Rev. 04/03/09 SJSU Bus. 142 - David Bentley

Rev. 04/03/09 SJSU Bus. 142 - David Bentley 1

Week 11 - Six-Sigma Management and Tools

6Σ Organization, DMAIC, Taguchi Method, Robust

Design, Design of Experiments, Design for Six

Sigma, Reasons for 6Σ Failure

11/13/07 SJSU Bus. 142 - David Bentley 2

Topics

What is Six-Sigma? Organizing Six-Sigma DMAIC overview DMAIC phases The Taguchi method Design for Six-Sigma Using Six-Sigma from a contingency perspective


Six Sigma Evolution Started as a simple quality metric at

Motorola in 1986 (Bill Smith) Migrated to Allied Signal

(acquired Honeywell and took its name) Picked up by General Electric

Commitment by CEO Jack Welch in 1995 Grown to be an integrated strategy for

attaining extremely high levels of quality


What is Six-Sigma?

Sigma () is a Greek letter used to designate a standard deviation (SD)

in statistics Six refers to the number of SD’s

from the specialized limit to the mean. Six sigma is a fairly recent umbrella

approach to achieve quality


Percent Not Meeting Specifications

+1Σ = 32% +2Σ = 4.5% +3Σ = 0.3% +6Σ = 0.00034%


Six-Sigma Levels

Sigma Level Long-term ppm*

defects

1 691,462

2 308,538

3 66,807

4 6,210

5 233

6 3.4


Statistics - DPU

Defect Six Sigma: “any mistake or error passed on

to the customer” ??? General view: any variation from

specifications DPU (defects per unit)

Number of defects per unit of work Ex: 3 lost bags ÷ 8,000 customers = .000375


Statistics – dpmo (defects per million opportunities)

Process may have more than one opportunity for error (e.g., airline baggage)

dpmo = (DPU × 1,000,000) ÷ opportunities for error Ex: (3 lost bags × 1,000,000) ÷ (8,000

customers × 1.6 average bags)= 234.375

or (.000375)(1,000,000) ÷ 1.6 = 234.375


Statistics – dpmo (cont’d)

May extend the concept to include higher level processes E.g., may consider all opportunities for

errors for a flight (from ticketing to baggage claim)


Statistics - Off-Centering Represents a shift in the process mean Impossible to always keep the process

mean the same (this WOULD be perfection)

Does NOT represent a change in specifications

Control of shift within ± 1.5 σ of the target mean keeps defects to a maximum of 3.4 per million


Statistics - Off-Centering (cont’d)Source: Evans & Lindsay, The Management and Control of Quality, Southwestern, 2005


k-Sigma Quality Levels

Number of defects per million opportunities For a specified off-centering and a desired quality level


k-Sigma Quality Levels Source: Evans & Lindsay, The Management and Control of Quality, Southwestern, 2005


Six Sigma and Other Techniques

Six-Sigma is … designed to handle the most difficult quality problems.

% Quality Problems

Techniques

90% Basic tools of Quality

< 10% Six-Sigma

< 1% Outside specialists


Organizing Six Sigma


Key Players Champion. Work with black belts to identify possible projects Master Black Belts. Work with and train new black belts Black Belts. Committed full time to completing cost-reduction projects Green Belts. Trained in basic quality tools


Distribution of Six Sigma Trained Employees

In a company with 100 employees there might be: One black belt Sixty green belts Some companies have yellow belts, employees familiar with improvement processes


Six Sigma Tools

DMAIC, Taguchi Method, Design for Six Sigma


DMAIC


DMAIC

DMAIC Overview

Stands for the six phases: Define Measure Analyze Improve Control


DMAIC

Define – (1)

Four Sub-Phases:1. Develop the business case2. Project evaluation3. Pareto analysis4. Project definition


DMAIC

Define – (2)

Developing the Business Case:1. Identify a group of possible projects2. Writing the business case3. Stratifying the business case into

problem statement and objective statement


DMAIC

Define – (3)

RUMBA is a device used to check the efficacy of the business case

1. Realistic2. Understandable3. Measurable4. Believable5. Actionable


DMAIC Measure – (1)

Two major steps: 1. Selecting process outcomes2. Verifying measurements



Selecting process outcomes (step 1)

Tools Used: Process map (flowchart) XY matrix (like QFD) FMEA (Failure Modes and Effects

Analysis) (aka DFMEA) Gauge R&R (Repeatability and

Reproducibility) Capability Assessment (cp or cpk)



Verifying measurements (step 2) Tools Used:

Gauges, calipers and other tools. Management System Analysis (MSA) is

used to determine if measurements are consistent



Gauge R&R Most commonly used MSA Determine the accuracy and

precision of your measurements


DMAIC Repeatability & Reproducibility


Measurement System DMAIC Evaluation

Variation can be due to: Process variation Measurement system error

Random Systematic (bias)

A combination of the two


DMAIC Metrology - 1

Definition: The Science of Measurement

Accuracy How close an observation is to a

standard Precision

How close random individual measurements are to each other


DMAIC Metrology - 2

Repeatability Instrument variation Variation in measurements using same

instrument and same individual Reproducibility

Operator variation Variation in measurements using same

instrument and different individual


DMAIC R&R Studies

Select m operators and n parts Calibrate the measuring instrument Randomly measure each part by each

operator for r trials Compute key statistics to quantify

repeatability and reproducibility


DMAIC R&R Spreadsheet Template


DMAIC R&R Evaluation

Repeatability and/or reproducibility error as a percent of the tolerance Acceptable: < 10% Unacceptable: > 30% Questionable: 10-30%

Decision based on criticality of the quality characteristic being measured and cost factors


DMAIC Calibration

Compare 2 instruments or systems 1 with known relationship to national

standards 1 with unknown relationship to national

standards


DMAIC

Analyze – (1)

Three major steps: 1. Define your performance objectives

(X’s)2. Identify independent variables3. Analyze sources of variability


DMAIC

Analyze – (2)

Define your performance objectives (X’s) (step 1)


DMAIC

Analyze – (3)

Identify the independent variables where data will be gathered (step 2) Process maps (flowcharts), XY matrices,

brainstorming, and FMEA’s are the tools used


DMAIC

Analyze – (4)

Analyze sources of variability (step 3) Use visual and statistical tools to better

understand the relationships between dependent and independent variables


DMAIC

Improve

Off-line experimentation

Analysis of variance (ANOVA) Determines whether independent

variable affect variation in dependent variables

Taguchi method or approach


DMAIC

Control Phase

Manage the improved processes using control charts… covered in:

Variables Attributes


The Taguchi Method


The Taguchi Method provides:

1. A basis for determining the functional relationship between controllable factors

2. A method for adjusting a mean of a process by optimizing controllable variables.

3. A procedure for examining the relationship between random noise … and product or service variability


Design of Experiments (DOE)

Robust design – designed so that products are inherently defect free

Concept Design – considers process design and technology choices

Parameter Design – selection of control factors and optimal levels

Tolerance Design – specification limits


The Taguchi Process

1. Problem identification2. Brainstorming session3. Experimental design4. Experimentation5. Analysis6. Confirming experiment


Taguchi Quality Loss Function

Traditional view: anything within specification limits is OK, with no loss

Taguchi Any variation from the target mean

represents a potential loss The greater the distance from the target

mean the greater the potential loss


Design for Six Sigma

DFSS


Design for Six-Sigma (DFSS)

Used in designing new products with high performance, instead of DMAIC1. DMADV (see next slide)2. IDOV (see 2 slides ahead)

Focuses on final engineering design optimization

Relates to new processes and products


DMADV

1. Design2. Measure3. Analyze4. Design5. Verify


IDOV

1. Identify2. Design3. Optimize4. Verify


Reasons for Six Sigma Failure


Reasons for Six-Sigma Failure - (1)

1. Lack of leadership by champions2. Misunderstood roles and

responsibility3. Lack of appropriate culture for

improvement


Reasons for Six-Sigma Failure - (2)

4. Resistance to change and the Six-Sigma structure

5. Faulty strategies for deployment6. Lack of data


Summary

The process for Six-Sigma is define, measure, analyze, improve and control

Keys to Six-Sigma success are skilled management, leadership and long-term commitment

Rev. 04/03/09 SJSU Bus. 142 - David Bentley

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