Six Sigma

Six Sigma (6σ) is a set of techniques and tools for process improvement. It was introduced by American engineer Bill Smith while working at Motorola in 1986. A six sigma process is one in which 99.99966% of all opportunities to produce some feature of a part are statistically expected to be free of defects.

Six Sigma strategies seek to improve manufacturing quality by identifying and removing the causes of defects and minimizing variability in manufacturing and business processes. It does this by using empirical and statistical quality management methods and by hiring people who serve as Six Sigma experts. Each Six Sigma project follows a defined methodology and has specific value targets, such as reducing pollution or increasing customer satisfaction.

The term Six Sigma originates from statistical modeling of manufacturing processes. The maturity of a manufacturing process can be described by a sigma rating indicating its yield or the percentage of defect-free products it creates—specifically, to within how many standard deviations of a normal distribution the fraction of defect-free outcomes corresponds.

Doctrine

Six Sigma asserts that:

1. Continuous efforts to achieve stable and predictable process results (e.g., by reducing process variation) are of vital importance to business success.
2. Manufacturing and business processes have characteristics that can be defined, measured, analyzed, improved, and controlled.
3. Achieving sustained quality improvement requires commitment from the entire organization, particularly from top-level management.

Features that set Six Sigma apart from previous quality-improvement initiatives include:

1. Focus on achieving measurable and quantifiable financial returns
2. Emphasis on management leadership and support
3. Commitment to making decisions on the basis of verifiable data and statistical methods rather than assumptions and guesswork

In fact, lean management and Six Sigma share similar methodologies and tools, including the fact that both were influenced by Japanese business culture. However, lean management primarily focuses on eliminating waste through tools that target organizational efficiencies while integrating a performance improvement system, while Six Sigma focuses on eliminating defects and reducing variation. Both systems are driven by data, though Six Sigma is much more dependent on accurate data.

Six Sigma's implicit goal is to improve all processes but not necessarily to the 3.4 Defects Per Million Opportunities(DPMO) level. Organizations need to determine an appropriate sigma level for each of their most important processes and strive to achieve these. As a result of this goal, it is incumbent on management of the organization to prioritize areas of improvement.

Methodologies

Six Sigma projects follow two project methodologies, inspired by W. Edwards Deming's Plan–Do–Study–Act Cycle, each with five phases.[6]

1. DMAIC ("duh-may-ick", /də.ˈmeɪ.ɪk/) is used for projects aimed at improving an existing business process
2. DMADV ("duh-mad-vee", /də.ˈmæd.vi/) is used for projects aimed at creating new product or process designs

DMAIC

The DMAIC project methodology has five phases:

1. Define the system, the voice of the customer and their requirements, and the project goals, specifically.
2. Measure key aspects of the current process and collect relevant data; calculate the "as-is" process capability
3. Analyze the data to investigate and verify cause and effect. Determine what the relationships are, and attempt to ensure that all factors have been considered. Seek out the root cause of the defect under investigation.
4. Improve or optimize the current process based upon data analysis using techniques such as design of experiments, poka yoke or mistake proofing, and standard work to create a new, future state process. Set up pilot runs to establish process capability.
5. Control the future state process to ensure that any deviations from the target are corrected before they result in defects. Implement control systems such as statistical process control, production boards, visual workplaces, and continuously monitor the process. This process is repeated until the desired quality level is obtained.

Some organizations add a Recognize step at the beginning, which is to recognize the right problem to work on, thus yielding an RDMAIC methodology.

DMADV

Also known as DFSS ("Design For Six Sigma"), the DMADV methodology's five phases are:[6]

1. Define design goals that are consistent with customer demands and the enterprise strategy.
2. Measure and identify CTQs (characteristics that are Critical To Quality), measure product capabilities, production process capability, and measure risks.
3. Analyze to develop and design alternatives
4. Design an improved alternative, best suited per analysis in the previous step
5. Verify the design, set up pilot runs, implement the production process and hand it over to the process owner(s).

Proffessionalization

One key innovation of Six Sigma involves professionalizing quality management. Prior to Six Sigma, quality management was largely relegated to the production floor and to statisticians in a separate quality department. Formal Six Sigma programs adopt an elite ranking terminology similar to martial arts systems like judo to define a hierarchy (and career path) that spans business functions and levels.

Six Sigma identifies several roles for successful implementation:[12]

1. Executive Leadership includes the CEO and other members of top management. They are responsible for setting up a vision for Six Sigma implementation. They also empower other stakeholders with the freedom and resources to transcend departmental barriers and overcome resistance to change.[13]
2. Champions take responsibility for Six Sigma implementation across the organization. The Executive Leadership draws them from upper management. Champions also act as mentors to Black Belts.
3. Master Black Belts, identified by Champions, act as in-house coaches on Six Sigma. They devote all of their time to Six Sigma, assisting Champions and guiding Black Belts and Green Belts. In addition to statistical tasks, they ensure that Six Sigma is applied consistently across departments and job functions.
4. Black Belts operate under Master Black Belts to apply Six Sigma to specific projects. They also devote all of their time to Six Sigma. They primarily focus on Six Sigma project execution and special leadership with special tasks, whereas Champions and Master Black Belts focus on identifying projects/functions for Six Sigma.
5. Green Belts are the employees who take up Six Sigma implementation along with their other job responsibilities, operating under the guidance of Black Belts.

According to proponents, special training is needed for all of these practitioners to ensure that they follow the methodology and use the data-driven approach correctly.

Some organizations use additional belt colors, such as "yellow belts", for employees that have basic training in Six Sigma tools and generally participate in projects, and "white belts" for those locally trained in the concepts but do not participate in the project team. "Orange belts" are also mentioned to be used for special cases.

Certification

General Electric and Motorola developed certification programs as part of their Six Sigma implementation. Following this approach, many organizations in the 1990s started offering Six Sigma certifications to their employees. In 2008 Motorola University later co-developed with Vative and the Lean Six Sigma Society of Professionals a set of comparable certification standards for Lean Certification.

Criteria for Green Belt and Black Belt certification vary; some companies simply require participation in a course and a Six Sigma project.[16] There is no standard certification body, and different certifications are offered by various quality associations for a fee.

The American Society for Quality, for example, requires Black Belt applicants to pass a written exam and to provide a signed affidavit stating that they have completed two projects or one project combined with three years' practical experience in the body of knowledge.

Tools and methods

Within the individual phases of a DMAIC or DMADV project, Six Sigma uses many established quality-management tools that are also used outside Six Sigma. The following table shows an overview of the main methods used.

1. 5 Whys
2. Statistical and fitting tools a. Analysis of variance b. General linear model c. ANOVA Gauge R&R d. Regression analysis e. Correlation f. Scatter diagram g. Chi-squared test
3. Axiomatic design
4. Business Process Mapping/Check sheet
5. Cause & effects diagram (also known as fishbone or Ishikawa diagram)
6. Control chart/Control plan (also known as a swimlane map)/Run charts
7. Cost–benefit analysis
8. CTQ tree
9. Design of experiments/Stratification
10. Histograms/Pareto analysis/Pareto chart
11. Pick chart/Process capability/Rolled throughput yield
12. Quality Function Deployment (QFD)
13. Quantitative marketing research through use of Enterprise Feedback Management (EFM) systems
14. Root cause analysis
15. SIPOC analysis (Suppliers, Inputs, Process, Outputs, Customers)
16. COPIS analysis (Customer centric version/perspective of SIPOC)
17. Taguchi methods/Taguchi Loss Function
18. Value stream mapping

Inadequacies

1. Quality expert Philip B. Crosby pointed out that the Six Sigma standard does not go far enough—customers deserve defect-free products every time. For example, under the Six Sigma standard, semiconductors, which require the flawless etching of millions of tiny circuits onto a single chip are all defective.

2. The use of "Black Belts" as itinerant change agents has fostered an industry of training and certification. Critics have argued there is overselling of Six Sigma by too great a number of consulting firms, many of which claim expertise in Six Sigma when they have only a rudimentary understanding of the tools and techniques involved or the markets or industries in which they are acting.

3. Stifling creativity in research. According to John Dodge, editor in chief of Design News, the use of Six Sigma is inappropriate in a research environment. Dodge states "excessive metrics, steps, measurements and Six Sigma's intense focus on reducing variability water down the discovery process. Under Six Sigma, the free-wheeling nature of brainstorming and the serendipitous side of discovery is stifled." He concludes "there's general agreement that freedom in basic or pure research is preferable while Six Sigma works best in incremental innovation when there's an expressed commercial goal."

4. One criticism voiced by Yasar Jarrar and Andy Neely from the Cranfield School of Management's Centre for Business Performance is that while Six Sigma is a powerful approach, it can also unduly dominate an organization's culture; and they add that much of the Six Sigma literature – in a remarkable way (six-sigma claims to be evidence, scientifically based) – lacks academic rigor:

   One final criticism, probably more to the Six Sigma literature than concepts, relates to the evidence for Six Sigma’s success. So far, documented case studies using the Six Sigma methods are presented as the strongest evidence for its success. However, looking at these documented cases, and apart from a few that are detailed from the experience of leading organizations like GE and Motorola, most cases are not documented in a systemic or academic manner. In fact, the majority are case studies illustrated on websites, and are, at best, sketchy. They provide no mention of any specific Six Sigma methods that were used to resolve the problems. It has been argued that by relying on the Six Sigma criteria, management is lulled into the idea that something is being done about quality, whereas any resulting improvement is accidental (Latzko 1995). Thus, when looking at the evidence put forward for Six Sigma's success, mostly by consultants and people with vested interests, the question that begs to be asked is: are we making a true improvement with Six Sigma methods or just getting skilled at telling stories? Everyone seems to believe that we are making true improvements, but there is some way to go to document these empirically and clarify the causal relations.