Basics of Six Sigma

Six Sigma Concepts

In Six Sigma terminology, a defect, or nonconformance is any mistake or error that is passed on to the customer. A unit of work is the output of a process or an individual process step. A measure of output quality is defects per unit (DPU).

Defects per unit = Number of defects discovered/Number of units produced

The Six Sigma concept redefines quality performance as defects per million opportunities (dpmo):

Dpmo = DPU x 1,000,000/ opportunities for error

For example, suppose an airline wishes to measure the effectiveness of its baggage handling system. A DPU measure might be lost bags per customer. However customers may have different numbers of bags; thus the number of opportunities for error is the average number of bags per customer. If the average number of bags per customer is 1.6 and the airline recorded 3 lost bags for 8000 passengers in one month then

Dpmo = (3/ (8000 x1.6)) x 1,000,000 = 234.375

Six Sigma represents a quality level of at most 3.4 defects per million opportunities. A k sigma quality level satisfies the equation:

K x process standard deviation = tolerance / 2

The sigma level can easily be calculated on an Excel spreadsheet using the formula

=NORMSINV (1- Number of defects/Number of opportunities) + SHIFT

=NORMSINV (1-dpmo/1000000) +SHIFT

SHIFT refers to the off centering as used in table 10.1. Using the airline example we discussed, if we had 3 lost bag for 8000(1.6) =12800 opportunities; we would find =NORMSINV (1-3/12800) + 1.5 = 4.99828 or about 5-sigma level.

The quality level of 3.4 defects per million can be achieved in several ways, for instance;

·         With 0.5 –sigma off-centering and 5-sigma quality

·         With 1.0-sigma off centering and 5.5-sigma quality

·         With 1.5-sigma off-centering and 6-sigma quality

Table 10.1 Number of defectives (Parts per million) for specified Off-Centering of the Process and Quality levels.

 Quality Level Off-centering 3-sigma 3.5-sigma 4-sigma 4.5-sigma 5-sigma 5.5-sigma 6-sigma 0 2700 465 63 6.8 0.57 0.034 0.002 0.25-sigma 3577 666 99 12.8 1.02 0.1056 0.0063 0.5-Sigma 6400 1382 236 32 3.4 0.71 0.019 0.75-sigma 12288 3011 665 88.5 11 1.02 0.1 1-sigma 22832 6433 1350 233 32 3.4 0.39 1.25-sigma 40111 12201 3000 577 88.5 10.7 1 1.5-sigma 66803 22800 6200 1350 233 32 3.4 1.75-sigma 105601 40100 12200 3000 577 88.4 11 2-sigma 158700 66800 22800 6200 1300 233 32

Although originally developed for manufacturing in the context of tolerance-based specifications, the Six Sigma concept has been operationalized to any process and has come to signify a generic quality level of at most 3.4 defects per million opportunities.

Project selection for Six Sigma

A useful way of classifying quality and performance-related problems that can help identify Six Sigma projects is by problem type.

1.       Conformance problems are defined by unsatisfactory performance by a well specified system. Users are not happy with system outputs, such as quality or customer service levels. The system has worked before, but for some reason it is not performing acceptably. The causes of deviations must be identified, and the system restored to its intended mode of functioning.

2.       Unstructured performance problems result from unsatisfactory performance by a poorly specified system. The task is nonstandardized and not fully specified by procedures and requirements. Unstructured problems require more creative approaches to solving them.

3.       Efficiency problems result from unsatisfactory performance from the stand point of stakeholders other than customers. Typical examples are cost and productivity issue. Even though the quality of the outputs may be acceptable, the system’s performance does not achieve internal organizational goals. Identification of solutions often involves streamlining processes.

4.       Product design problems involve designing new products that better satisfy user needs – the expectations of customers that matter most to them. In Six Sigma those vital characteristics are called “critical to quality” (CTQ) issues.

5.       Process design problems involve designing new processes or substantially revising existing processes. The challenge here is determining process requirements, generating new process alternatives, and linking these processes to customer needs. Benchmarking and re-engineering are useful tools for process design.

In the words of Russell Ackoff, managers must learn “mess management”, he defines mess as a “system of external conditions that produces dissatisfaction.” Lynch and colleagues point out two ways to generate projects: top-down and bottom-up. Top-down projects generally are tied to business strategy and are aligned with the customer needs. Their major weakness is that they are often too broad in scope to be completed in a timely manner. In a bottom-up approach, Black Belts (or MBBs) choose the projects that are well-suited to the capabilities of teams. However, a major drawback of this approach is that the project may not be tied closely to strategic concerns of top management, thus receiving little support and low recognition from the top.

Factors that should be considered when selecting Six Sigma projects include the following:

1.       Financial return, as measured by cost associated with quality and process performance, and impacts on revenues and market share.

2.       Impacts on customers and organizational effectiveness

3.       Probability of success

4.       Impact on employees

5.       Fit to strategy and competitive advantage

Six Sigma problem solving

Problem solving is the activity associated with changing the state of what is actually happening to what should be happening. Juran defined breakthrough as the accomplishment of any improvement that takes an organization to unprecedented levels of performance. Breakthrough attacks chronic losses or, in Deming’s terminology, common causes of variation.

Successful quality and business performance improvement depends on the ability to identify and solve problems; this ability is fundamental to the Six Sigma philosophy. Many non-quantitatively inclined managers (which may include 75 or 80 percent of the population) have difficulty in grasping the concept of systematic fact based, often statistical, problem-solving approach. Yet, using such an approach is vital to effectively identifying the sources of problems, understanding their causes, and developing improvement solutions.

“Speaking the same language” builds confidence and assures that solutions are developed objectively, rather than by intuition. A structured problem-solving process provides all employees with a common language and a set of tools to communicate with each other, particularly as members of cross-functional teams.

Deming, Juran and Crosby proposed specific methodologies for improvement, which have following common points:

1.       Redefining and analyzing the problem: Collect and organize information, analyze the data and underlying assumptions, and reexamine the problem for new perspectives, with the goal of achieving a workable problem definition.

2.       Generating ideas: “Brainstorm” to develop potential solutions.

3.       Evaluating and selecting ideas: Determine whether the ideas have merit and will achieve the problem solver’s goal.

4.       Implementing ideas: Sell the solution and gain acceptance by those who must use them.

These themes are reflected in the principal problem solving methodology sued by Six Sigma – DMAIC – define, measure, analyze, improve, control – which we will discuss next.

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