を図る生産工程効率化支援方法であって、
前記人手作業を含む生産工程の稼働における、稼働率、作業時間、サイクルタイム及び良品率の稼働状況データを前記生産工程シミュレーターに取り込み、作業工程及び作業者毎のデータベースを作成するとともに、前記データベースに基づき前記生産工程シミュレーターで、生産工程の進行と略同時進行となるリアルタイムで、もしくは生産工程の進行とは別途に進行するオフラインで、生産工程のシミュレーションを行うことで前記作業者の疲労度及び作業者の習熟度を考慮した生産工程の最適な人員配置を算出することを特徴とする生産工程効率化支援方法。
（２）
前記生産工程シミュレーターに稼働状況データを取り込み、シミュレーションを行う際に、取り込んだ前記稼働状況データを前記データベース上に格納されているデータと比較し、作業者の疲労度及び習熟度の評価を行うとともに、前記生産工程のシミュレーションを行うことを特徴とする（１）項に記載の生産工程効率化支援方法。
（３）
生産工程に生産工程内の作業者に情報伝達する情報伝達手段を有し、前記情報伝達手段で前記生産工程シミュレーターでのシミュレーションの結果を前記作業者に伝達するとともに、前記作業者は、伝達された前記シミュレーションの結果に基づき人員配置の変更と生産工程に配設された生産機器の稼働条件を設定する前記生産機器のパラメータの変更の一方または両方を実施することを特徴とする（１）項または（２）項に記載の生産工程効率化支援方法。
（４）
前記生産機器のパラメータの変更は、前記シミュレーションの結果に基づき前記生産機器に対し自動的に行われることを特徴とする（３）項に記載の生産工程効率化支援方法。
（５）
前記稼働状況データの取り込み、前記シミュレーション及び該シミュレーションの結果に基づく人員配置の変更と前記パラメータの変更の一方または両方の実施を所定周期毎に繰り返すことを特徴とする（１）項乃至（４）項の何れか１項に記載の生産工程効率化支援方法。 The above object is achieved by the following configuration.
(1)
A production process efficiency support method that has a production process simulator that captures operational status data indicating the operational status of a production process including manual labor, and simulates the production process, and uses the production process simulator to improve the efficiency of the production process. There,
In the operation of the production process including the manual operation, the operation rate data of the operation rate, work time, cycle time and non-defective product rate is taken into the production process simulator, and a database for each work process and worker is created, and the database Based on the production process simulator, the worker's fatigue level and work can be performed by simulating the production process in real time which is almost simultaneous with the progress of the production process, or offline which is separate from the progress of the production process. A production process efficiency support method characterized by calculating an optimum staffing of a production process in consideration of a person's proficiency level.
(2)
When the operation status data is captured in the production process simulator and the simulation is performed, the captured operation status data is compared with the data stored in the database, and the fatigue level and proficiency level of the worker are evaluated. The production process efficiency support method according to item (1), wherein the production process is simulated.
(3)
The production process has information transmission means for transmitting information to the worker in the production process, and the information transmission means transmits the result of the simulation in the production process simulator to the worker, and the worker is transmitted. (1) The method is characterized in that one or both of a change in personnel assignment and a change in the parameters of the production equipment for setting the operating conditions of the production equipment arranged in the production process are implemented based on the simulation result. Or the production process efficiency support method as described in (2) term.
(4)
The production process efficiency support method according to (3), wherein the parameter change of the production equipment is automatically performed on the production equipment based on the result of the simulation.
(5)
(1) to (4), wherein one or both of the operation status data fetching, the simulation, and the change of the personnel assignment based on the result of the simulation and the change of the parameter are repeated at predetermined intervals. The production process efficiency support method according to any one of the items.

上記構成により、人手作業を含む生産工程の効率化を行うための生産工程シミュレーションにおいて、人特有の時間の経過に伴う作業者の疲労度及び習熟度（学習による多能工化）を考慮して生産工程のシミュレーションを行うことで、実稼働生産工程に対し時間的誤差因子が少ない最適な人員配置を算出することが可能となり、また前記最適な人員配置を生産工程に適用することで生産工程の作業の均一化を図ることができ、生産工程の効率化を図ることができる。   With the above configuration, in the production process simulation for improving the efficiency of the production process including manual work, taking into consideration the fatigue level and proficiency level of the worker with the passage of time peculiar to humans (multifunctionalization through learning) By simulating the production process, it is possible to calculate the optimal personnel assignment with less time error factor compared to the actual production process, and by applying the optimal personnel assignment to the production process, The work can be made uniform, and the production process can be made more efficient.

以下、図を参照しながら本発明の実施の形態を説明するが、本発明はこれに限定されるものではない。   Hereinafter, embodiments of the present invention will be described with reference to the drawings, but the present invention is not limited thereto.

図１は、本実施の形態の生産工程効率化支援方法の構成を示すブロック図である。図１において、人手作業を含む生産工程（以下、人手生産工程とも略す）１は、製品を生産する生産工程である。稼働状況データ２は、人手生産工程１の稼働率、サイクルタイム、作業時間及び良品率の稼働状況データであり、生産工程シミュレーター３に取り込まれる。生産工程シミュレーター３は取り込まれた稼働状況データ２を基に作業工程及び作業者毎のデータベースを作成し、既存のデータベース４を更新する。   FIG. 1 is a block diagram showing the configuration of the production process efficiency support method of the present embodiment. In FIG. 1, a production process including manual work (hereinafter also abbreviated as manual production process) 1 is a production process for producing a product. The operation status data 2 is operation status data of the operation rate, cycle time, work time, and non-defective product rate of the manual production process 1 and is taken into the production process simulator 3. The production process simulator 3 creates a database for each work process and worker based on the captured operation status data 2 and updates the existing database 4.

また、生産工程シミュレーター３はデータベース４に基づいて作業者の疲労度及び習熟度の評価を行うとともに、前記評価を考慮に入れた生産工程のシミュレーションを行い生産工程の最適な人員配置を算出する。前記生産工程のシミュレーションにおける生産工程の最適な人員配置の算出時に、必要に応じて生産工程に配設された生産機器の稼働条件を設定する前記生産機器のパラメータが同時に算出される。生産工程シミュレーター３は図示しないコンピューターにより実行される。   Further, the production process simulator 3 evaluates the fatigue level and proficiency level of the worker based on the database 4, and calculates the optimum personnel allocation of the production process by performing a simulation of the production process taking the evaluation into consideration. When calculating the optimal personnel allocation of the production process in the simulation of the production process, the parameters of the production equipment for setting the operating conditions of the production equipment arranged in the production process are simultaneously calculated as necessary. The production process simulator 3 is executed by a computer (not shown).

前記シミュレーションによる生産工程の最適な人員配置は、情報伝達手段５により作業者に伝達され、作業者は人手生産工程１の人員配置を変更する。また、前記生産機器の前記パラメータは、生産機器の表示部６に表示され、作業者は前記パラメータを変更して生産工程の効率化を図る。前記パラメータの変更は、作業者を介さず自動で行うこともできる。   The optimal personnel allocation of the production process by the simulation is transmitted to the worker by the information transmission means 5, and the worker changes the personnel allocation of the manual production process 1. The parameters of the production equipment are displayed on the display 6 of the production equipment, and the operator changes the parameters to improve the efficiency of the production process. The parameter can be changed automatically without an operator.

図２は、図１に示す生産工程効率化支援方法を用いて生産工程の人員配置を最適化する場合のワークフローを示す。また、生産機器のパラメータの算出及び変更は、必要に応じて実施されるが、図２のワークフローは、生産機器のパラメータの算出及び変更が実施される場合の例を示している。   FIG. 2 shows a workflow for optimizing the staffing of the production process using the production process efficiency improvement support method shown in FIG. Further, the calculation and change of the parameters of the production equipment are performed as necessary, but the workflow in FIG. 2 shows an example in which the calculation and change of the parameters of the production equipment are executed.

最初にステップＳ０１で人手生産工程１の稼働が開始されると同時にステップＳ０５で生産工程シミュレーター３が稼働開始する。次にステップＳ０２で人手生産工程１が稼働継続状態となる。次にステップＳ０６で人手生産工程１から稼働率、サイクルタイム、作業時間及び良品率の稼働状況データ２が、オンラインで生産工程シミュレーター３に取り込まれる。次にステップＳ０７で生産工程シミュレーター３は、取り込まれた稼働状況データ２を基に作業工程及び作業者毎のデータベースを作成し、データベース４を更新する。   First, the operation of the manual production process 1 is started in step S01, and at the same time, the production process simulator 3 is started in step S05. Next, in step S02, the manual production process 1 is in an operation continuation state. Next, in step S06, the operation rate data 2 of the operation rate, cycle time, work time, and non-defective rate from the manual production process 1 is taken into the production process simulator 3 online. Next, in step S07, the production process simulator 3 creates a database for each work process and worker based on the fetched operation status data 2, and updates the database 4.

次にステップＳ０８で生産工程シミュレーター３は、データベース４に基づき作業者の疲労度及び習熟度を評価する。   Next, in step S08, the production process simulator 3 evaluates the fatigue level and proficiency level of the worker based on the database 4.

ステップＳ０９では、データベース４及びステップＳ０８での評価に基づき生産工程のシミュレーションを実施し、生産工程の最適な人員配置及び生産機器のパラメータを算出する。   In step S09, a simulation of the production process is performed based on the database 4 and the evaluation in step S08, and the optimal personnel allocation of the production process and parameters of the production equipment are calculated.

ステップＳ０９における生産工程のシミュレーションの実施において、生産工程シミュレーターを実行するコンピューターの処理能力が十分に有る場合には、生産工程のシミュレーションの進行を、人手生産工程１の進行と略同時進行となるリアルタイムで実行することが好ましい。これにより、人手生産工程１の進行と生産工程シミュレーター３による生産工程のシミュレーションの進行との時間的誤差を減少させることができ、より人手生産工程１の進行に即した生産工程の最適化ができる。しかしながら、前記コンピューターの処理能力等の関係から前述のようなリアルタイムでの実行が困難な場合には、人手生産工程１の進行とは別途に生産工程のシミュレーションの進行を実行させることも可能である。但し、リアルタイムでの実行に比較し前記時間的誤差は増加する。   In the simulation of the production process in step S09, if the computer that executes the production process simulator has sufficient processing capability, the simulation of the production process is performed substantially simultaneously with the progress of the manual production process 1. Is preferably performed. Thereby, the time error between the progress of the manual production process 1 and the progress of the simulation of the production process by the production process simulator 3 can be reduced, and the production process can be further optimized in accordance with the progress of the manual production process 1. . However, if it is difficult to execute in real time as described above due to the processing capacity of the computer, it is possible to execute the simulation of the production process separately from the progress of the manual production process 1. . However, the time error increases as compared with execution in real time.

図２のワークフローに戻り、ステップＳ１０では、ステップＳ０９で算出した生産工程の最適な人員配置を情報伝達手段５に表示し、作業者に伝達する。情報伝達手段５の表示は、生産工程内に設けられたディスプレイ、プリンター等のハードコピー装置、音声装置等で行うことができる。次に、ステップＳ１１では、ステップＳ０９で算出した生産機器のパラメータを各生産機器の表示装置のディスプレイ等に表示する。   Returning to the workflow of FIG. 2, in step S10, the optimal personnel assignment of the production process calculated in step S09 is displayed on the information transmission means 5 and transmitted to the worker. The information transmission means 5 can be displayed by a display provided in the production process, a hard copy device such as a printer, an audio device, or the like. Next, in step S11, the parameters of the production equipment calculated in step S09 are displayed on the display of the display device of each production equipment.

次にステップＳ０３で、ステップＳ１０で作業者に伝達された最適な人員配置の情報に基づき、作業者は人員配置の変更を実施する。次に、ステップＳ０４で、ステップＳ１１で作業者に伝達された生産機器のパラメータに基づき、各生産機器パラメータの変更を実施する。前記ステップＳ０３及びステップＳ０４の実施順序は、逆にまたは同時に実施しても良い。更に、図２には図示しないが、前述のようにステップＳ０４の生産機器のパラメータの変更は、作業者を介さず自動で行うこともできる。この場合には、作業者の作業を減少させることができ、省力化の点で好ましい。   Next, at step S03, the worker changes the personnel assignment based on the information on the optimum personnel assignment transmitted to the worker at step S10. Next, in step S04, each production equipment parameter is changed based on the production equipment parameters transmitted to the worker in step S11. The order of performing Step S03 and Step S04 may be reversed or simultaneously. Further, although not shown in FIG. 2, as described above, the change of the parameters of the production device in step S04 can be automatically performed without involving the operator. In this case, the operator's work can be reduced, which is preferable in terms of labor saving.

上記により、人手生産工程１の人員配置の変更及び生産機器のパラメータの変更が行われ、ステップＳ０２で人手生産工程１の稼働が継続される。   As described above, the personnel allocation change and the production equipment parameter change in the manual production process 1 are performed, and the operation of the manual production process 1 is continued in step S02.

図２のワークフローに示す一連の稼働状況データ取り込みから人員配置までを所定周期毎に繰り返すことで、人手生産工程１の人員配置を常時最適な人員配置にすることができる。   By repeating a series of operation status data fetching to personnel allocation shown in the workflow of FIG. 2 at predetermined intervals, the personnel allocation in the manual production process 1 can always be the optimal personnel allocation.

上記により、人特有の時間の経過に伴う作業者の疲労度及び習熟度（学習による多能工化）を考慮して生産工程のシミュレーションを行うことで、実稼働生産工程に対し時間的誤差因子が少ない最適な人員配置を算出することが可能となり、また前記最適な人員配置を生産工程に適用することで生産工程の作業の均一化を図ることができ、生産工程の効率化を図ることができる。また、作業者の入れ替わりの多いような場合においても疲労度及び習熟度を考慮することにより、より実稼働生産工程に即した生産工程シミュレーションが可能になる。   Based on the above, the time error factor for the actual production process is simulated by simulating the production process taking into account the worker's fatigue and proficiency (multifunctionality through learning) over time. It is possible to calculate the optimal personnel assignment with a small amount, and by applying the optimum personnel assignment to the production process, the work of the production process can be made uniform and the production process can be made more efficient. it can. Further, even in the case where workers are frequently replaced, the production process simulation more suitable for the actual production process can be performed by considering the fatigue level and the proficiency level.

本発明に係る生産工程効率化支援方法のブロック図である。It is a block diagram of a production process efficiency improvement support method according to the present invention. 生産工程効率化支援方法での人員配置最適化のワークフロー図である。It is a workflow figure of personnel allocation optimization in a production process efficiency improvement support method.

符号の説明Explanation of symbols

１ 人手作業を含む生産工程
２ 稼働状況データ
３ 生産工程シミュレーター
４ データベース
５ 情報伝達手段
６ 生産機器表示部 1 Production process including manual work 2 Operation status data 3 Production process simulator 4 Database 5 Information transmission means 6 Production equipment display section

Claims (5)

人手作業を含む生産工程の稼働状況を示す稼働状況データを取り込み生産工程のシミュレーションを行う生産工程シミュレーターを有し、前記生産工程シミュレーターを用いて生産工程の効率化を図る生産工程効率化支援方法であって、
前記人手作業を含む生産工程の稼働における、稼働率、作業時間、サイクルタイム及び良品率の稼働状況データを前記生産工程シミュレーターに取り込み、作業工程及び作業者毎のデータベースを作成するとともに、前記データベースに基づき前記生産工程シミュレーターで、生産工程の進行と略同時進行となるリアルタイムで、もしくは生産工程の進行とは別途に進行するオフラインで、生産工程のシミュレーションを行うことで前記作業者の疲労度及び作業者の習熟度を考慮した生産工程の最適な人員配置を算出することを特徴とする生産工程効率化支援方法。 A production process efficiency support method that has a production process simulator that captures operational status data indicating the operational status of a production process including manual labor, and simulates the production process, and uses the production process simulator to improve the efficiency of the production process. There,
In the operation of the production process including the manual operation, the operation rate data of the operation rate, work time, cycle time and non-defective product rate is taken into the production process simulator, and a database for each work process and worker is created, and the database Based on the production process simulator, the worker's fatigue level and work can be performed by simulating the production process in real time which is almost simultaneous with the progress of the production process, or offline which is separate from the progress of the production process. A production process efficiency support method characterized by calculating an optimum staffing of a production process in consideration of a person's proficiency level. 前記生産工程シミュレーターに稼働状況データを取り込み、シミュレーションを行う際に、取り込んだ前記稼働状況データを前記データベース上に格納されているデータと比較し、作業者の疲労度及び習熟度の評価を行うとともに、前記生産工程のシミュレーションを行うことを特徴とする請求項１に記載の生産工程効率化支援方法。 When the operation status data is captured in the production process simulator and the simulation is performed, the captured operation status data is compared with the data stored in the database, and the fatigue level and proficiency level of the worker are evaluated. The production process efficiency support method according to claim 1, wherein simulation of the production process is performed. 生産工程に生産工程内の作業者に情報伝達する情報伝達手段を有し、前記情報伝達手段で前記生産工程シミュレーターでのシミュレーションの結果を前記作業者に伝達するとともに、前記作業者は、伝達された前記シミュレーションの結果に基づき人員配置の変更と生産工程に配設された生産機器の稼働条件を設定する前記生産機器のパラメータの変更の一方または両方を実施することを特徴とする請求項１または２に記載の生産工程効率化支援方法。 The production process has information transmission means for transmitting information to an operator in the production process, and the information transmission means transmits the result of the simulation in the production process simulator to the worker, and the worker is transmitted. The method according to claim 1, wherein one or both of a change in personnel assignment and a change in parameters of the production equipment for setting operating conditions of the production equipment arranged in a production process are performed based on the simulation result. 2. The production process efficiency support method according to 2. 前記生産機器のパラメータの変更は、前記シミュレーションの結果に基づき前記生産機器に対し自動的に行われることを特徴とする請求項３に記載の生産工程効率化支援方法。 4. The production process efficiency support method according to claim 3, wherein the change of the parameter of the production device is automatically performed on the production device based on the result of the simulation. 前記稼働状況データの取り込み、前記シミュレーション及び該シミュレーションの結果に基づく人員配置の変更と前記パラメータの変更の一方または両方の実施を所定周期毎に繰り返すことを特徴とする請求項１乃至４の何れか１項に記載の生産工程効率化支援方法。 5. The method according to claim 1, wherein one or both of taking in the operation status data, changing the personnel assignment based on the simulation and the result of the simulation, and changing the parameter are repeated at predetermined intervals. The production process efficiency support method according to Item 1.
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2018205818A (en) * 2017-05-30 2018-12-27 ファナック株式会社 Work supply system

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH1034499A (en) * 1996-07-23 1998-02-10 Hitachi Ltd Capacity information gathering method for production facility and production control system
JPH11300585A (en) * 1998-04-16 1999-11-02 Nec Corp Production control system
JP2002006934A (en) * 2000-06-27 2002-01-11 Matsushita Electric Works Ltd Worker allocation adjustment method on production line and its system
JP2004138555A (en) * 2002-10-18 2004-05-13 Seiko Epson Corp Measurement support method, manufacture support system, measurement support device, and program for measurement support method

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH1034499A (en) * 1996-07-23 1998-02-10 Hitachi Ltd Capacity information gathering method for production facility and production control system
JPH11300585A (en) * 1998-04-16 1999-11-02 Nec Corp Production control system
JP2002006934A (en) * 2000-06-27 2002-01-11 Matsushita Electric Works Ltd Worker allocation adjustment method on production line and its system
JP2004138555A (en) * 2002-10-18 2004-05-13 Seiko Epson Corp Measurement support method, manufacture support system, measurement support device, and program for measurement support method

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2018205818A (en) * 2017-05-30 2018-12-27 ファナック株式会社 Work supply system
US10384880B2 (en) 2017-05-30 2019-08-20 Fanuc Corporation Workpiece supply system

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