Dr. Mikel Harry

Right up front in our discussion, let us recognize that the 1.5 sigma shift can be attributable solely to the influence of random error. In this context, the 1.5 sigma shift is a statistically based correction for scientifically compensating or otherwise adjusting a postulated model of instantaneous reproducibility (short-term capability) for the inevitable consequences associated […]

Measure what leads to success.

To open our discussion, we acknowledge that not all product (or service) opportunities should be Six Sigma. In the total scheme of things, some are not destined to be critical – to anything. For example, in a garden supply store we can find many different types of tools.  More specifically, let us consider an ordinary hand […]

It sounds to me like you’ve been “trapped in a barrel and tossed overboard,” so to speak.  Where is your champion?  He or she is supposed to prevent things like this from happening (i.e., sound project selection criteria).  Your project champion’s main purpose in life is to guard his or her flock of Black Belts. […]

Essentially, the idea of a “process” is to “Six Sigma” as the idea of “teaching” is to “knowledge.”  Perhaps Martin Luther King, Jr. best summed it when he stated: “Knowledge is a process of piling up facts; wisdom lies in their simplification.”  Not only is the process approach important, it is what under girds the […]

Obviously, a suggested course of action should be quite guarded, as it would be very case sensitive (i.e., circumstantial by nature).  As we all know, some consultants make their living resolving such “catch 22” situations.  We also recognize that the ability to find a balance point is more art than science.  It is much like […]

Extensive benchmarking has revealed the “average company” to be about 4 sigma capable.  Compared to Six Sigma the difference is about 1,800X.  Obviously, if one aspires to such a plateau, change is certain.  If change is certain, it is prudent to manage that change.  After all, it is doubtful that one can achieve a 1,800X […]

Seems you already have a pretty good idea of what to do.  To quote your words, “… such as in buying power, billing for energy consumption etc and which will save money for the company.”  Life is fairly simple partner: Y = f (X ).  Of course, the Ys of corporate life are constituted by; […]

Get the book “Six Sigma for Everyone” by George Eckes, John Wiley and Sons 2003.  It does a very nice job of outlining what to do and provides some really good tools.  Seems like a good book for green belts. To extend beyond the aforementioned book, let us come to understand the importance of properly […]

Do not employ money as the improvement variable (it is a symptom). Remember that RTY is a function of dpu. Since RTY and dpu are directly related, most would likely prefer the defect-centric metric.

Upfront, rolled throughput yield has a lot of sex appeal (and is an excellent instructional concept), but many discontinue its application after a short period of time – it is impractical for a relatively complex process. Recognize that most of the defect-centric metrics are usually better for purposes of quality reporting (and improvement efforts).

Let us postulate that a certain process is comprised of three progressive steps, say A, B, and C, respectfully. Further, we note the observed defects-per-unit (dpu) at the first step to be dpu.A = .10. At the second step, dpu.B = .05. The third step was found to be dpu.C = .008. Of course, we acknowledge dpu as a […]

To help you better understand the nature of this question; let us consider a very simple example.  Let us suppose that we go to the store – looking for fresh apples.  Once there, we notice a sign that reads “3 apples for $1.00.”  Based on this sign, we ask the storekeeper: “If I want to buy […]

Perhaps you are both in error (as related to your Sigma calculations.) Do not be discouraged by such debate, as it is quite common among those new to Six Sigma. However, do be aware of a phenomenon I call “denominator management.” This colorful term is used to describe the practice of inflating or otherwise distorting the denominator […]

So as to better appreciate the spirit and intent of our ensuing discussion, we must call upon the nature and purpose of two recognized entities – the US Postal Service and Ford Motor Company.  If we were to contrast these organizations, how would they appear to be similar? How would they appear to be dissimilar?  […]

1) There is no such thing as a one-size-fits all Black Belt or Green Belt program of study. 2) Many customers are naïve.  They often want more tools (not fewer), regardless of whether or not they will ever be used. 3) Some customers seek to purchase a hardware store so as to fix the kitchen […]

As you likely know, the issue of opportunity counting is somewhat illusive. It is laced with many misconceptions. The seeming intuitive nature of a “defect opportunity” runs wider and deeper than what one would naturally expect. To help us better understand this concept (and some of the related pitfalls), we will discuss the classic quality metric […]

Here are 7 progressive questions to help plan a project. 1) What decisions must be made? 2) What do you need to know to make each decision? 3) What form of visual will provide the information? 4) What kind of tool will generate the visual? 5) What kind of data is needed for the tool? […]

Under the condition that D = 0 defects for the constrained condition of N = 20 samples, we can statistically approximate the short-term capability and provide its quantity in the form Z.st = 3.33.  Of course, this is directly equivalent to Cp = 1.11. Interestingly, the statistical base underpinning this set of computations is fully […]

Consider the case where a particular system is comprised of three subordinate elements. In this case, we will say the first-time yield (quality confidence) of each element is known to be .85, .90, and .95, respectively. The cross product would then be given as .85 x .90 x .95 = .612, or about 61.2 percent.  This value […]

To facilitate an answer to your question, consider the following table. The first column is the given measure of process capability (provided in the form of Z).  The second column is the corresponding short-term yield of the first column (based on a one-sided specification). Of course, the third column is the associated long-term yield, also predicated on […]

There is little difference between Statistical Quality Control (SQC) and Statistical Process Control (SPC).  At one time, there might have been some philosophical separation, but today, they exist as general synonyms.  Some prefer SQC because the idea of “quality” is larger and more encompassing than that of “process.”  Others counter this by pointing out that […]

Establishing the initial list of potential causes is often more art than science.  Unfortunately, the brainstorming process is still one of the best ways to surface candidate variables.  However, there are several other alternatives: 1)   Query process experts. 2)   Benchmark similar processes. 3)   Review the literature. 4)   Perform an Internet search. 5)   Conduct correlation study. […]

To facilitate an answer, we will consider three examples.  First, consider the game of baseball.  We understand the field-of-play consists of 9 positions.  The coach is “free” to assign any of the 9 players to any of the 9 positions. Once the 8th player is assigned to the 8th position, the 9th player-position is pre-determined, […]