Six Sigma Methodology seeks to improve the quality of process outputs by identifying and removing the causes of defects (errors) and minimizing variability in manufacturing and business processes. It uses a set of quality management methods, including statistical methods, and creates a special infrastructure of people within the organization with the use of a hierarchy of Six Sigma Belts and Six Sigma Certification levels called Black Belts, Green Belts, Yellow Belts, White Belts, and Champions who are experts in the methods.
Six Sigma Methodology asserts that:
- Continuous efforts to achieve stable and predictable process results (i.e., reduce process variation) are of vital importance to business success.
- Manufacturing and business processes have characteristics that can be measured, analyzed, controlled and improved.
- 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:
- A clear focus on achieving measurable and quantifiable financial returns from any Six Sigma project.
- An increased emphasis on strong and passionate management leadership and support.
- A clear commitment to making decisions on the basis of verifiable data and statistical methods, rather than assumptions and guesswork.
- In recent years, practitioners have combined Six Sigma ideas with Lean Manufacturing to create a methodology named Six Sigma Certification. The Lean Six Sigma methodology views lean manufacturing, which addresses process flow and waste issues, and Six Sigma, with its focus on variation and design, as complementary disciplines aimed at promoting “business and operational excellence”. Companies such as GE, Verizon, GENPACT, and IBM use Lean Six Sigma to focus transformation efforts not just on efficiency but also on growth. It serves as a foundation for innovation throughout the organization, from manufacturing and software development to sales and service delivery functions.
Six Sigma Methodologies
Six Sigma projects follow two project methodologies inspired by Deming’s Plan-Do-Check-Act Cycle. These methodologies, composed of five phases each, bear the acronyms DMAIC and DMADV.
- DMAIC is used for projects aimed at improving an existing business process. DMAIC is pronounced as “duh-may-ick” (<ˌdʌ ˈmeɪ ɪk>).
- DMADV is used for projects aimed at creating new product or process designs. DMADV is pronounced as “duh-mad-vee” (<ˌdʌ ˈmæd vi>).
The DMAIC project methodology has five phases:
- Define the system, the voice of the customer and their requirements, and the project goals, specifically.
- Measure key aspects of the current process and collect relevant data.
- Analyze the data to investigate and verify cause-and-effect relationships. Determine what the relationships are, and attempt to ensure that all factors have been considered. Seek out root cause of the defect under investigation.
- 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.
- Control the future state process to ensure that any deviations from 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.
- 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 or DFSS
The DMADV project methodology, known as DFSS (“Design For Six Sigma”), features five phases:
- Define design goals that are consistent with customer demands and the enterprise strategy.
- Measure and identify CTQs (characteristics that are Critical To Quality), product capabilities, production process capability, and risks.
- Analyze to develop and design alternatives
- Design an improved alternative, best suited per analysis in the previous step
- Verify the design, set up pilot runs, implement the production process and hand it over to the process owner(s).