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Six Sigma Project Managment and Technical Consulting
Russ Wrisley has the lead role in this capability at FasTrak Network. Having cut his teeth on cost reduction and continuous process improvement projects at Corning Glass Works in the 80's, he continues, after 17 years, with his Six Sigma Black Belt Certification (pending review of submission).
CSS: Statistica, is the primary tool in all of FasTrak Network's Six Sigma projects. It is the hands down favorite software for all of our analytical data analysis. Go to or call Statsoft 's Paul Portrey at 918-749-1119 for additional information -- tell him Russ sent you. Check out our page on Statistical Data Analysis for more detail.
DMAIC Principles are highly endorsed at FasTrak Network. Every Six Sigma project undertaken by Russ and his staff has rigidly followed this format and principles. Yes, we use the Rath Strong Six-Sigma literature. (Visit for more information.) Data collection using these Six Sigma programs involves gleaning useful information gathered everywhere from old records in the back of the warehouse, to power spectral density plots from the research lab. Of course, the best information comes from actual process monitoring and test bench metrology. Either way, we understand the value of it and how to get it.
In the case of metrological data, none is used without qualifying it through gage R&R. Quantitative or qualitative, we do them all. In all sample collection, either from off the line, gage R&R, or experimental design, sampling plans are used to provide the necessary credibility. In DoE we favor fractional factorials and central composites, probably because of the types of processes we're working on.  (Although we haven't done much with Taguchi designs, I suppose we could.) Of course, no discussion on DoE would be complete without mentioning regression analysis. One of the innovative practices of DoE we've used is to combine parts from two separate DoE's into one grand design and measure response or functionality of the assembly. This allows us to quantify the effects of the fundamental process parameters on system level performance. That being said, we ultimately model the functionality performance as a function of processing parameters or other key geometric features which can then be confirmed in process capability evaluation and process monitoring.
If you've stuck with me this long, I won't bore you with the dissertation on Quality control tools, let it suffice to say, we do that too.