Suporte a decisão na gestão da manutenção industrial: abordagem baseada em mineração de processos, simulação e métodos multi-critério

Abstract

Industrial maintenance (IM) processes in the context of industry 4.0 have evolved significantly in recent years, being increasingly conditioned to the use of technologies, which facilitates the vision and execution of intelligent factories, which do not depend only on people for decision-making decisions. In this sense, this research contributes to decision making in industrial maintenance, the objective is to propose a framework for the simulation of discrete events that allows generating information for the calculation of performance indicators with the aid of process mining. The simulation model was developed in CPN (Colored Petri Nets) based on the indicators to be selected by a maintenance team from a predefined location. Process mining will be responsible for extracting the information needed for modeling and also extracting information from the simulations to be performed. For decision making in addition to the values of each indicator, the opinion of the same maintenance team that defined the weights of each indicator through the AHP method (Analytic Hierarchy Process) will also be considered. The combination of the quantitative and qualitative data was made using the Promethee method (Preference Ranking Organization Method for Enrichment Evaluation), which ordered the simulated scenarios according to their performance. The results of this study showed that it is possible to reach a reliable decision, and it allows its executors to continuously improve, by creating and simulating new scenarios for a given environment.