A hybrid FAHP–entropy–TOPSIS model for selecting the facility layout in small-scale manufacturing

The strategic layout of a facility is crucial for achieving optimal productivity, operational efficiency, and ergonomic functionality in manufacturing systems. The availability of resources on the shop floor has a direct impact on how effectively each industry performs its tasks. The current study proposes a combined approach for selecting the optimal layout design from several options for a specific small-scale manufacturing industry. To achieve this, authors employed the FAHP to make decisions in the presence of uncertainty, the Entropy method to assign objective weights to different criteria, and the TOPSIS method to rank design options based on their proximity to the ideal solution. Five different facility layout designs were evaluated, with three qualitative factors examined: layout flexibility, shop floor utilisation, and ergonomics. The method is designed for use in a car parts manufacturing company that has experienced operational bottlenecks and poor shop floor layout for years. The people in charge, as well as the industry management, were unsatisfied with the setup. The results show that Layout 5 is superior to the others because it can be modified and outperforms all the other criteria used to evaluate it. The current study provides a comprehensive model to help small-scale industries, which are often at the bottom of the industrial hierarchy, transition from simple methods to more advanced ones in making decisions about layout design.

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Publication Details

Journal
Frontiers in Mechanical Engineering
Published
2025-09-29
DOI
https://doi.org/10.3389/fmech.2025.1666571
Citations
2
Primary Topic
Advanced Manufacturing and Logistics Optimization
Type
article
Field-Weighted Citation Impact
2.48
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article

A hybrid FAHP–entropy–TOPSIS model for selecting the facility layout in small-scale manufacturing

Saneh Lata Yadav, Parveen Sharma, Kashmir Singh Ghatorha, Vladimíra Schindlerová et al.
2 citations
Frontiers in Mechanical Engineering
Advanced Manufacturing and Logistics Optimization
2.48
article

A hybrid FAHP–entropy–TOPSIS model for selecting the facility layout in small-scale manufacturing

Saneh Lata Yadav, Parveen Sharma, Kashmir Singh Ghatorha, Vladimíra Schindlerová, Rakesh Kumar Phanden, Lenka Čepová, Ajay Kumar, Neil Ray
article en
2 citations

Abstract

The strategic layout of a facility is crucial for achieving optimal productivity, operational efficiency, and ergonomic functionality in manufacturing systems. The availability of resources on the shop floor has a direct impact on how effectively each industry performs its tasks. The current study proposes a combined approach for selecting the optimal layout design from several options for a specific small-scale manufacturing industry. To achieve this, authors employed the FAHP to make decisions in the presence of uncertainty, the Entropy method to assign objective weights to different criteria, and the TOPSIS method to rank design options based on their proximity to the ideal solution. Five different facility layout designs were evaluated, with three qualitative factors examined: layout flexibility, shop floor utilisation, and ergonomics. The method is designed for use in a car parts manufacturing company that has experienced operational bottlenecks and poor shop floor layout for years. The people in charge, as well as the industry management, were unsatisfied with the setup. The results show that Layout 5 is superior to the others because it can be modified and outperforms all the other criteria used to evaluate it. The current study provides a comprehensive model to help small-scale industries, which are often at the bottom of the industrial hierarchy, transition from simple methods to more advanced ones in making decisions about layout design.

Frontiers in Mechanical EngineeringVol. 11
Lovely Professional University (IN), VSB - Technical University of Ostrava (CZ), Guru Teg Bahadur Hospital (IN), KR Mangalam University (IN), Central Queensland University (AU), University of Rajasthan (IN)
Openalex Percentile: Top 9%
Advanced Manufacturing and Logistics Optimization
2.48
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