Optimum Scheduling of a Multi-Machine Flexible Manufacturing System Considering Job and Tool Transfer Times without Tool Delay

Author:

Prayagi Sunil1,Mareddy Padma Lalitha2,Katta Lakshmi Narasimhamu3ORCID,Narapureddy Sivarami Reddy4

Affiliation:

1. Mechanical Engineering Department, Yeshwantrao Chavan College of Engineering, Nagpur 441110, Maharashtra, India

2. Electrical Engineering Department, Annamacharya Institute of Technology and Sciences, Rajampet 516126, Andhra Pradesh, India

3. Mechanical Engineering Department, Mohan Babu University (Erstwhile Sree Vidyanikethan Engineering College), Tirupati 517102, Andhra Pradesh, India

4. Mechanical Engineering Department, Annamacharya Institute of Technology and Sciences, Rajampet 516126, Andhra Pradesh, India

Abstract

In order to minimize makespan (Cmax) without causing tool delay with the fewest copies of each tool type, this study investigates the concurrent scheduling of automated guided vehicles (AGVs), machines (MCs), tool transporter (TT), and tools in a multi-machine flexible manufacturing system (FMS). The tools are housed in a central tool magazine (CTM), accessible to and utilized by several machines. AGVs and the tool transporter (TT) move jobs and tools between machines. Since it involves allocating tool copies and AGVs to job operations, sequencing job operations on machines, and related trip operations, such as AGVs’ and TT’s empty trip and loaded trip times, this simultaneous scheduling problem is highly complicated. This issue is resolved using the symbiotic organisms search algorithm (SOSA), based on the symbiotic interaction strategies that organisms adapt to survive in the ecosystem. This study proposes a mixed nonlinear integer programming formulation to address this problem. Verification is performed using an industrial problem from a manufacturing organization. The results show that employing two copies for two tool types out of 22 tool kinds and one copy for the remaining tool types results in no tool delay, which causes a reduction in the Cmax as well as cost. The industries that can benefit directly from this study are consumer electronics manufacturers, original equipment manufacturers, automobile manufacturers, and textile machine producers. The results demonstrate that the SOSA provides promising results compared to the flower pollination algorithm (FPA).

Publisher

MDPI AG

Subject

General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)

Reference36 articles.

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