Proposta de um framework para a condução de projetos de simulação a eventos discretos integrando Lean Six Sigma

Abstract

There are many Modeling and Simulation methods available in the literature, which are commonly used in Discrete Event Simulation (DES) projects. However, most of these methods focus on constructing computational models, which results in opportunities for improvement in the problem definition and results analysis stages, as they are often overlooked. One way to address this gap is by incorporating alternative methods to DES. In this regard, the integration of the Lean Six Sigma (LSS) method, based on the Define, Measure, Analyze, Improve, and Control (DMAIC) framework, with the DES method has shown positive results in various application areas. However, the scientific literature provides few studies addressing this integration. Given this context, the present work aims to propose a framework that allows the integration of a robust and systematic problem-solving method (LSS) with a modeling and simulation tool (DES), aiming for more accurate and effective execution of discrete event simulation projects. To achieve this objective, a systematic literature review (SLR) was conducted to gather information regarding the state of the art on the topics addressed, to identify the focus of the works (DES or LSS), their structure, usage, and the main tools involved in the process, to determine in which phases of DMAIC the DES models were applied, and finally, the main elements found in works that presented some kind of framework. Among the analyzed works, only seven proposed an integrated framework, all of which were evaluated to identify past and future trends in the main practices presented. Based on these analyses, associations were established between the concepts of the two methods to relate common objectives within the same stage. Thus, the initial version of the framework was developed and subsequently subjected to evaluation through an online questionnaire, answered by experts in the areas of DES and LSS, with the purpose of being statistically validated. After considerations and tests, the final version of the framework was proposed, representing the outcome of this work.