RSS Cientifico geral Automobile repair scheduling: a real case

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Breve resumo:
Scheduling represents a classic combinatorial problem, which has been extensively studied in Operational Research (OR). These type of problems arise in several economic domains, and in spite of the great variety of studies present in the literature, few are those that portray problems in the automobile sector, particularly in the scheduling of car maintenance tasks, and that use real data for their resolution. This project will portray the case of a Portuguese rm in the automobile sector, in the branch located in Porto, focusing on the repairs performed at its mechanical section. The process of each vehicle that arrives at the repair shop starts by the opening of a repair order (RO) form, indicating the necessary mechanical repairs to be performed. Next the repair shop manager assigns the repair tasks to one of the eight mechanics available in this repair shop. This study intends to develop a mathematical model that, using data provided by the rm, would allow to improve the scheduling of the repairs, considering the mechanics and resources available, the necessary interventions to perform and the execution time of each one of these interventions. The aim is to reduce the time of inactivity of the vehicles between interventions, as well as increasing the productivity of the mechanics' work. For this, a Mixed Integer Linear Programming (MILP) model will be developed, combining linear ordering variables to sequence the interventions performed in each vehicle, assignment variables and linear variables for start times. The problem will be formulated and solved using the AMPL modeling language, using the Gurobi solver, to solve the real instances tested. With the application of the developed model, the vehicles' interventions scheduling will be performed in a suitable form, reducing both the downtime between the vehicles' interventions as well as the downtime of mechanics, and therefore improve productivity. The results show that all the necessary mechanical interventions are correctly schedule and there is a decrease in the downtimes.​



Info Adicional:
Scheduling represents a classic combinatorial problem, which has been extensively studied in Operational Research (OR). These type of problems arise in several economic domains, and in spite of the great variety of studies present in the literature, few are those that portray problems in the automobile sector, particularly in the scheduling of car maintenance tasks, and that use real data for their resolution. This project will portray the case of a Portuguese rm in the automobile sector, in the branch located in Porto, focusing on the repairs performed at its mechanical section. The process of each vehicle that arrives at the repair shop starts by the opening of a repair order (RO) form, indicating the necessary mechanical repairs to be performed. Next the repair shop manager assigns the repair tasks to one of the eight mechanics available in this repair shop. This study intends to develop a mathematical model that, using data provided by the rm, would allow to improve the scheduling of the repairs, considering the mechanics and resources available, the necessary interventions to perform and the execution time of each one of these interventions. The aim is to reduce the time of inactivity of the vehicles between interventions, as well as increasing the productivity of the mechanics' work. For this, a Mixed Integer Linear Programming (MILP) model will be developed, combining linear ordering variables to sequence the interventions performed in each vehicle, assignment variables and linear variables for start times. The problem will be formulated and solved using the AMPL modeling language, using the Gurobi solver, to solve the real instances tested. With the application of the developed model, the vehicles' interventions scheduling will be performed in a suitable form, reducing both the downtime between the vehicles' interventions as well as the downtime of mechanics, and therefore improve productivity. The results show that all the necessary mechanical interventions are correctly schedule and there is a decrease in the downtimes.



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