Optimization of the Operation Management Process of a Company in the Electronic Manufacturing Sector

The use of mathematical programming models for production planning has been proposed since the 1950s, being a widely applied tool, since it can provide optimal solutions for production planning problems. For manufacturing companies, it is a great challenge to plan in uncertain environments when there are large variations in planning parameters. Thus, the greatest difficulty in dealing with Mathematical Programming models in production planning is that, in general, with the intention of simulating reality through these models, it is necessary to estimate values for the planning parameters, which may not always be possible accurately, and consequently, the model's optimal solution may not represent the best solution to the problem. In this context, the classic approach to deal with a dynamic economic scenario is the use of robust optimization models, which propose a suboptimal solution in relation to the deterministic model. Therefore, the objective of this paper is to apply a robust optimization model in the operations management process of an electronic components manufacturing company. First, a content analysis was performed, then company data was collected, the model was proposed, and the results were analyzed. Results suggested more than 80% of the production should be done in anticipation. The optimal solution, at the lowest cost, was obtained from the minimal scenario. The worst and robust solution, bringing the highest cost, came from the intermediate scenario, proving that the production plan could be performed even with adversities on sight.