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https://dspace.iiti.ac.in/handle/123456789/7180
Title: | Sustainability formation of machine cells in group technology systems using modified artificial bee colony algorithm |
Authors: | Paulraj, Maheandera Prabu |
Keywords: | artificial neural network;computer simulation;equipment component;genetic algorithm;machinery;manufacturing;operations technology;parameterization;sustainability;Apoidea |
Issue Date: | 2018 |
Publisher: | MDPI |
Citation: | Arunagiri, A., Marimuthu, U., Gopalakrishnan, P., Slota, A., Zajac, J., & Paulraj, M. P. (2018). Sustainability formation of machine cells in group technology systems using modified artificial bee colony algorithm. Sustainability (Switzerland), 10(1) doi:10.3390/su10010042 |
Abstract: | The efficiency and sustainability of a cellular manufacturing system (CMS) in batch type manufacturing is highly valued. This is done using a systematic method of equipment into machine cells, and components into part families, based on the suitable similar criteria. The present work discusses the cell formation problem, with the objective of minimizing the cumulative cell load variation and cumulative intercellular moves. The quantity of parts, operation sequences, processing time, capacity of machines, and workload of machineries were considered as parameters. For the grouping of equipment, the modified artificial bee colony (MABC) algorithm is considered. The computational procedure of this approach is explained by using up to 40 machines and 100 part types. The result obtained from MABC is compared with the findings acquired from the genetic algorithm (GA) and ant colony system (ACS) in the literature. © 2017 by the authors. |
URI: | https://doi.org/10.3390/su10010042 https://dspace.iiti.ac.in/handle/123456789/7180 |
ISSN: | 2071-1050 |
Type of Material: | Journal Article |
Appears in Collections: | Department of Mechanical Engineering |
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