SCENARIO PRIORITIZATION FOR AUTOMOTIVE ASSEMBLY SYSTEM SIMULATION: AN APPROACH BASED ON AHP

Abstract

Abstract Simulation methods that strive to faithfully depict possible models of the actual reality faced are increasingly used in industries. Designing scenarios, defining plans and strategies, making decisions based on situations presented by models currently are important facilitators enabled by simulations. In contrast, problems with complex models require deeper studies that may result in failure to identify effective solutions using only this tool. One proposal to provide more assertive solutions is the use of simulations linked to decision support methods. Based on criteria of relevance, these methods can perform pairwise comparisons among the alternatives identified in the problem statement. In addition, these work with the execution of multi-criteria analyzes at the same time, helping in decision-making and also in prioritizing needs / actions. The objective of this paper is to demonstrate the applicability of the AHP (Analytic Hierarchy Process) decision making method for the purpose of prioritizing and directing efforts in possible solutions identified for the problem. The case study chosen is in an automotive assembly plant where the rising interaction between Logistics and Assembly workstations results in the need for complex, multi-variable decisions (sizing of packages, number of operators allocated, takt time/line speed, process type definition, ergonomic issues, among others). After defining the priority criteria, a simulation is developed to present the scenario and behaviors indicated by AHP that the production line being studied can apply. The conclusions offer a discussion of the decisions made by deploying the method and of the scenario depicted. This paper presents the formulation of a model for the development of factory layouts, including the effective contributions that can be achieved through the deployment of decision support aids in prioritizing criteria linked to the scenario simulations with positive outcomes on problems of the manufacturing sector.