Planejamento de leiautes para empresas de pequeno e médio porte: uma análise a partir do systematic layout planning e particle swarm optimization

Abstract

As one of the most important activities in production engineering, facility planning consists of making decisions regarding the layout of the sectors, production/manufacturing units, storage locations, and so on. This concept is supported by the variability of production processes, which changes from one period of production to another and from one company to another. Currently, the literature presents approaches of how to solve the problem of layout for small and medium-sized companies with models of planning, and decision-making multi-criteria, or metaheuristics. The literature addresses these two methods separately. In fact, there are no reports of comparisons between them since the knowledge of the author. In response to this research gap, the following objective was defined: "to identify a method for layout planning applicable to small and medium-sized enterprises". The objective was to develop a generic modeling tool that meets different needs. Thus, this work approached Systematic Layout Planning (SLP) and Particle Swarm Optimization (PSO) for the layout planning, evaluating the best proposal by the Analytic Hierarchy Process (AHP). Because of practical interests that aim at the application of tools for the solution of specific problems, this work is classified as applied research of quantitative approach, based on processes of decision-making and modeling. The results obtained demonstrate that SLP provides better layout proposals than the PSO, for small and medium enterprises. The SLP respects the adjacent allocation of the sectors according to the material flow, while the PSO randomly distributes the productive areas, which provides greater variability in the layout proposals. The SLP required greater planning time and an auxiliary method (AHP) to define the best layout proposal. The PSO provided the best layout without a support tool and the simulation was faster after structuring the algorithm model. Practical implications of this research lie in the analysis of cost reduction with real data. Optimization objectives and constraints that are more usual have been identified in the literature. As for the type of layout, according to the characteristics of the company, and because it is a single case study, the job-shop type will be considered. This research contributes to the academic environment in the context of synthesizing two distinct methods for planning layouts and comparing them with a multi-criteria decision-making tool. In the business environment, it provides methods that can be incorporated into companies’ day-to-day planning and decision making.