Application of Monte Carlo's method to predict the Overall Equipment Effectiveness index of a cellulose machine

Abstract

The application of simulation in organizations brings several advantages, from an understanding of their systems and processes, to perspectives on strategies and next steps, as it allows designing scenarios and developing action plans, at low cost. In this context, the opportunity was identified to continue a study regarding the global equipment efficiency indicator, Overall Equipment Effectiveness (OEE), in a pulp and paper industry. Therefore, Monte Carlo simulations were carried out, based on historical data of a quantitative nature, referring to the operation of a machine - which has a current average OEE of 65.08% and theoretical capacity to produce 624 tons of cellulose in 24 hours of operation. The objective was to verify the feasibility of this equipment reaching the level of 85% in the OEE index, considered World Class, and to understand which variables and parameters most impact the efficiency of this indicator, through Monte Carlo simulations, performed in the Crystal Ball software . As a result, 50,000 iterations were performed and it was found that the probability of the equipment reaching a world-class OEE was only 0.009%. It was also verified, from the sensitivity graph, that the parameters that most interfere in the efficiency of this index are the Performance (54.7%) and the Availability (31.9%) of the machine. It is concluded that, from the generation of a robust volume of data, the simulation allowed to evaluate the interaction of different variables present in the production line and their impacts on relevant company indicators, without the need to make any previous changes in the environment. job. Therefore, it can be applied as an important tool for feasibility studies, performance analysis and decision making in companies.