Six Sigma is widely used in many industries for the purpose of improving process performance. Typical improvements sought in Six Sigma projects 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” (DMAIC) methodology.

This paper proposes the use of simulation and multi response optimization in addition to other typical Six Sigma tools in order to arrive at optimum performance at the end of each project through an established optimization framework. The framework is used in a real case study performed at a global logistics company.

The case study is concerned with an e-commerce logistics station located at John F. Kennedy airport (JFK) in New York; a station that suffers from low on-time delivery performance and high operational cost. As result, a Six Sigma project was implemented and the process was simulated to reveal various scenarios suggested by the Six Sigma team in order to optimize the process.

The project resulted in 65 percent reduction in labor, 41 percent reduction in work in process (WIP) and 55 percent reduction in average time packages spend at the station. These improvements highly support the effectiveness of implementing Six Sigma projects in the format suggested.

六西格码（Six Sigma）被广泛用于许多行业，以提高过程性能。在六个西格玛项目中寻求的典型改进包括降低运营成本，提高客户满意度，缩短周期时间并提高利润，但是，不管改进的性质如何，所有项目都遵循“定义，测量，分析，改进，控制”（DMAIC） ） 方法。

本文提出除了其他典型的六西格玛工具之外，还建议使用仿真和多响应优化，以便通过建立的优化框架在每个项目结束时获得最佳性能。该框架用于在一家全球物流公司进行的实际案例研究中。

案例研究与位于纽约约翰·肯尼迪机场（JFK）的电子商务物流站有关；准时交付性能差和运营成本高的站点。结果，实施了一个六西格码项目，并对过程进行了仿真，以揭示六西格码团队建议的各种方案，以优化流程。

该项目使劳动力减少了65％，在制品（WIP）减少了41％，在车站花费的平均时间减少了55％。这些改进高度支持以建议的格式实施六个西格玛项目的有效性。