Simulation-based Lean Six-Sigma and Design for Six-Sigma

Simulation modeling within the context of six-sigma and design for six-sigma (DFSS) methods is constantly getting more attentions from black belts, green belts, and other six-sigma deployment operatives, process engineers, lean experts, and academics all over the world.This trend can easily be seen by the increasing use of simulation tools in several successful six-sigma initiatives in many Fortune 500 companies, coupled with the tremendous development in simulation software tools and applications. For a six-sigma project, conducting experimental design and “what-if” analysis is a common key practice toward achieving significant results. Simulation models can be utilized effectively as a flexible platform for six-sigma and DFSS experimentation and analyses, which reduces the time and cost of physical experimentation and provides a visual method to validate tested scenarios. On the other hand, simulation studies often suffer from the unavailability of accurate input data and lack of a structured approach for conducting analysis.The proven and widely used six-sigma and DFSS approaches provide the simulation study with reliable simulation data as input, an accurate process map, and integrates the simulation process with a state-of-the-art set of process analyses. Hence, coupling simulation modeling with a well-structured sixsigma process compensates for such limitations and bridges the gap between modeling and process engineering. Such integration provides the synergy and infrastructure essential for successful problem solving and continuous improvement in a wide spectrum of manufacturing and service applications. To develop an appreciation for the simulation-based six-sigma methodology, the subject of this book, we first review both six-sigma and simulation approaches and then lay the background for their integration.