A fuzzy analytic hierarchy process approach for optimal selection of manufacturing layout

• Main Authors: Esmeria, Giselle Joy C., Promentilla, Michael Angelo B., Bacudio, Lindley R.
• Format: text
• Published: Animo Repository 2016
• Subjects: Plant layout; Fuzzy analytic hierarchy process; Multiple criteria decision making
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/10026
• Institution: De La Salle University

Selection of the right layout design is critical in any manufacturing company. With the right layout design, productivity can increase, lead time and non-value added operations can be minimized, and flow of materials can be streamlined. Proper arrangement of departments and machines directly contributes to the reduction of material handling cost and improvement of overall efficiency. Manufacturing layout requires large capital investment and long-term planning horizon and costs cannot be avoided if modification of an existing layout is necessary. In this study, the fuzzy Analytic Hierarchy Process (FAHP) is thus applied in the selection of the best manufacturing layout that integrates both quantitative and qualitative criteria in the decision structure. AHP is a widely used multi-criteria decision analysis that decomposes the decision problem in a hierarchical structure and derives priorities from the value judgment of individual or a group in decision making. However, the conventional method of AHP has limitation in addressing the vagueness of subjective judgment. Variant of Fuzzy AHP was thus developed and applied to model the vagueness of judgment by representing the verbal scale in terms of fuzzy numbers. To illustrate the method, a case study was conducted in a company located in Cavite which manufactures bolo knives. Layout alternatives were generated using Systematic Layout Planning (SLP). The criteria used for the decision model are productivity, initial investment, flexibility and ease of maintenance for the optimal selection of manufacturing layout. Results of the FAHP-based decision model were then presented in this paper.