Axiomatic Six Sigma, A Simulation-Based Decision-Making Framework

For the last few decades, companies used six sigma in almost all processes to improve performance. Typical improvements include decreased operational cost, increased customer satisfaction, decreased cycle time, and enhanced profits, but regardless of the nature of the improvement, all projects follow the “Define-Measure-Analyze-Improve-Control” methodology. This paper proposes the use of a decision framework that utilizes the use of axiomatic design in the analyze and improve phases in order to reach optimum performance at the end of each project through an established optimization framework. The framework includes the use of simulation and a managerial decision-making tool called “alternative evaluation tool”. The author implemented the framework in a real case study performed at a global logistics company that has an e-commerce logistics station located at John F. Kennedy airport in New York; a station that suffers from low on-time delivery and high operational cost. As result, the author implemented a six-sigma project along with simulation to reveal various scenarios suggested by the six-sigma team in order to optimize the process. The project resulted in 65% reduction in labor, 41% reduction in work in process and 55% reduction in average time packages spend at the station.