Six Sigma

Overview of Six Sigma Methodologies (DMAIC and DFSS)

Six-Sigma is a well disciplined and structured set of techniques and tools for process improvement and quality attainment. The strategy was introduced by engineer Bill Smith while working at Motorola in 1986. Jack Welch made it central to his business strategy at General Electric in 1995. Today, it is successfully used in many industrial sectors.

As with TQMOpens in new window, the key focus of all Six Sigma is to optimize overall business results by balancing cost, quality; as well as improving customer satisfaction, work processes, profitability, speed, and efficiencies of all kinds.

What Exactly Is Six Sigma?

Six Sigma is a smarter way to manage a business or a department. Six Sigma puts the customer first and uses facts and data to drive better solutions.

Six Sigma is a method that provides businesses with tools to improve the capability of their business processes. It brings about increase in performance, improvement in profits, reduction in defect, boosts in employee morale, quality of products or services, which ultimately culminates in customer satisfaction.

The term Six Sigma is derived from statistics and is used in statistical quality control, which evaluates process capability.

Sigma is a letter (σ) in the Greek alphabet used to denote the standard deviation of a process. A standard deviation measures the variation or amount of spread about the process mean. A process with Six Sigma capability exhibits twelve standard deviations between the upper and lower specification limits. Essentially, under Six Sigma, process variation is reduced so that no more than 3.4 parts per million fall outside the specification limits. The higher the sigma level, the more assurance we have in the process producing defect-free outcomes.

Six Sigma is both a statistical concept that measures the number of nonconformities in a product or service, and a quality improvement methodology that helps to analyze problems and find the solutions and control the nonconformities. Six Sigma methodologies target three main areas:

  • Improving customer satisfaction
  • Reducing cycle time
  • Reducing defect

Improvements in these areas usually represent dramatic cost savings to businesses, as well as opportunities to attain customers, capture new markets, and build a reputation for top performing products and services.

Achieving the goal of Six Sigma requires more than small, incremental improvements; it requires breakthroughs in every area of an operation. In statistical terms, “reaching Six Sigma” means that your process or product will perform with almost no defects.

But the real message of Six Sigma goes beyond statistics. Six Sigma is a total management commitment and philosophy of excellence, customer focus, process improvement, and the rule of measurement rather than gut feel.

Six Sigma is about making every area of the organization better able to meet the changing needs of customers, markets, and technologies — with benefits for employees, customers, and shareholders.

In that sense, Six Sigma is a more strategic and more aggressive initiative than simple improvement projects.

One particularly eloquent testimonial of the impact of Six Sigma is provided by Robert W. GalvinOpens in new window, previous Chairman of the Executive Committee, Motorola, IncOpens in new window. In the foreword to the book Modern Industrial Statistics: Design and Control of Quality and Reliability by Kenett and Zacks, Galvin states:

At Motorola we use statistical methods daily throughout all of our disciplines to synthesize an abundance of data to derive concrete actions. … How has the use of statistical methods within Motorola Six Sigma initiative, across disciplines, contributed to our growth? Over the past decade we have reduced in-process defects by over 300 fold, which has resulted in a cumulative manufacturing cost savings of over 11 billion dollars.

Terminologies in Six Sigma

  1.    Green Belt

An employee of an organization who participates in a Six Sigma team is referred to as Green Belt.

A Green Belt will have sufficient knowledge to support and champion Six Sigma implementation and to participate in Six Sigma projects as team leader or team member.

  1.    Black Belt

A managerial level or technical specialist assigned full responsibility to implement Six Sigma throughout the business unit is referred to as Black Belt.

This term, as well as Six Sigma, Green Belts, etc., were coined by Motorola and adopted by other organizations as a de facto industry standard.

A Black Belt is a Six Sigma implementation expert. Each project is expected to have at least one Black Belt as a team member. Many companies have experienced the benefits of Six Sigma with, on average, savings between $50,000 and $250,000 per project.

Black Belts, with 100% of their time allocated to projects, can executed five or six projects during a 12-month period, potentially adding over $1 million to annual profits.

DMAIC

Six Sigma improvement projects are orchestrated from the executive-level Quality Council and consist of a Define–Measure–Analyze–Improve–Conrol (DMAIC) roadmap.

DMAIC (an acronym for Define, Measure, Analyze, Improve, and Control ) refers to a data-driven improvement cycle used for improving, optimizing and stabilizing business processes and designs.

The DMAIC improvement cycle is the core tool used to drive Six Sigma projects:

  • Define phase is where a particular process problem is identified and the solution is planned
  • Measure is where the relevant data is collected and the extent of the problem is determined
  • Improve is where the plan to improve the process is put into effect
  • Control is where the change is piloted to determine if organizational business goals are being achieved and the change is monitored after deployment to ensure that process improvement goals are being achieved.

Within Six Sigma training, the Measure phase encompasses more than just measurements. It typically includes the tracking of key process output variables (KPOVs) over time, quantifying the process capability of these variables, gaining insight into improvement opportunities through the application of cause-and-effect diagrams and failure mode and effects analysis (FMEA), and quantifying the effectiveness of current measurement systems.

These activities help define how a key process output variable (KPOV) is performing, and how it could relate to its primary upstream causes, the key process input variables (KPIVs). The Measure step is repeated at successive business, operations, and process levels of the organization, measuring baseline information for KPOVs in order to provide an accurate picture of the overall variation that the customer sees.

Measurements provide estimates of the process capability relative to specifications and drive investigations of all significant sources of variation, including measurement system analyses, which provide us with insight into the accuracy of measurements. This information is then used throughout the Analyze, Improve, and Control phases to help make overall business improvements.

Several unique Six Sigma metrics, such as sigma quality level, yield, and cost of poor quality (COPQ), have been deployed to help quantify and reduce the “hidden factory,” that is, hidden, non-added-value production costs.

Six Sigma relies heavily on the ability to access information. When the most important information is hard to find, access, or understand, the result is extra effort that increases both the hidden factory and the cost of poor quality (COPQ).

Many organizations set a dollar threshold as they begin to prioritize Six Sigma projects. Successful projects thereby provide returns that will pay for up-front investments in Six Sigma training and full-time Black Belt team leaders.

The definition of what types of savings are considered is also critical and drives specific behaviors to the identification of the low-hanging fruit first.

In many organizations, soft or indirect benefits fall into categories such as cost avoidance related to regulatory or legal compliance, or benefits related to improving employee morale or efficiency. Such benefits cannot be tied directly to operating margins or incremental revenues through a specific measurement.

DFSS

Design for Six Sigma (DFSS) is a Six Sigma quality process focused on the Quality Planning of the Juran Trilogy.

The DMAIC methodology requires that a process be in place and functioning. In contrast, DFSS has the objective of determining the needs of customers and the business, and driving those needs into product solution created.

Unlike the DMAIC methodology aimed at improving an existing product or process, the DFSS approach is used during development of new products or services. The DFSS model is based on the five-step DMADV cycle: Define–Measure–Analyze–Design–Verify.

DMADV is applied to new processes or products whose goal is to achieve Six Sigma quality levels. We now review these basic steps:

  • Define consists in defining project goals and customer demands (both external and internal).
  • Measure involves measuring and quantifying the expectations and requirements of customers.
  • Analyze is analyzing the options of the process required to meet the needs of the customer.
  • Design consists in detailed designing of processes to meet the needs of the customers.
  • Verify is verification of the designed performance and the ability to meet the needs of the customer.

DFSS is especially relevant to integrated systems with significant system development.

DFSS seeks to avoid manufacturing/service process problems by using systems engineering techniques of problem avoidance and robust designs at the outset (i.e., fire prevention).

These techniques include tools and processes to predict, model, and simulate the product delivery system as well as the analysis of the system life cycle itself to ensure customer satisfaction from the proposed system design solution. In this way, DFFSS is closely related to systems engineeringOpens in new window, operations researchOpens in new window, systems architectingOpens in new window, and concurrent engineeringOpens in new window.

DFSS is largely a design activity requiring specialized tools, including quality function deployment (QFD)Opens in new window, axiomatic designOpens in new window, TRIZOpens in new window, Design for XOpens in new window, Design of Experiments (DoE)Opens in new window, Taguchi methodsOpens in new window, tolerance designOpens in new window, RobustificationOpens in new window, and response surface methodologyOpens in new window.

While these tools are sometimes used in the classic DMAIC Six Sigma process, they are uniquely used by DFSS to analyze new and unprecedented systems/products. DMAIC improvements and DMADV designs result in changes in processes, activities, definition of roles and responsibilities, and interactions between different parts of the organization.

Six Sigma roadmaps typically consist of a 6-month intensive program combining training and the implementation of projects. The training of Black Belts typically consists of 16 full-time equivalent training days with projects that usually span 6 months.

Following completion of the projects and the training program, the project leaders get certified as Black Belts. A typical small- or medium-sized development organization will identify two or three Black Belt candidates and launch two or three Six Sigma projects defined after an initial one-day training of the management team. Projects are conducted in teams led by a Black Belt. A Master Black Belt mentors the various projects and provides the necessary training.

To graduate as a certified Black Belt, the candidates must demonstrate knowledge in the tools and methodologies of the Six Sigma Body of Knowledge, in addition to completing a Six Sigma project.

As part of Six Sigma Black Belt training, the Master Black Belt reviews, critiques, and advises the Black Belt candidates throughout their training. A typical Six Sigma roadmap covers the following topics in a mixture of frontal and hands-on training and implementation steps as outlined below:

Month 1, DEFINE:
  • Six Sigma Basics
  • Elicitation of potential Six Sigma projects
  • Screenng of Six Sigma projects and Black Belt candidates
  • Defining and launching of Six Sigma project
Month 2, MEASURE
  • Process baselining
  • VOC and QFD
  • Seven basic tools
  • Process flow mapping
  • Data collection and analysis
  • Defect metrics
  • Cycle-time assessment
  • Benchmarking
Month 3, ANALYZE:
  • Project reviews
  • Process capability analysis
  • Measurement system evaluation
  • FMEA
  • Systems thinking
  • Statistical thinking
  • Control charts
  • 10X metrics/capability
  • Statistical inference
  • Decision and risk analysis
  • Project management
  • Financial impact assessment
Month 4, IMPROVE:
  • Project reviews
  • Regression modeling
  • Design of experiments
  • Tolerancing
  • Variance components
Month 5, IMPROVE:
  • Project reviews
  • Robust design
  • Pugh concepts
  • DFA/DFM
  • Lean manufacturing
Month 6, CONTROL:
  • Project reviews
  • Evaluation of results
  • Post project assessment
  • Lessons learned
  • Where else?

Six Sigma didn’t spring up overnight. Its background stretches back eighty-plus years, from management science concepts developed in the United States to Japanese management breakthroughs to “Total Quality” efforts in the 1970s and 1980s. But its real impact can be seen the waves of change and positive results sweeping such companies as General Electric (GE), Motorola, Johnson & Johnson, and American Express.

    Research data for this work have been adapted from the manuals:
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  2. Lucas, J. M. (2002, January). The essential Six-Sigma. Quality Progress,
  3. Snee, R. D. (2004). Six Sigma: The evolution of a 100 years of business improvement methodology. International Journal of Six Sigma and Competitive Advantage, 1(1), 4 – 20.
  4. Sheehy, P., Navarro, D., Silvers, R., Keyes, V., & Dixon, D. (2002). The black belt memory jogger. Salem: Goal/QPC and Six Sigma Academy.
  5. Tannock, J. D. T., Balogun, O., & Hawisa, H. (2007). A variation management system supporting Six Sigma. Journal of Manufacturing Technology Management, 18 (5), 561 – 575.
  6. Haikonen, A., Savolainen, T., & Jarvinen, P. (2004). Exploring Six Sigma CI capability development: Preliminary case study findings on management role. Journal of Manufacturing Technology Management, 15 (4), 369 – 378.
  7. Motwani, J., Kumar, A., & Antony, J. (2004). A business process change framework for examining the implementation of Six Sigma: A case study of Dow Chemicals. The TQM Magazine, 16 (4), 273 – 283.
  8. Maleyeff, J., & Kaminsky, F. C. (2002). Six Sigma and introductory statistics education. Education + Training, 44 (2), 82 – 89.
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