著者

中谷 圭佑 岩村 幸治 谷水 義隆 杉村 延広

出版者

公益社団法人 精密工学会

雑誌

精密工学会学術講演会講演論文集

巻号頁・発行日

vol.2009, pp.983-984, 2009

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本研究では,加工フロアにおいて手動工作機械を用いて加工作業を行う作業者の勤務スケジューリングについて検討する.本研究の特徴として,作業者の休日に対する希望を考慮してスケジューリングを行う.そのため,作業者が希望する休日と実際の休日が一致する日数の最大化を目的関数,制約条件を労働基準法で定められた勤務日数および要求生産量を満たすための各日の作業者数とし,整数計画問題として勤務スケジュールを作成する.

著者

NGUYEN QUANG Thinh 岩村 幸治 杉村 延広 浦出 俊和 竹歳 一紀 香川 文庸 平原 嘉幸 木下 泰宏

出版者

一般社団法人 日本機械学会

雑誌

日本機械学会論文集 (ISSN:21879761)

巻号頁・発行日

pp.18-00220, (Released:2019-02-26)

参考文献数

17

被引用文献数

1

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Much emphasis is now being given to research and development of plant factories which daily produce a large volume of high-quality vegetables under artificially controlled environments. One of the important issues to be considered for the management and the daily operations of the plant factories is to find a set of suitable customers and/or markets to which the daily produced vegetables are sold and delivered. The current wholesale markets of the vegetables are not suitable for trading the high-quality vegetables produced by the plant factories, therefore, a new market is required to sell and to buy the products made by the plant factories. A new trading market system is proposed, to sell and to buy the lettuces supplied by the plant factories, based on the stock exchange mechanisms, in this paper. An estimation method of yield rate is also proposed to generate a suitable volume of sales for the plant factories. Some case studies have been carried out to verify the effectiveness of the proposed trading market.

著者

岩村 幸治 眞弓 宗久 谷水 義隆 杉村 延広

出版者

THE INSTITUTE OF SYSTEMS, CONTROL AND INFORMATION ENGINEERS (ISCIE)

雑誌

システム制御情報学会論文誌 (ISSN:13425668)

巻号頁・発行日

vol.26, no.4, pp.129-137, 2013 (Released:2013-07-15)

参考文献数

15

被引用文献数

1 1

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Autonomous Distributed Manufacturing Systems (ADMS) have been proposed to realize flexible control structures of manufacturing systems. In the previous researches, a real-time scheduling method based on utility values has been proposed and appliedto the ADMS. In the proposed method, all the job agents and the resource agents evaluate the utility values for the cases where the agent selects the individual candidate agents for the next machining operations. Multi-agent reinforcement learning is newly proposed and implemented to the job agents and resource agents, in order to improve their coordination processes. In the reinforcement learning method, an agent must be able to sense the status of the environment to some extent and must be able to takeactions that affect the status. The agent also must have a goal or goals relating to the status of the environment. The status, the action and the reward are defined for the individual job agents and the resource agents to evaluate the suitable utility values based on the status of the ADMS.