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A BRIEF INTRODUCTION TO SIX SIGMA Dr. Ömer Yağız Department of Business Administration METU.

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Presentation on theme: "A BRIEF INTRODUCTION TO SIX SIGMA Dr. Ömer Yağız Department of Business Administration METU."— Presentation transcript:

1 A BRIEF INTRODUCTION TO SIX SIGMA Dr. Ömer Yağız Department of Business Administration METU

2 2 What is six-sigma?  Six-sigma is a is a comprehensive and flexible system for achieving, sustaining, and maximizing business success by minimizing defects and variability in processes.  It relies heavily on the principles and tools of TQM.  It is driven by a close understanding of customer needs; the disciplined use of facts, data, and statistical analysis; and diligent attention to managing, improving, and reinventing business processes.

3 What is six-sigma?  Another definition from Six Sigma is a rigorous and disciplined methodology that uses data and statistical analysis to measure and improve a company's operational performance by identifying and eliminating "defects" in manufacturing and service-related processes. 3

4 What is six-sigma?  GE and many other successful practitioners of six-sigma, view it as a strategy  focusing on what the customer wants, internal or external  aiming at total customer satisfaction  achieve better business results as measured by market share, revenue and profits 4

5 What is six-sigma? a discipline  it has a formal sequence of steps, called the Six-sigma Improvement Model, to accomplish desired improvements in process performance  the goal is to simplify processes in order to make them more efficient and effective a set of tools  makes use of many powerful tools, some of them statistical in nature, in order to monitor, analyze, correct and/or redesign operations and processes used in all areas of an organization 5

6 Origins of Six-sigma  Motorola credited with developing six-sigma in 1987 to improve its manufacturing capability in a world marketplace that was becoming increasingly competitive set a “stretch goal in 1987 to  “Improve product and services quality ten times by 1989, and at least one hundred fold by 1991. Achieve six sigma capability by 1992. 6

7 Origins of Six-sigma At Motorola, six sigma became part of the common language of all employees. To them it meant “near perfection”, even if some did not understand the statistical details. Six Sigma helped Motorola realize powerful bottom-line results in their organization - in fact, they documented more than $16 Billion in savings as a result of Six Sigma efforts. 7

8 Origins of Six-sigma  Other early adopters of Six Sigma who achieved well-publicized success include Honeywell (previously known as AlliedSignal) and General Electric, where the method was introduced by Jack Welch. By the late 1990s, about two- thirds of the Fortune 500 organizations had begun Six Sigma initiatives with the aim of reducing costs and improving quality. Honeywell AlliedSignalGeneral ElectricJack WelchFortune 500 8

9 Statistical meaning of Six-sigma  Every instance of a product coming off a production line is in some way different from every other instance. The thickness or length of a part is never exactly the same  The amount of time it takes to perform a certain transaction varies from instance to instance  In other words, variation is a fact of life in manufacturing and services 9

10 Statistical meaning of Six-sigma Process variability

11 Process Capability Süreç (proses) yeterlilik  Process capability is the ability of the process to meet the design specifications for a service or product.  Nominal value is a target for design specifications.  Tolerance is an allowance above or below the nominal value. 11

12 Process Capability 12 202530 Minutes Upperspecification LowerspecificationNominalvalue Process is capable Process distribution

13 Process Capability 13 Process is not capable 202530 Minutes Upperspecification LowerspecificationNominalvalue Process distribution

14 Calculating population standard deviation from a single large sample 14

15 Standard deviation of a group of data 15 where = arithmetic mean of data i = 1, 2, …, n n = total number of observations

16 Process Capability 16 Process Capability = 6σ

17 Relationship of Proc. Cap. to specification limits Three cases (situations): 1.6σ < USL – LSL 2.6σ = USL – LSL 3.6σ > USL – LSL 17

18 Relationship of Proc. Cap. to specification limits Process Capability and the specification limits (i.e., tolerances) are combined to form a Capability Index: 18 Case 3 Case 2 Case 1

19 Capability Index C p  The capability index measures whether the process or machine can produce pieces which conform to the specifications.  The larger the index, the more likely the process will generate conforming parts or pieces provided that the process is centered at the nominal or target value. (C P >= 1.33)  CAUTION : The capability index does not indicate process performance in terms of the nominal or target value. 19

20 20 Nominal = 7 USL = 9 LSL = 5 Suppose Although C p > 1.33, the process is not capable. Why not ? An Illustration of Process Capability Index:

21 A better measure of process capability (C pk ) 21 This measure takes into account the centering of the process. We first obtain two one-sided indexes, then select the minimum of the two.

22 C pk Illustration 22  Nominal = 7 USL = 9 LSL = 5 The process is capable.

23 C pk Illustration 23

24 C pk Illustration 24 The process is barely capable. If

25 C pk Illustration 25 The process is barely capable.

26 Process variation and its effect on process defects per million opportunities (DPMO) 26 USL LSL Process variation 3 sigma process variation = 66800 defects per million opportunities 4 sigma process variation = 6200 defects per million opportunities 5 sigma process variation = 230 defects per million opportunities 6 sigma process variation = 3.4 defects per million opportunities USL LSL USL LSL USL LSL

27 Case of process shift in the long run 27 With the process centered exactly in the middle (nominal dimension), only 2 defectives out of one billion are expected. If the process mean shifts ± 1.5 sigma, the expected number of defectives will be 3.4 per million. What is the key to achieving six-sigma capability?

28 Defects per million occurrences DPMO Sigma quality levels (defects per million) 28 SigmasDPMO 2308,538 366,803 46,200 5233 63.4

29 Now what?  What all this explanation boils down to is this: The objective of Six Sigma improvement efforts is to reduce process output variation so that on a long term basis, which is the customer's aggregate experience with our process over time, this will result in no more than 3.4 Defects Per Million Opportunities – DPMO. therefore make sure that you have a capable process, i.e. keep 6σ < USL – LSL with proper centering, and reduce process variation as much as you can so that you achieve a DPMO of 3.4 defects. (In reality, this is not achieved easily; but this should be the ultimate goal of your improvement efforts) 29

30 What does six-sigma do?  Six Sigma focuses on improving quality by helping organizations produce products and services better, faster and cheaper.  In more traditional terms, Six Sigma focuses on defect prevention, cycle time reduction, and cost savings. Unlike cost- cutting programs that reduce value and quality, Six Sigma identifies and eliminates costs that provide no value to customers; in other words, waste costs. 30

31 What does six-sigma do?  The “Six Sigma” quality philosophy incorporates many of the traditional quality philosophies and approaches established by Shewhart, Deming, Juran, Taguchi, and Ishikawa, by developing an organized framework for continuous improvement. 31

32 Six-sigma infrastructure  A very powerful feature of Six Sigma is the creation of an infrastructure to assure that performance improvement activities have the necessary resources. Six Sigma makes improvement and change the full time job of a small but critical percentage of the organization’s personnel. 32

33 Six-sigma infrastructure These full time change agents who act as the catalysts that institutionalize change are classified as follow:  Champions and Sponsors: Six Sigma champions are high-level individuals who understand Six Sigma and are committed to its success. They are usually a member of senior management who are charged with leading and energizing the Six Sigma effort and most often theirs is a full-time position, such as an Executive Vice-President. They are also often charged with identifying projects, prioritizing those projects in relation to the organization’s strategy, and assigning projects to Black Belts and/or Green Belts. Sponsors are owners of processes and systems, who help initiate and coordinate Six Sigma improvement activities in their areas of responsibility. 33

34 Six-sigma infrastructure  Master Black Belts: Master Black Belts are the senior technical advisors for a Six Sigma effort, providing technical leadership for the Six Sigma program. Thus, they must know everything the Black Belts know, as well as understand the theory on which the statistical methods are based. Master Black Belts must be able to assist Black Belts in applying the methods correctly in unusual situations. 34

35 Six-sigma infrastructure  Black Belts: The front line leaders of Six Sigma are called black belts. These individuals are full-time project leaders with the primary responsibility of providing technical expertise and leadership for process improvement projects. Since they are dedicated to the implementation, it becomes cost effective to invest additional resources in developing the Black Belts’ ability to apply a broad range of process improvement tools and techniques 35

36 Six-sigma infrastructure  Green Belts: are Six Sigma project leaders capable of forming and facilitating Six Sigma teams and managing Six Sigma projects from concept to completion. They receive a wide range of training that covers project management, quality management tools, quality control tools, problem solving, and descriptive data analysis. It is generally a part-time commitment and suitable for middle managers, engineers and supervisors. 36

37 Six-sigma infrastructure  The good thing about the belt system is that  everyone in the organization is speaking the same language.  Another important impact of such company- wide training is that it fosters a culture whereby the ownership of quality is viewed as the responsibility of the entire organization and not just of the quality department. 37

38 Six Sigma Improvement Model  known as DMAIC model Define, Measure, Analyze, Improve and Control  highly disciplined and structured problem-solving and improvement methodology  has five steps for improving processes and solving problems both in goods production and services Let us take look at DMAIC in more detail….. 38

39 DMAIC Improvement Model  Define Define the goals of the improvement activity. At the top level the goals will be the strategic objectives of the organization, such as a higher ROI or market share. at the operations level, a goal might be to increase the throughput of a production or service department. at the project level goals might be to reduce the defect/error level and increase throughput. 39

40 DMAIC Improvement Model  Measure Measure the existing system. establish valid and reliable metrics to help monitor progress towards the goal(s) defined at the previous step. begin by determining the current baseline. Use exploratory and descriptive data analysis to help you understand the data. 40

41 DMAIC Improvement Model  Analyze Analyze the system to identify ways to eliminate the gap between the current performance of the system or process and the desired goal. apply statistical and other tools provided by TQM to guide the analysis. identify several possible causes of variation or defects that are affecting the outputs of the process. 41

42 DMAIC Improvement Model  Analyze cont’d one of the most frequently used tools in the Analyze step is the cause and effect diagram. Root cause is the number one team deliverable coming out of the Analyze step. 42

43 DMAIC Improvement Model  Improve Improve the process or system. modify or redesign the process or system be creative in finding new ways to do things better, cheaper, or faster. use project management and other planning and management tools to implement the new approach. use statistical methods to validate the improvement. improvements should be selected based on probability of success, time to execute, impact on resources, and cost 43

44 DMAIC Improvement Model  Control teams may develop poka-yokes or mistake proof devices to help control a process. The ultimate goal for this step is to reduce variation by controlling the inputs and monitoring the outputs. institutionalize the improved system by modifying compensation and incentive systems, policies, procedures, budgets, operating instructions and other management systems. 44

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