pranatiSix Sigma is a system of practices originally developed by Motorola to systematically improve processes by eliminating defects. Defects are defined as units that are not members of the intended population. Since it was originally developed, Six Sigma has become an element of many Total Quality Management (TQM) initiatives.
The process was pioneered by Bill Smith at Motorola in 1986 and was originally defined as a metric for measuring defects and improving quality, and a methodology to reduce defect levels below 3.4 Defects Per (one) Million Opportunities (DPMO).
Six Sigma is a registered service mark and trademark of Motorola, Inc. Motorola has reported over US$17 billion in savings from Six Sigma as of 2006.
In addition to Motorola, companies which also adopted Six Sigma methodologies early-on and continue to practice it today include Bank of America,Caterpillar, Honeywell International (previously known as Allied Signal), Raytheon and General Electric (introduced by Jack Welch).
Recently Six Sigma has been integrated with the TRIZ methodology for problem solving and product design.
Key Concepts of Six Sigma
At its core, Six Sigma revolves around a few key concepts.
Critical to Quality: Attributes most important to the customer
Defect: Failing to deliver what the customer wants
Process Capability: What your process can deliver
Variation: What the customer sees and feels
Stable Operations: Ensuring consistent, predictable processes to improve what the customer sees and feels
Design for Six Sigma: Designing to meet customer needs and process capability
Six Sigma has two key methodologies: DMAIC and DMADV. DMAIC is used to improve an existing business process. DMADV 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.
Also see DFSS (Design for Six Sigma) quality. Sometimes a DMAIC project may turn into a DFSS project because the process in question requires complete redesign to bring about the desired degree of improvement.
Basic methodology consists of the following five steps:
Define the process improvement goals that are consistent with customer demands and enterprise strategy.
Measure the current process and collect relevant data for future comparison.
Analyze to verify relationship and causality of factors. Determine what the relationship is, and attempt to ensure that all factors have been considered.
Improve or optimize the process based upon the analysis using techniques like Design of Experiments.
Control to ensure that any variances are corrected before they result in defects. Set up pilot runs to establish process capability, transition to production and thereafter continuously measure the process and institute control mechanisms.
Basic methodology consists of the following five steps:
Define the goals of the design activity that are consistent with customer demands and enterprise strategy.
Measure and identify CTQs (critical to qualities), product capabilities, production process capability, and risk assessments.
Analyze to develop and design alternatives, create high-level design and evaluate design capability to select the best design.
Design details, optimize the design, and plan for design verification. This phase may require simulations.
Verify the design, set up pilot runs, implement production process and handover to process owners.
Some people have used DMAICR (Realize). Others contend that focusing on the financial gains realized through Six Sigma is counter-productive and that said financial gains are simply byproducts of a good process improvement.
Another additional flavor of Design for Six Sigma is the DMEDI method. This process is almost exactly like the DMADV process, utilizing the same toolkit, but with a different acronym. DMEDI stands for Define, Measure, Explore, Develop, Implement.
Quality Approaches and Models
DFSS (Design for Six Sigma) - A systematic methodology utilizing tools, training and measurements to enable us to design products and processes that meet customer expectations and can be produced at Six Sigma Quality levels.
DMAIC (Define, Measure, Analyze, Improve and Control) - A process for continued improvement. It is systematic, scientific and fact based. This closed-loop process eliminates unproductive steps, often focuses on new measurements, and applies technology for improvement.
Six Sigma - A vision of quality, which equates with only 3.4 defects per million opportunities for each product or service transaction. Strives for perfection.
Associates are exposed to various tools and terms related to quality. Below are just a few of them.
Control Chart - Monitors variance in a process over time and alerts the business to unexpected variance which may cause defects.
Defect Measurement - Accounting for the number or frequency of defects that cause lapses in product or service quality.
Pareto Diagram - Focuses our efforts on the problems that have the greatest potential for improvement by showing relative frequency and/or size in a descending bar graph. Based on the proven Pareto principle: 20% of the sources cause 80% of any problems.
Process Mapping - Illustrated description of how things get done, which enables participants to visualize an entire process and identify areas of strength and weaknesses. It helps reduce cycle time and defects while recognizing the value of individual contributions.
Root Cause Analysis - Study of original reason for nonconformance with a process. When the root cause is removed or corrected, the nonconformance will be eliminated.
Statistical Process Control - The application of statistical methods to analyze data, study and monitor process capability and performance.
Tree Diagram - Graphically shows any broad goal broken into different levels of detailed actions. It encourages team members to expand their thinking when creating solutions.
Black Belt - Leaders of teams responsible for measuring, analyzing, improving and controlling key processes that influence customer satisfaction and/or productivity growth. Black Belts are full-time positions.
Control - The state of stability, normal variation and predictability. Process of regulating and guiding operations and processes using quantitative data.
CTQ: Critical to Quality (Critical "Y") - Element of a process or practice which has a direct impact on its perceived quality.
Customer Needs, Expectations - Needs, as defined by customers, which meet their basic requirements and standards.
Defects - Sources of customer irritation. Defects are costly to both customers and to manufacturers or service providers. Eliminating defects provides cost benefits.
Green Belt - Similar to Black Belt but not a full-time position.
Master Black Belt - First and foremost teachers. They also review and mentor Black Belts. Selection criteria for Master Black Belts are quantitative skills and the ability to teach and mentor. Master Black Belts are full-time positions.
Variance - A change in a process or business practice that may alter its expected outcome.
 Statistics and robustness
The core of the Six Sigma methodology is a data-driven, systematic approach to problem solving, with a focus on customer impact. Statistical tools and analysis are often useful in the process. However, it is a mistake to view the core of the Six Sigma methodology as statistics; an acceptable Six Sigma project can be started with only rudimentary statistical tools.
Still, some professional statisticians criticize Six Sigma because practitioners have highly varied levels of understanding of the statistics involved.
Six Sigma as a problem-solving approach has traditionally been used in fields such as business, engineering, and production processes.
 Roles required for implementation
Six Sigma identifies five key roles for its successful implementation.
Executive Leadership includes CEO 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 organization in an integrated manner. The Executive Leadership draws them from the upper management. Champions also act as mentor to Black Belts. At GE this level of certification is now called "Quality Leader".
Master Black Belts, identified by champions, act as in-house expert coach for the organization on Six Sigma. They devote 100% of their time to Six Sigma. They assist champions and guide Black Belts and Green Belts. Apart from the usual rigor of statistics, their time is spent on ensuring integrated deployment of Six Sigma across various functions and departments.
Experts This level of skill is used primarily within Aerospace and Defense Business Sectors. Experts work across company boundaries, improving services, processes, and products for their suppliers, their entire campuses, and for their customers. Raytheon Incorporated was one of the first companies to introduce Experts to their organizations. At Raytheon, Experts work not only across multiple sites, but across business divisions, incorporating lessons learned throughout the company.
Black Belts operate under Master Black Belts to apply Six Sigma methodology to specific projects. They devote 100% of their time to Six Sigma. They primarily focus on Six Sigma project execution, whereas Champions and Master Black Belts focus on identifying projects/functions for Six Sigma.
Green Belts are the employees who take up Six Sigma implementation along with their other job responsibilities. They operate under the guidance of Black Belts and support them in achieving the overall results.
In many successful modern programs, Green Belts and Black Belts are empowered to initiate, expand, and lead projects in their area of responsibility. The roles as defined above, therefore, conform to the antiquated Mikel Harry/Richard Schroeder model, which is far from being universally accepted. The terms black belt and green belt are borrowed from the ranking systems in various martial arts.
Bill Smith did not really "invent" Six Sigma in the 1980s; rather, he applied methodologies that had been available since the 1920s developed by luminaries like Shewhart, Deming, Juran, Ishikawa, Ohno, Shingo, Taguchi and Shainin. All tools used in Six Sigma programs are actually a subset of the Quality Engineering discipline and can be considered a part of the ASQ Certified Quality Engineer body of knowledge. The goal of Six Sigma, then, is to use the old tools in concert, for a greater effect than a sum-of-parts approach.
The use of "Black Belts" as itinerant change agents is controversial as it has created a cottage industry of training and certification. This relieves management of accountability for change; pre-Six Sigma implementations, exemplified by the Toyota Production System and Japan's industrial ascension, simply used the technical talent at hand—Design, Manufacturing and Quality Engineers, Toolmakers, Maintenance and Production workers—to optimize the processes.
The expansion of the various "Belts" to include "Green Belt", "Master Black Belt" and "Gold Belt" is commonly seen as a parallel to the various "Belt Factories" that exist in martial arts.
 The term Six Sigma
Sigma (the lower-case Greek letter ó) is used to represent standard deviation (a measure of variation) of a population (lower-case 's', is an estimate, based on a sample). The term "six sigma process" comes from the notion that if one has six standard deviations between the mean of a process and the nearest specification limit, he will make practically no items that exceed the specifications. This is the basis of the Process Capability Study, often used by quality professionals. The term "Six Sigma" has its roots in this tool, rather than in simple process standard deviation, which is also measured in sigmas. Criticism of the tool itself, and the way that the term was derived from the tool, often sparks criticism of Six Sigma.
The widely accepted definition of a six sigma process is one that produces 3.4 defective parts per million opportunities (DPMO). A process that is normally distributed will have 3.4 parts per million beyond a point that is 4.5 standard deviations above or below the mean (one-sided Capability Study). This implies that 3.4 DPMO corresponds to 4.5 sigmas, not six as the process name would imply. This can be confirmed by running on QuikSigma or Minitab a Capability Study on data with a mean of 0, a standard deviation of 1, and an upper specification limit of 4.5. The 1.5 sigmas added to the name Six Sigma are arbitrary and they are called "1.5 sigma shift" (SBTI Black Belt material, ca 1998). Dr. Donald Wheeler dismisses the 1.5 sigma shift as "goofy".
In a Capability 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". As process standard deviation goes up, or the mean of the process moves away from the center of the tolerance, the Process Capability sigma number goes down, because fewer standard deviations will then fit between the mean and the nearest specification limit (see Cpk Index). The notion that, in the long term, processes usually do not perform as well as they do in the short term is correct. That requires that Process Capability sigma based on long term data is less than or equal to an estimate based on short term sigma. However, the original use of the 1.5 sigma shift is as shown above, and implicitly assumes the opposite.
As sample size increases, the error in the estimate of standard deviation converges much more slowly than the estimate of the mean (see confidence interval). Even with a few dozen samples, the estimate of standard deviation often drags an alarming amount of uncertainty into the Capability 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 Capability Studies often ought not to be taken too literally.
Estimates 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. Unfortunately, there are no means for proving that data belong to any particular distribution. One can only assume normality, based on finding no evidence to the contrary. Estimating defective parts per million down into the 100s or 10s 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.
 The ±1.5 Sigma Drift
The ±1.5 sigma drift is the drift of a process mean, which occurs in all processes in a six sigma program. If a product being manufactured measures 100 ± 3 cm (97 – 103 cm), over time the ±1.5 sigma drift may cause the average to range up to 98.5 - 104.5 cm or down to 95.5 - 101.5 cm. This could be of significance to customers.
The ±1.5 shift was introduced by Mikel Harry. Harry referred to a paper about tolerancing, the overall error in an assembly is affected by the errors in components, written in 1975 by Evans, "Statistical Tolerancing: The State of the Art. Part 3. Shifts and Drifts". Evans refers to a paper by Bender in 1962, "Benderizing Tolerances – A Simple Practical Probability Method for Handling Tolerances for Limit Stack Ups". He looked at the classical situation with a stack of disks and how the overall error in the size of the stack, relates to errors in the individual disks. Based on "probability, approximations and experience", Bender suggests:
Harry then took this a step further. Supposing that there is a process in which 5 samples are taken every half hour and plotted on a control chart, Harry considered the "instantaneous" initial 5 samples as being "short term" (Harry's n=5) and the samples throughout the day as being "long term" (Harry's g=50 points). Due to the random variation in the first 5 points, the mean of the initial sample is different to the overall mean. Harry derived a relationship between the short term and long term capability, using the equation above, to produce a capability shift or "Z shift" of 1.5. Over time, the original meaning of "short term" and "long term" has been changed to result in "long term" drifting means.
Harry has clung tenaciously to the "1.5" but over the years, its derivation has been modified. In a recent note from Harry "We employed the value of 1.5 since no other empirical information was available at the time of reporting." In other words, 1.5 has now become an empirical rather than theoretical value. A further softening from Harry: "... the 1.5 constant would not be needed as an approximation".
Despite this, industry has fixed on the idea that it is impossible to keep processes on target. No matter what is done, process means will drift by ±1.5 sigma. In other words, if a process has a target value of 10.0, and control limits work out to be 13.0 and 7.0, over the long term the mean will drift to 11.5 (or 8.5), with control limits changing to 14.5 and 8.5.
In truth, any process where the mean changes by 1.5 sigma, or any other amount, is not in statistical control. Such a change can often be detected by a trend on a control chart. A process that is not in control is not predictable. It may begin to produce defects, no matter where specification limits have been set.
 Digital Six Sigma
In an effort to permanently minimize variation, Motorola has evolved the Six Sigma methodology to use information systems tools to make business improvements absolutely permanent. Motorola calls this effort Digital Six Sigma.
 Some companies that have embraced it have done poorly
The cartoonist Scott Adams featured Six Sigma in a Dilbert cartoon published on November 26th 2006. When the process is introduced to his company Dilbert asks "Why don't we jump on a fad that hasn't already been widely discredited?" The Dilbert character states "Fortune magazine says... blah blah... most companies that used Six Sigma have trailed the S&P 500."
Dilbert was referring to an article in Fortune which stated that "of 58 large companies that have announced Six Sigma programs, 91 percent have trailed the S&P 500 since." The statement is attributed to "an analysis by Charles Holland of consulting firm Qualpro (which espouses a competing quality-improvement process)." The gist of the article is that Six Sigma is effective at what it is intended to do, but that it is "narrowly designed to fix an existing process" and does not help in "coming up with new products or disruptive technologies."
 Based on arbritrary standards
While 3.4 defects per million might work well for certain products/processes, it might not be ideal for others. A pacemaker might need higher standards, for example, whereas a direct mail advertising campaign might need less. The basis and justification for choosing 6 as the number of standard deviations is not clearly explained.
Examples of some key tools used
ANOVA Gage R&R
Catapult Exercise on variability
Cause & Effects Diagram (a.k.a. Fishbone or Ishikawa Diagram)
Chi-Square Test of Independence and Fits
Cost Benefit Analysis
Customer Output Process Input Supplier Maps
Design of Experiments
Failure Modes Effects Analysis
General Linear Model
Homogeneity of Variance
Thought Process Map
 Software used for Six Sigma
There are generally two classes of software used to support Six Sigma: analysis tools, which are used to perform statistical or process analysis, and program management tools, used to manage and track a corporation's entire Six Sigma program. Analysis tools include statistical software such as Minitab, JMP, SigmaXL, RapAnalyst or Statgraphics as well as process analysis tools such as iGrafx. Some alternatives include Microsoft Visio, Telelogic System Architect, IBM WebSphere Business Modeler, and Proforma Corp. ProVision. For program management, tracking and reporting, the most popular tools are Instantis, PowerSteering, iNexus and SixNet. Other Six Sigma for IT Management tools include Proxima Technology Centauri, HP Mercury, BMC Remedy.
Six Sigma was industry specific
The average was very subjective in nature, it was very difficult to define average
There were problems in finding whether six sigma has been achieved or not.
 List of Six Sigma companies
Bank of America
Advanced Micro Devices
Honeywell International
The Boeing Company
Littlewoods Shop Direct Group
^ Motorola University - What is Six Sigma?. Retrieved on 29 January, 2006.
^ The Inventors of Six Sigma. Retrieved on 29 January, 2006.
^ Motorola University Six Sigma Dictionary. Retrieved on 29 January, 2006.
^ Motorola Inc. - Motorola University. Retrieved on 29 January, 2006.
^ About Motorola University. Retrieved on 29 January, 2006.
^ Averboukh, Elena A.. Six Sigma Trends: Six Sigma Leadership And Innovation Using TRIZ. Retrieved on 13 November, 2006.
^ Joseph A. De Feo & William W Barnard. JURAN Institute's Six Sigma Breakthrough and Beyond - Quality Performance Breakthrough Methods, Tata McGraw-Hill Publishing Company Limited, 2005. ISBN 0-07-059881-9
^ Mikel Harry & Richard Schroeder. Six Sigma, Random House, Inc, 2000. ISBN 0-385-49437-8
^ Tonner, Craig; Patra, Pradeep (2003-09-03). Six Sigma (English). Retrieved on 2006-11-26.
^ Wheeler, Donald J., Phd, The Six Sigma Practitioner's Guide to Data Analysis, p307, http://www.spcpress.com
^ Betsy Morris (2006-07-11). Old rule: be lean and mean. Fortune. Retrieved on 2006-11-26.
^ Six Sigma - a roadmap to breakthrough performance. 3M. Retrieved on 2007-01-07.
^ Remarks to the 33rd Annual Banc of America Securities Investment Conference. Bank of America. Retrieved on 2007-02-04.
^ Technology partners. Advanced Micro Systems. Retrieved on 2007-01-08.
^ Company Information. Caterpillar Inc.. Retrieved on 2007-01-08.
^ Better, faster, cheaper—but most of all, better. The Boeing Company. Retrieved on 2007-02-02.
^ Six Sigma at Amazon.com.
^ 2006 Business Excellence Awards, North of England, URL accessed February 26, 2007.
From India, Mumbai
medha.mathuri think this was one of the most comprehensive articles on six sigma...have been trying to understand this concept for the past two years but nobody has been able to describe it so well...hats off to you pranati !
keep it up ! :)
From India, Gurgaon
khatrijayaIts great. I forwarded the same document to lot of my friends and believe me, everyone praised Praniti’s contribution. Good job done Praniti. Keep posting. Thanks indeed. Jaya
From India, Delhi
rahul3232can any body send me paranties ppt on six sigma..... could not download it ... lots of appreciation must be good
From India, Pune
Its a great presentation, i was struggling to understand the six sigma processes. It helped me a lot..
Thanks a lot Pranati
K. Uday Gupta
Asst Manager Operations
From India, Bangalore
ksa04Hi Binzy, Hope this presentation is uesful....
From India, Madras
Anoo27Hey Pranati this is the first time I am reading about 6 Sigma in plain simple English, too good of an Article, do keep posting things like this
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From India, Mumbai
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