©2004 prentice-hall s. thomas foster, jr

©2004 Prentice-Hall©2004 Prentice-Hall

S. Thomas Foster, Jr.S. Thomas Foster, Jr.Boise State UniversityBoise State University

PowerPointPowerPoint prepared byprepared byDave MageeDave Magee

University of KentuckyUniversity of KentuckyLexington Community CollegeLexington Community College

Chapter 14Chapter 14

Six-Sigma Management and Six-Sigma Management and ToolsTools

2Slide 14-2© 2004 Prentice-Hall© 2004 Prentice-HallManaging Quality: An Integrative Approach; 2nd EditionManaging Quality: An Integrative Approach; 2nd Edition

Chapter OverviewChapter OverviewSlide 1 of 2Slide 1 of 2

• What is Six Sigma?• Organizing Six Sigma• DMAIC Overview• Define Phase• Measure Phase• Analyze Phase• Improve Phase• Control Phase


Chapter OverviewChapter OverviewSlide 2 of 2Slide 2 of 2

• Taguchi Design of Experiments• Background of the Taguchi Method• The Taguchi Process• Design for Six Sigma• Lensing Six Sigma From A Contingency

Perspective


Differences of Six Sigma from Differences of Six Sigma from Traditional Continuous Traditional Continuous

ImprovementImprovement• Six Sigma represents a well thought out packaging

of quality tools and philosophies in an honest effort to provide rigor and repeatability to quality improvement efforts.

• Six Sigma is much more cost reduction-oriented than traditional continuous improvement.

• Six Sigma is organized around creating champions, black belts, green belts, and in some situations, yellow belts.


What Is Six Sigma? What Is Six Sigma? Slide 1 of 4Slide 1 of 4

• Sigma stands for the Greek symbol σ that designates a standard deviation in statistics.

• Six refers to the number of standard deviations from a mean specifications should be.

• Began at Motorola in 1982 as an effort to reduce costs and improve quality.

• It now involves planning, organization, training, human resources planning, and pay-for-knowledge. It requires both organizational and individual cooperation to achieve a goal.



Six-Sigma Variation Figure 14.4

3-sigmaproducing someproduct out ofspecification

6-sigmaproducing almostno product out of

specification

σσ σ σ



Sigma Levels and ppm Defects

Sigma Level

1

2

3

4

5

6

Long-Term ppm* Defects

691,462

308,538

66,807

6,210

233

3.4

*ppm = parts-per-million



Six Sigma EffectivenessOutside specialists

(Less than 1%)

Six Sigma(Less than 90%)

Basic Tools of Quality(90%)


Organizing Six SigmaOrganizing Six SigmaSlide 1 of 5Slide 1 of 5

• Cost of training can run $10,000 to $16,000 for a single black belt

• Expected returns from projects can run into the $100’s of thousands

• Key Players in Six Sigma Efforts– Champion

– Master black belt

– Black belt

– Green belt

– Yellow belt


Organizing Six Sigma Organizing Six Sigma Slide 2 of 5Slide 2 of 5

• Champion– Job is to work with black belts and potential black belts

to identify possible projects.

– Provides continuing support for the project and validates the results at the end of the project.

– Would probably be the CEO in smaller companies and a senior VP in larger companies.

• Master Black Belt– Experienced black belts who serve as mentors and

trainers for new black belts.

– Brings training in-house and can reduce costs.



ScarceResource

ScarceResource

Champion Decision Making Figure 14.3

VOBVOC VOE Financial

DataStrategicDirectionI D E A S

Blackbelt Projects

Champion



• Black Belt– Key to Six Sigma

– Specially trained individuals who are committed full-time to completing cost reduction projects.

– Training usually lasts about 4 months.

– Each project lasts from 2 months to a year depending on the project scope.

– Individuals usually spend about two years as a black belt and are then moved into management jobs.



• Green Belt– Trained in basic quality tools and work in teams to

improve quality.

– Assigned part-time to work on process and design improvement.

– In some cases, activities are the same as black belts.

– In other companies, green belts are involved in less critical projects.

• Yellow Belts– Some companies have employees who are familiarized

with improvement processes.


DMAIC OverviewDMAIC OverviewSlide 1 of 2Slide 1 of 2

• DMAIC Process– Very similar to the PDCA cycle.

• DMAIC Phases– Define

– Measure

– Analyze

– Improve

– Control


DMAIC OverviewDMAIC OverviewSlide 2 of 2Slide 2 of 2

Control ImproveAnalyze Measure Define

•Business Case•Project Desirability Matrix•Problem/Objective Statement•Primary/Secondary Metric•Change Management•VOC/QFD•SIPOC•Process Mapping

•Business Case•Project Desirability Matrix•Problem/Objective Statement•Primary/Secondary Metric•Change Management•VOC/QFD•SIPOC•Process Mapping

•XY Matrix•Process FMEA•Basic Statistics•Decision-Making•Non-Normal Data Graphical Analysis•Measurement System Analysis•Process Capability

•XY Matrix•Process FMEA•Basic Statistics•Decision-Making•Non-Normal Data Graphical Analysis•Measurement System Analysis•Process Capability

•Graphical Data Analysis•Multi-Vari Analysis•Inferential Statistics•Hypothesis Tests•Correlation •Regression •Process Modeling and Simulation

•Graphical Data Analysis•Multi-Vari Analysis•Inferential Statistics•Hypothesis Tests•Correlation •Regression •Process Modeling and Simulation

•Hypothesis Tests•Design of Experiments (DOE)•Advanced Regression•Process Modeling and Simulation•Pilot and Test

•Hypothesis Tests•Design of Experiments (DOE)•Advanced Regression•Process Modeling and Simulation•Pilot and Test

•Solution Selection•Solution Implementation•Control Plans•Control Charts•Hypothesis Tests•Process Capability Assessment•Best Practice Sharing/Translation

•Solution Selection•Solution Implementation•Control Plans•Control Charts•Hypothesis Tests•Process Capability Assessment•Best Practice Sharing/Translation

Overview of Six Sigma Process Figure 14.4


Define PhaseDefine PhaseSlide 1 of 7Slide 1 of 7

• Define Phase– Projects are identified and selected.

– Project selection is performed under the direction and with the participation of the champion

– Master black belts and black belts or green belts are also involved in selection.

• Phases of the Define Phase– Developing the business case.

– Project evaluation

– Pareto analysis

– Project definition



• Developing the Business Case includes:– Identifying a group of possible projects

– Writing the business case

– Stratifying the business case into problem statement and objective statement.



• The mnemonic device “RUMBA” is used to check the efficacy of a business case.– Realistic - Are the goals attainable, is the time line

feasible?

– Understandable - Do I understand the case?

– Measurable - Do we show the measures?

– Believable - That is a lot of money. Can it be done?

– Actionable - Can it be implemented?

• If the business case meets all of these requirements, it probably will be a good project.



• Project Evaluation– There are several methods for evaluating a project

including risk and return assessment.

• Risk and Return Assessment– Risk assessment evaluates a potential project across

several dimensions to establish an overall risk factor for the project which will be used to determine the attractiveness of the project.

– Project return assessment evaluates a potential project on 3 dimensions - growth, urgency, and impact.

– The risk and return scores are placed on a grid to determine the attractiveness of the potential project.



Project Risk and Return Figure 14.7

Stars

Low hangingfruit

?

Dogs

Risk Factor

Ret

urn

Fac

tor

00

10 20 30 40 50 60 70 80 90 100

10

20

30

40

50

60

70

80

90100



• Pareto Analysis– Part of the responsibility of the champion is to perform

a cost of poor quality (COPQ) analysis.

– This is based on the PAF categorization of costs discussed in Chapter 4.

– Performing a study of internal and external failure costs will help to determine where the most benefit can be found.

• Problem Definition– Project definition consists of a problem statement,

project goals/objectives, primary metrics, secondary metrics, and team member identification.



Problem Statement: In 2002, plant A lost $5.6 million on COPQ. Of this, almost $3.5 million occurred in operation 2. This has resulted in a loss of profitability for the firm.

Project Goals/Objective: Reduce COPQ for operation 2 by 30% by year-end.

Primary Metrics: - COPQ - Rework (% of sales)

- Scrap (% of sales)

Secondary Metrics: - Downtime for process- Plant sales- Labor productivity

Team Members: Pat ShannonPhillip FryLyman GallupJerry LaCava

Problem Statement: In 2002, plant A lost $5.6 million on COPQ. Of this, almost $3.5 million occurred in operation 2. This has resulted in a loss of profitability for the firm.

Project Goals/Objective: Reduce COPQ for operation 2 by 30% by year-end.

Primary Metrics: - COPQ - Rework (% of sales)

- Scrap (% of sales)

Secondary Metrics: - Downtime for process- Plant sales- Labor productivity

Team Members: Pat ShannonPhillip FryLyman GallupJerry LaCava

Problem Definition Figure 14.9


Measure PhaseMeasure PhaseSlide 1 of 4Slide 1 of 4

• Two Major Steps in the Measure Phase– Selecting process outcomes

– Verifying measurements

• Measure Phase Tools– Process Map

– XY Matrix

– FMEA

– Gage R&R

– Capability Assessment


Measure Phase Measure Phase Slide 2 of 4Slide 2 of 4

• Selecting Process Outcomes– To define process outcomes, you first need to

understand the process. This involves process mapping. A process map is a flowchart with responsibility. The goal with a process map is to identify non-value added activities.

– Two important measures that are monitored are defects per unit (DPU) and defects per million opportunities (DPMO).

– The XY matrix is used to identify inputs (X’s) and outputs (Y’s) from a project you have mapped and are desiring to pursue.



• Verifying Measurements

– It is necessary to use gauges, calipers and other tools when measuring critical characteristics of processes.

– Measurement system analysis (MSA) is used to determine if measurements are consistent.

– Product and process capability analysis is another approach for verifying measurements.

– Gage Repeatability and Reproducibility Analysis (Gage R&R) is the most commonly used MSA.



• Verifying Measurements (continued)– Reasons for problems in measurement

• The measurement gauges are faulty.

• Operators are using gauges improperly.

• Training in measurement procedures is lacking.

• The gauge is calibrated incorrectly.

– Statistical experiments using analysis of variance (ANOVA) are useful in performing Gage R&R.

– Two-way ANOVA is used to determine whether variation comes from the part being measured, differences in operator measurements, or from the measurement instrument.


Analyze PhaseAnalyze PhaseSlide 1 of 4Slide 1 of 4

• Analyze Phase– Involves gathering and analyzing data relative to a

particular Black belt project.

• Steps in the Analyze Phase– Define your performance objectives.

– Identify independent variables (X’s).

– Analyze sources of variability.


Analyze Phase Analyze Phase Slide 2 of 4Slide 2 of 4

• Defining Objectives– Attempting to determine what characteristics of the

process need to be changed to achieve improvement.

– Capability analysis is reviewed to determine where the processes are incapable and prioritized in order of importance.



• Identifying X’s– This involves identifying independent variables where

data will be gathered.

– These variables significantly contribute to process or product variation.

– Primary tools used in identifying X’s• Process maps

• XY matrices

• Brainstorming

• FMEA



• Analyzing Sources of Variation– The goal of this step is to use visual and statistical tools

to better understand the relationships between dependent and independent variables (X’s and Y’s) for use in future experimentation.

– Tools for Analyzing Sources of Variation• Histograms

• Box plots

• Scatter plots

• Regression analysis

• Hypothesis tests


Improve PhaseImprove Phase

• Improve Phase of the DMAIC Process – Involves off-line experimentation.

• Off-Line Experimentation– Involves studying the variables we have identified and

using analysis of variance to determine whether these independent variables significantly affect variation in our dependent variables.

– The Taguchi method is an important method for performing off-line experiments.


Control PhaseControl Phase

• Control Phase of the DMAIC Process – Involves managing the improved process using process

charts.

– Process charts were covered in Chapters 12 and 13


Taguchi Design of Experiments Taguchi Design of Experiments Slide 1 of 3Slide 1 of 3

• Taguchi Method– A standardized approach for determining the best

combination of inputs to produce a product or service.

– This is accomplished through design of experiments (DOE) for determining parameters.

– It provides a method for quantitatively identifying just the right ingredients that go together to make a high-quality product or service.



• Robust Design– The Taguchi concept of robust design states that

products and services should be designed so that they are inherently defect free and insensitive to random variation.

– Taguchi’s approach for creating robust design is through a three-step method consisting of concept design, parameter design, and tolerance design.

• Concept design– The process of examining competing technologies to

produce a product.

– Includes process technology and process design choices.



• Parameter design– The selection of control factors and the determination of

optimal levels for each of the factors.

– Control factors are those variables in a process that management can manipulate.

– Optimal levels are the targets or measurements for performance.

• Tolerance design– Deals with developing specification limits.

– Occurs after parameter design has been used to reduce variation and the resulting improvement has been insufficient.


Background of the Taguchi Background of the Taguchi MethodMethodSlide 1 of 6Slide 1 of 6

• History and Impact– The Taguchi method was first introduced by Dr.

Genichi Taguchi to AT&T Bell Laboratories in 1980.

– Thanks to its wide acceptance and utilization, the Taguchi method for improving quality is now commonly views as comparable in importance to statistical process control(SPC), the Deming approach, and the Japanese concept of total quality control.



• Taguchi Definition of Quality– In Taguchi terms, ideal quality refers to a reference

point or target value for determining the quality level of a product or service.

– Ideal quality is delivered if a product or tangible service performs its intended function throughout its projected life under reasonable operating conditions without harmful side effects.



• Quality Loss Function– If a measurement is taken of the critical product

characteristic and it is within the specification limits, the traditional conclusion was that it wasn’t a problem.

– However, if it is closer to being out of specification than to being at the target measurement, it might cause a problem. Taguchi calls this potential for problem a potential loss to society.

– Loss to society is the cost of a deviation from a target value.



Classical QC-Step Function

Scrap Cost

LSL USL

Target

A

Figure 14.16

Q(c)



• Quality Loss Function (continued)– To quantify loss to society, Taguchi used the concept of

a quadratic loss function.

– Any variation from the target of six (where T = 6) results in some loss to the company.

– The quality loss function focuses on the economic and societal penalties incurred as a result of purchasing a nonconforming product.

– Losses may include maintenance costs, failure costs, ill effects to the environment such as pollution, or excessive costs of operating the product.



Taguchi Quadratic Loss Function Figure 14.17


The Taguchi ProcessThe Taguchi ProcessSlide 1 of 6Slide 1 of 6

Taguchi Process Figure 14.18



• Step 1: Problem Identification– The production problem must be identified. The

problem may have to do with the product process or the service itself.

• Step 2: Brainstorming Session– To identify variables that have a critical affect on

service or product quality takes place.

– The critical variables identified in the brainstorming sessions are referred to by Taguchi as factors.

– These may be identified as either control factors (variables that are under the control of management) or noise factors (uncontrollable variation).



• Step 3: Experimental Design– Using the factors, factor levels, and objectives from the

brainstorming session, the experiment is designed.

– The Taguchi method uses off-line experimentation as a means of improving quality.

– This contrasts with traditional on-line (in process) quality measurement.



• Step 4: Experimentation– There are different Taguchi analysis approaches that

use quantitatively rigorous techniques such as analysis of variance (ANOVA), signal-to-noise ratios (S/N), and response charts. These approaches, although not always theoretically sound, are useful in engineering related projects involving engineered specifications, torques, and tolerances.



• Step 5: Analysis– Experimentation is used to identify the factors that

result in closest-to-target performance.

– If interactions between factors are evident, two alternatives are possible.

• Either ignore the interactions (there is inherent risk to this approach)

• Provided the cost is not prohibitive, run a full factorial experiment to detect interactions.

– The full factorial experiment tests all possible interactions among variables.



• Step 6: Confirming Experiment– Once the optimal levels for each of the factors have

been determined, a confirming experiment with factors set at the optimal levels should be conducted to validate the earlier results.

– If earlier results are not validated, the experiment may have somehow been significantly flawed.

– If results vary from those expected, interactions also may be present, and the experiment should, therefore, be repeated.


Design for Six Sigma Design for Six Sigma Slide 1 of 2Slide 1 of 2

• Design for Six Sigma (DFSS)– Used in designing new products and services with high

performance as measured by customer-based critical to quality metrics.

– Requires DMADV methodology instead of DMAIC.• Design

• Measure

• Analyze

• Design

• Verify

– DMADV pertains to developing new processes and products, whereas DMAIC pertains to improving existing processes and products.


Design for Six Sigma Design for Six Sigma Slide 2 of 2Slide 2 of 2

• Design for Six Sigma (DFSS)– IDOV is another method.

• Identify

• Design

• Optimize

• Verify

– IDOV is focused on final engineering design optimization.

– These methods are customer focused, encompassing the entire business-to-market process and pertain to both services and products.


Lensing Six Sigma from a Lensing Six Sigma from a Contingency Perspective Contingency Perspective

Slide 1 of 2Slide 1 of 2

• Six Sigma– Very popular approach for improving the robustness of

designs and processes.

– Very technical and requires special expertise.

– Can be useful for companies that need to improve their cost and efficiency through quality efforts.

• Requirements for Six Sigma Success– Culture

– Leadership

– Commitment

– Availability of data for projects


Lensing Six Sigma from a Lensing Six Sigma from a Contingency Perspective Contingency Perspective

Slide 2 of 2Slide 2 of 2

• Reasons for Six Sigma Failure– Lack of leadership by champions

– Misunderstood roles and responsibilities

– Lack of appropriate culture for improvement

– Resistance to change and the Six Sigma structure

– Faulty strategies for deployment

– Lack of data


SummarySummarySlide 1 of 2Slide 1 of 2

• What is Six Sigma?• Organizing Six Sigma• DMAIC Overview• Define Phase• Measure Phase• Analyze Phase• Improve Phase• Control Phase


SummarySummarySlide 2 of 2Slide 2 of 2

• Taguchi Design of Experiments• Background of the Taguchi Method• The Taguchi Process• Design for Six Sigma• Lensing Six Sigma From A Contingency

Perspective

©2004 prentice-hall s. thomas foster, jr

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