Title: Machine cell formation and part family identification by combined algorithm

Authors: M. Shunmugasundaram; R. Kamalakannan; V. Anbumalar; D. Maneiah

Addresses: Department of Mechanical Engineering, CMR Technical Campus, Hyderabad, 501401, Telangana, India ' Department of Mechanical Engineering, M. Kumarasamy College of Engineering, Karur, 639113, Tamilnadu, India ' Department of Mechanical Engineering, Velammal College of Engineering and Technology, Madurai, 625009, Tamilnadu, India ' Department of Mechanical Engineering, CMR Technical Campus, Hyderabad, 501401, Telangana, India

Abstract: Two major problems in the cell manufacturing process are machine cell formation and component family identification. A combined algorithm is proposed in this paper to improve the cellular production system. The aim of this algorithm is to maximise the effectiveness of grouping and efficacy of grouping to reduce the part's travel time and increase production. Grouping efficiency and grouping efficacy are the two most widely utilised measures of quality for the proposed cellular manufacturing systems. The proposed method integrates appropriate production data to shape the device cell and classify the component unit, compared to the well-known approaches. The combined algorithm is increased the grouping efficiency at maximum of 30.85% and it is maximising the grouping efficacy at the maximum of 5%. It will reduce the total travelling time of parts and increase the machine utilisation.

Keywords: machine cell; part family; cellular manufacturing system; CMS; combined algorithm; grouping efficiency; grouping efficacy.

DOI: 10.1504/PIE.2020.113421

Progress in Industrial Ecology, An International Journal, 2020 Vol.14 No.3/4, pp.200 - 211

Received: 07 Dec 2019
Accepted: 17 Apr 2020
Published online: 04 Mar 2021 *

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