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Material handling robots fleet size optimization by a heuristic

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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. | Material handling robots fleet size optimization by a heuristic Journal of Project Management 4 2019 177 188 Contents lists available at GrowingScience Journal of Project Management homepage www.GrowingScience.com Material handling robots fleet size optimization by a heuristic V. K. Chawlaa A. K. Chandab and Surjit Angrac a Department of Mechanical and Automation Engineering Indira Gandhi Delhi Technical University for Women Delhi India b Department of Mechanical and Automation Engineering G.B. Pant Engineering College Delhi India c Department of Mechanical Engineering National Institute of Technology Kurukshetra Haryana India CHRONICLE ABSTRACT Article history The application of material handling robots MHRs has been commonly observed in flexi- Received March 8 2019 ble manufacturing systems FMS for efficient material handling activities. In order to gain Received in revised format maximum throughput minimum tardiness from the minimum investment of funds for the April 2 2019 material handling activities it is important to determine the optimum numbers of MHRs Accepted April 2 2019 Available online required for efficient production of jobs in the FMS. In the present work the requirement of April 4 2019 MHRs is optimized for different FMS layouts by using a heuristic procedure. Initially a Keywords mathematical model is proposed to identify the MHRs requirement to perform the material Fleet size optimization handling activities in the FMS later on the model is optimized by simulating a novel heu- Material handling robots ristic procedure to find the required optimum number of MHRs in the FMS. The proposed Modified memetic particle methodology is found to be generic enough and can also be applied in various industries swarm optimization algorithm employing the MHRs. 2019 by the authors licensee Growing Science Canada. 1. Introduction The flexible manufacturing system FMS consists of flexible reprogrammable highly advanced and accurate computer-controlled .