Material handling robots fleet size optimization by a heuristic

IF 1.3 Q4 ENGINEERING, INDUSTRIAL Journal of Project Management Pub Date : 1900-01-01 DOI:10.5267/J.JPM.2019.4.002

V. Chawla, A. Chanda, Surjit Angra

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引用次数: 11

Abstract

Article history: Received: March 8 2019 Received in revised format: April 2 2019 Accepted: April 2 2019 Available online: April 4 2019 The application of material handling robots (MHRs) has been commonly observed in flexible manufacturing systems (FMS) for efficient material handling activities. In order to gain maximum throughput, minimum tardiness from the minimum investment of funds for the material handling activities, it is important to determine the optimum numbers of MHRs required for efficient production of jobs in the FMS. In the present work, the requirement of MHRs is optimized for different FMS layouts by using a heuristic procedure. Initially, a mathematical model is proposed to identify the MHRs requirement to perform the material handling activities in the FMS, later on, the model is optimized by simulating a novel heuristic procedure to find the required optimum number of MHRs in the FMS. The proposed methodology is found to be generic enough and can also be applied in various industries employing the MHRs. © 2019 by the authors; licensee Growing Science, Canada.

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基于启发式算法的物料搬运机器人车队规模优化

文章历史:接收:2019年3月8日接收:修订格式:2019年4月2日接收:2019年4月2日在线提供:2019年4月4日材料搬运机器人(mhr)的应用已在柔性制造系统(FMS)中普遍观察到，以实现高效的材料搬运活动。为了在物料处理活动中以最小的资金投入获得最大的吞吐量，最小的延迟，确定FMS中有效生产作业所需的最佳mhr数量是很重要的。在本工作中，采用启发式方法对不同FMS布局的mhr要求进行了优化。首先，提出了一个数学模型来确定在FMS中执行物料搬运活动所需的mhr，然后，通过模拟一种新的启发式过程来优化模型，以找到FMS中所需的最佳mhr数量。所提出的方法被认为是足够通用的，也可以应用于采用MHRs的各种行业。©2019作者所有;加拿大Growing Science公司

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