O uso da simulação computacional como ferramenta auxiliar no custeio de produtos de uma fábrica de usinagem

Abstract

This work employs computational simulation to assess production costs in a machining factory, applying the absorption costing method and emphasizing the capability of simulation to generate production costs based on stochastic variables, a significant differential compared to traditional deterministic calculations. The methodology begins with defining the problem and identifying the most impactful products. Critical demands in the company, such as inventory control and production planning, were identified, leading to the selection of production cost as the study’s object. Using the Pareto principle, products with the greatest impact on the company’s financial health were chosen for more detailed analysis. The mapping of processes was carried out after identifying the products, detailing the manufacturing processes and collaborating with employees to ensure the accuracy of the information. During data collection, specific information about each production process was gathered, necessary for computational modeling. Using FlexSim®, a computational model was developed, based on the documentation of processes and collected data, including the representation of the factory layout and the integration of processing times in a 3D environment. The distinctive aspect of this approach is the ability of computational simulation to incorporate stochastic variables in the generation of production costs, allowing a level of precision and realism that traditional deterministic methods cannot achieve. This aspect is crucial as it considers the variability and uncertainty inherent in production processes, providing a more dynamic and adaptable view of costs. The effectiveness of the simulation model was ensured through verifications and validations, guaranteeing that the model accurately represented the reality of production. After validating the model, it was possible to analyze the resources used and the costs associated with each stage of production. The simulation provided a detailed and accurate understanding of the production costs of the focal product.