Six Sigma

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Six Sigma is a methodology to manage process variations that cause defects, defined as unacceptable deviation from the mean or target; and to systematically work towards managing variation to eliminate those defects. The objective of Six Sigma is to deliver high performance, reliability, and value to the end customer. It was pioneered by ill Smith at !otorola in "#$% and was originally defined as a metric for measuring defects and improving &uality; and a methodology to reduce defect levels below '.( )efects *er +one, !illion -pportunities +)*!-,. Six Sigma has now grown beyond defect control. Six Sigma is a registered service mark and trademark of !otorola, Inc. !otorola has reported over .S/"0 billion in savings from Six Sigma to date.

Methodology
Six Sigma has two key methodologies1 )!2I3 and )!2)4. )!2I3 is used to improve an existing business process. )!2)4 is used to create new product designs or process designs in such a way that it results in a more predictable, mature and defect free performance. Sometimes a )!2I3 project may turn into a )5SS project because the process in &uestion re&uires complete redesign to bring about the desired degree of improvement. DMAIC asic methodology consists of the following five phases6
• •

• •

Define formally define the process improvement goals that are consistent with customer demands and enterprise strategy. Measure to define baseline measurements on current process for future comparison. !ap and measure process in &uestion and collect re&uired process data. Analyze to verify relationship and causality of factors. 7hat is the relationship8 2re there other factors that have not been considered8 Improve optimi9e the process based upon the analysis using techni&ues like )esign of :xperiments.



Control setup pilot runs to establish process capability, transition to production and thereafter continuously measure the process and institute control mechanisms to ensure that variances are corrected before they result in defects.

DMADV asic methodology consists of the following five phases6
• • • • •

Define formally define the goals of the design activity that are consistent with customer demands and enterprise strategy. Measure identify 3T;s, product capabilities, production process capability, risk assessment, etc. Analyze develop and design alternatives, create high<level design and evaluate design capability to select the best design. Design develop detail design, optimi9e design, and plan for design verification. This phase may re&uire simulations. Verify design, setup pilot runs, implement production process and handover to process owners.

2lso see )esign for Six Sigma &uality. The most common acronym for )esign for Six Sigma is )5SS.

Some people have used )!2I3R +reali9e,. -thers contend that focusing on the financial gains reali9ed through Six Sigma is counter<productive and that said financial gains are simply byproducts of a good process improvement. 2nother additional flavor of )esign for Six Sigma is the )!:)I method. This process is almost exactly like the )!2)4 process, utili9ing the same toolkit, but with a different acronym. )!:)I stands for6
• • • • •

Define Measure Explore Develop Implement

Roles Required for Implementation
Six Sigma identifies five key roles for its successful implementation.










Executive eadership includes 3:- and other key top management team members. They are responsible for setting up a vision for Six Sigma implementation. They also empower the other role holders with the freedom and resources to explore new ideas for breakthrough improvements. Champions are responsible for the Six Sigma implementation across the organi9ation in an integrated manner. The :xecutive =eadership draws them from the upper management. 3hampions also act as mentor to lack elts. 2t >: this level of certification is now called ?;uality =eader?. Master !lac" !elts, identified by champions, act as in<house expert coach for the organi9ation on Six Sigma. They devote "@@A of their time to Six Sigma. They assist champions and guide lack elts and >reen elts. 2part from the usual rigor of statistics, their time is spent on ensuring integrated deployment of Six Sigma across various functions and departments. !lac" !elts operate under !aster lack elts to apply Six Sigma methodology to specific projects. They devote "@@A of their time to Six Sigma. They primarily focus on Six Sigma project execution, whereas 3hampions and !aster lack elts focus on identifying projectsBfunctions for Six Sigma. #reen !elts are the employees who take up Six Sigma implementation along with their other job responsibilities. They operate under the guidance of lack elts and support them in achieving the overall results.

Specific training programs are available to train people to take up these roles. The above listed roles conform to the old !ikel CarryBDichard Schroeder model, which is far from being universally accepted. In many successful programs, both >reen elts and lack elts lead projects, and work on problems in their existing area of responsibility. $he $erm %ix %igma Sigma +the lower<case >reek letter ?s?, is used to represent standard deviation +a measure of variation, of a population +lower<case EsE, is an estimate, based on a sample,. The term ?six sigma process? comes from the notion that if you have six standard deviations between the mean of a process and the nearest specification limit, you will make practically no items that exceed the specifications. This is the basis of the *rocess 3apability Study, often used by &uality professionals. The term ?Six Sigma? has its roots in this tool, rather than in simple process standard deviation, which is also measured in ?sigmas?. 3riticism of the tool itself, and the way that the term was derived from the tool, often spark criticism of Six Sigma. The widely accepted definition of a six sigma process is one that produces '.( defective parts per million opportunities +)*!-,.

http6BBwww.isixsigma.comBdictionaryBSixFSigma<$G.htm 2 process that is normally distributed will have '.( parts per million beyond a point that is (.G standard deviations above or below the mean +one<sided 3apability Study,. So '.( )*!- corresponds to (.G sigmas, not six. 2nyone with access to !initab or ;uikSigma can &uickly confirm this by running a 3apability Study on data with a mean of @, a standard deviation of ", and an upper specification limit of (.G. So, how is this truly (.G sigma process transformed to a % sigma process8 y arbitrarily adding ".G sigmas to the calcuated result, the ?".G sigma shift? +S TI lack elt material, ca "##$,. )r. )onald 7heeler, one of the most respected authors on the topics of 3ontrol 3harts, 3apability Studies, and )esigned :xperiments, dismisses the ".G sigma shift as ?goofy?. +7heeler, )onald H., *hd, The Six Sigma *ractitionerEs >uide to )ata 2nalysis, p'@0, www.spcpress.com, In a 3apability Study, sigma refers to the number of standard deviations between the process mean and the nearest specification limit, rather than the standard deviation of the process, which is also measured in ?sigmas?. 2s process standard deviation goes up, or the mean of the process moves away from the center of the tolerance, the *rocess 3apability sigma number goes down, because fewer standard deviations will then fit between the mean and the nearest specification limit. http6BBen.wikipedia.orgBwikiB3pkFIndex The notion that, in the long term, processes usually do not perform as well as they do in the short term is correct. That re&uires that that *rocess 3apability sigma based on long term data is less than or e&ual to an estimate based on short term sigma. Cowever, the original use of the ".G sigma shift is as shown above, and implicitly assumes the opposite. 2s sample si9e increases, the error in the estimate of standard deviation converges much more slowly than the estimate of the mean +see confidence interval,. :ven with a few do9en samples, the estimate of standard deviation often drags an alarming amount of uncertainty into the 3apability Study calculations. It follows that estimates of defect rates can be very greatly influenced by uncertainty in the estimate of standard deviation, and that the defective parts per million estimates produced by 3apability Studies often ought not to be taken too literally. :stimates for the number of defective parts per million produced also depends on knowing something about the shape of the distribution from which the samples are drawn. .nfortunately, we have no means for proving that data belong to any particular distribution. 7e only assume normality, based on finding no evidence to the contrary. :stimating defective parts per million down into the "@@Is or "@Is of units based on such an assumption is wishful thinking, since actual defects are often deviations from normality, which have been assumed not to exist. In summary, the term JSix SigmaK has its roots in a &uality tool that can easily be misapplied by a naLve user and in the controversial ".G sigma shift. The core of the Six Sigma methodology is a data<driven, systematic approach to problem solving, and focus on customer impact. Statistical tools just happen to be useful along the way.

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