I am an Assistant Professor of Marketing and Business Information Systems at the Rohrer College of Business, Rowan University, New Jersey. I hold a PhD in Operations Management from the University of Cincinnati (UC). Prior to PhD, I was employed for several years in the industry verticals such as logistics, construction/agricultural equipment manufacturing, and consumer packaged goods. My research interests span the areas of sustainable operations, supply chain, inventory management and transportation. At UC, I taught introductory courses on business analytics to undergraduate students. My teaching interests include: operations management, business analytics, logistics and supply chain management. Before joining Rowan, I taught at Quinnipiac University for four years.
Hi.... the formulae for the standard deviation during LT, found in many books, has always bugged me... if you include the units, you will see that they won´t take you to sqrt(pen^2) = [pen] .... the L(bar) should also be squared for it to work. Using you example (just the units): sqrt( [wk] x [pen/wk]^2 + [pen/wk]^2 x [wk]^2)
We are talking about 6sigma and you have used 99.73% achievement only. 6 Sigma requires 99.99966% achievement within the design width. Could you please clarify
Great video! A yamazumi chart is a great way to see bottlenecks visually as well. I am Industrial Engineer and I like to teach this to my students and new hires.
For Q1(b), should be multiply with $10? If we multiply with $, then the productivity just a ration number without unit. The definition is output divide by multifactor input. If we multiply with $10, it will become sales? Confuse about this part. Then last question, why no need to multiply with $110 for labour productivity?
so when we speak in terms of lean 6sigma, does this refer to 6 sigma on either side of the distribution curve or is this the span of six sigma across the distribution curve?
Until I found this explanation I wasted about an hour to find the right definition of six sigma and realized most of the experts if not all in this subject lacks the mathematical or statistical concept.