Análise dos serviços emergenciais de manutenção agrícola e borracharia na agroindústria canavieira utilizando teoria de filas
Rodrigues, Lásara Fabrícia
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The sugarcane industry is an important branch of the Brazilian agroindustry considering the major role of sugarcane cultivation in the country history and the prominent position that this industry has achieved in the international scenario. In recent years, this industry has faced major changes and challenges. Therefore, the use of methods to support decision making has become increasingly necessary to optimize the available resources and enable the analysis of larger data sets. The present study addresses the Maintenance and Tire Repair Emergency Services in the agricultural stage of the sugarcane industry. In order to analyze and support decisions in the Tire Repair System, the Hypercube Model, the Simulation Model, and the known Queue Models M/M/m and M/G/m were developed or adapted using data from a case study conducted in a sugar and alcohol mill with centralized servers. In addition, an alternative scenario with decentralized servers was also investigated, and it showed better results in terms of performance measures compared to those of the original scenario. Extensions of the Hypercube Model, the Approximated Hypercube Model and the Simulation Models were developed to analyze and support decisions in the Maintenance Service System. At first, an illustrative example was used to address the issues of priority queue, partial backup, and differentiated service rates between the hypercube states and the states of the tail. Subsequently, experiments using these models and the case study data were conducted. An alternative scenario including one more server was also studied, and it showed better results than those of the original scenario, especially in terms of travel times. The present study shows that the adaptations and extensions of the hypercube model and the simulation models developed to treat Maintenance and Tire Repair Emergency Systems in sugarcane mills have proven to be effective approaches for these systems planning and analysis. The results of this study indicate that the models developed and adapted are suitable for application in sugarcane industries.