Today, I stumbled over a blog article Six Sigma and Simulation Part 2 written by Jeff Joines, who is an Associate Professor in Textile Engineering at NCSU. He identifies the areas he feels that Monte Carlo simulation can be used in each of the phases of the DMAIC process.
*Estimate cost savings for each project by indicating variability instead of using single-point estimates; provide a more reliable estimation as well as a confidence level of achieving the estimated savings.
Analyze and Improve
*Design of Experiments (DOE) (Full, Fractional, Mixed, etc.) is the most common tool utilized that provides a base line to illustrate improvement when changes are made, as well identifying factors of interest to control or change.
*DFSS – If the product or process does not exist as is the case in a Design for Six Sigma, simulation models can be used to ascertain capability of a new process and product before implementation.
*Cost reduction of performing a DOE (i.e., raw material cost, cost of shutting down current process). You can determine the process capabilities and ascertain the potential improvements while minimizing time and expenditures.
*Multiple processes that feed one another. Transfer functions can be generated from a traditional DOE on each individual process but not the entire system. A simulation model can be used to combine each individual transfer function into determining the capability of the whole system as well as testing a wider range of values.
*Simulation can also be used as a process control aid as the process is being implemented to determine potential problems.
I don’t know Jeff’s background and experience with Six Sigma, but he did a very nice job in both blogs explaining the Six Sigma methodologies. To read either posting in their entirety, visit Success in Simulation. I am looking forward to the third and final posting in the series.