Title: Revolutionising facility layout: a case study of dynamic facility layout in cable production

Authors: G.R. Vineetha; Shiyas Chekkot Rasheedali

Addresses: Division of Computer Science and Engineering, Department of Mechanical Engineering, Cochin University College of Engineering, CUSAT, Kuttanadu, Alappuzha, Kerala, India ' Division of Computer Science and Engineering, Department of Mechanical Engineering, Cochin University College of Engineering, CUSAT, Kuttanadu, Alappuzha, Kerala, India

Abstract: In the competitive landscape of globalised markets, businesses must prioritise cost reduction for sustained competitiveness. This study delves into the dynamic facility layout problem (DFLP) within a cable production company in Kerala, emphasising adaptability to changing production demands. Addressing material handling costs and rearrangement expenses, the research evaluates the efficacy of the current static layout and explores the benefits of transitioning to a dynamic layout. The case study reveals potential cost savings through the strategic restructuring of machine arrangements. The innovative machine learning-based genetic algorithm (ML-GA) integrates machine learning algorithms, genetic algorithms, and a local search method, offering a cutting-edge solution to dynamic facility layout challenges. By considering demand variability and relocation costs, the study provides insights for informed decision-making, emphasising the significance of material flow patterns. This research contributes to enhancing efficiency and profitability, providing practical implications for businesses navigating the complexities of modern manufacturing.

Keywords: quadratic assignment problem; QAP; dynamic facility layout problem; DFLP; machine learning; k-means clustering; pair-wise exchange local search; genetic algorithm; GA.

DOI: 10.1504/IJWET.2024.142216

International Journal of Web Engineering and Technology, 2024 Vol.19 No.3, pp.267 - 309

Received: 30 Dec 2023
Accepted: 28 May 2024
Published online: 14 Oct 2024 *

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