CASE STUDY OF THE OPTIMIZING THE AUTOMOTIVE MANUFACTURING SYSTEMS EFFICIENCY VIA APPLYING NEW METHOD OF SCHEDULING
- 1 The University of Toledo, USA
Copyright: © 2020 Seyedehfarzaneh Nojabaei and Matthew Franchetti. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Efficiency is becoming a pivotal aspect in each manufacturing system and scheduling plays a crucial role in sustaining it. The applicability of distributed computing to coordinate and execute jobs has been investigated in the past literature. Moreover, it is significant that even for sensitive industrial systems the only criterion of allocating jobs to appropriate machines is the FIFO policy. On the other flip, many researchers are of the opinion that the main reason behind failing to provide fairness in distributed systems is considering the only criterion of time stamp to judge upon and form the queue of jobs with the aim of allocating those jobs to the machines. In order to increase the efficiency of sensitive industrial system, this study takes into consideration of three criteria of each job including priority, time action and time stamp. The methodology adopted by this study is definition of job scheduler and positioning jobs in temporary queue and sorting via developing bubble sort. In sorting algorithm criterion of priority, time action should be considered besides time stamp to recognize the tense jobs for processing earlier. To evaluate this algorithm first a numerical test case (simulation) is programmed and then the case study performing in order to optimize efficiency of applying this method in real manufacturing system. Eventually the results of this study provided evidence on that the rate of efficiency is increased.
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- Automotive Manufacturing Systems
- Distributed Control System