Simulação Monte Carlo aplicada na análise de indicadores de desempenho em um contexto sob incerteza: um estudo na cadeia de suprimentos de uma indústria de grande porte

• Autor(a) principal: Maeda, Camila Terumi Koketsu [UNESP]
• Data de Publicação: 2017
• Tipo de documento: Trabalho de conclusão de curso
• Idioma: por
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://hdl.handle.net/11449/156889; http://www.athena.biblioteca.unesp.br/exlibris/bd/capelo/2018-08-09/000905466.pdf
• topic: Monte Carlo, Método de; Cadeia de logística integrada; Processo decisório; Gestão da qualidade total; Integrated logistic support

The increasing competitiveness and volatility of the economic environment have forced companies to seek greater efficiency in all the processes of their supply chain. In order to increase this supply chain visibility, the main objective of this research is to analyze Key Performance Indicators (KPIs) in a context under uncertainty, since performance indicators are developed based on the strategic objectives of the company. The method used to perform this analysis is modeling and simulation, via Monte Carlo Simulation (SMC). To perform these studies, Crystal Ball® and Microsoft Office Excel® software were used. The topics covered in the theoretical foundation are: KPI, Modeling and Simulation and SMC. The company under study was chosen based on the locality criteria, once there is an easy access, and in the feasibility criteria, once it already has a history of measurements of KPIs. The work in question aims to analyze the applicability of SMC in the analysis of performance indicators in a context under uncertainty. As a result of the research, it was demonstrated that from the three KPIs that was simulated, two of them could be applied using Crystal Ball®, and the third would also need the VBA application to be able to aid in a decision making.