Six Sigma

Six Sigma is a quality improvement philosophy and a methodology and collection of statistical techniques used to implement that philosophy. The purpose of Six Sigma is to reduce or remove identifiable sources of variation that result in defective outputs in a manufacturing or other process, so that only small amounts of random variation remain. Implementation of the Six Sigma standard produces no more than 3.4 defects per million units of output. Regular collection and analysis of data is key to the Six Sigma approach, which rests on the assumption that the outputs of a process are the product of inputs that can be defined and controlled.

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Overview

The roots of the Six Sigma philosophy and methodology lie in the 1920s, when the American engineer Walter Shewhart, working for the Bell Telephone Company, developed the first control charts. W. Edwards Deming, an American statistician, applied many of Shewhart’s ideas to the reconstruction of Japanese industries after World War II. However, the concepts and practices of Six Sigma became well known only in the 1980s and 1990s, when companies such as Motorola and General Electric adopted them. In the twenty-first century, Six Sigma concepts and techniques continued to be applied in many different settings, including health care and financial services, as well as manufacturing.

Quality in Six Sigma is defined in terms of the customer’s needs and desires, so a defect is defined as any aspect of output that does not meet these needs and desires, from a machine part of the wrong dimension to an unreasonably long waiting time in the emergency room. Six Sigma focuses on reducing variations in the manufacturing process that are critical to characteristics of quality (CTQs) as defined by the customer.

The most common Six Sigma methodology is DMAIC: Define, Measure, Analyze, Improve, and Control. DMAIC is often used to refine existing processes and begins by defining the goal of a project and the problems to be solved. This is followed by a measurement phase in which data is collected to understand the current state of the process. This data is then analyzed to determine what, in the current process, is responsible for the observed defects. Using this information, the process is improved to remove the cause of the defects, and the improved process is then controlled and monitored to confirm that it continues to operate optimally. In addition to identifying problems and seeking to resolve them, effective Six Sigma organizations set goals, create and adhere to action plans, quantify and track progress, collaborate, and allow data to drive decision-making.

Lean Six Sigma is the application of Six Sigma concepts to a lean manufacturing process (one that focuses on reduction of waste by eliminating the use of resources for any purpose that does not create value for the customer). Eight types of waste are targeted for elimination in a Lean Six Sigma process: transportation, inventory, motion, waiting, overproduction, overprocessing, defects, and unused talent.

One tool closely identified with the Six Sigma approach is the control chart, which displays characteristics of output (for instance, the diameter of a screw) as produced over time, with lines indicating the ideal dimensions and allowable limits. Examining control charts allows an analyst to see when a process is going out of control, i.e., producing output that is defective, and to correct the error.

A common criticism of the Six Sigma methodology has been that its rigid focus on quality control may come at the cost of the creativity and innovation needed to generate new ideas and products, the core of company growth. Another has been that proper implementation of Six Sigma requires sophisticated mathematical and technical knowledge, and that unintended consequences may result if it is improperly executed.

Bibliography

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