Lecture 11 six sigma management and tools
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Lecture 11 - Six-Sigma Management and Tools. 6 Σ Organization, DMAIC, Taguchi Method, Robust Design, Design of Experiments, Design for Six Sigma, Reasons for 6 Σ Failure. Topics. Six Sigma Evolution. Started as a simple quality metric at Motorola in 1986 ( Bill Smith )

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Lecture 11 - Six-Sigma Management and Tools

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Lecture 11 six sigma management and tools

Lecture 11 - Six-Sigma Management and Tools

6Σ Organization, DMAIC, Taguchi Method, Robust Design, Design of Experiments, Design for Six Sigma, Reasons for 6Σ Failure

SJSU Bus. 142 - David Bentley


Topics

Topics

SJSU Bus. 142 - David Bentley


Six sigma evolution

Six Sigma Evolution

  • Started as a simple quality metric at Motorola in 1986 (Bill Smith)

  • Concept 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

SJSU Bus. 142 - David Bentley


What is six sigma

What is Six-Sigma?

SJSU Bus. 142 - David Bentley


Percent not meeting specifications

Percent Not Meeting Specifications

  • +1Σ = 32%

  • +2Σ = 4.5%

  • +3Σ = 0.3%

  • +6Σ = 0.00034%

SJSU Bus. 142 - David Bentley


Six sigma levels

Six-Sigma Levels

SJSU Bus. 142 - David Bentley


Statistics dpu

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

SJSU Bus. 142 - David Bentley


Statistics dpmo defects per million opportunities

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

    or (3 lost bags × 1,000,000) ÷ (8,000 customers × 1.6 average bags)

    = 234.375

SJSU Bus. 142 - David Bentley


Statistics dpmo cont d

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)

SJSU Bus. 142 - David Bentley


Statistics off centering

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

SJSU Bus. 142 - David Bentley


Lecture 11 six sigma management and tools

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

SJSU Bus. 142 - David Bentley


K sigma quality levels

k-Sigma Quality Levels

  • Number of defects per million opportunities

    • For a specified off-centering and

    • a desired quality level

SJSU Bus. 142 - David Bentley


K sigma quality levels source evans lindsay the management and control of quality southwestern 2005

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

SJSU Bus. 142 - David Bentley


Six sigma and other techniques

Six Sigma and Other Techniques

SJSU Bus. 142 - David Bentley


Organizing six sigma

Organizing Six Sigma

SJSU Bus. 142 - David Bentley


Key players

Key Players

SJSU Bus. 142 - David Bentley


Distribution of six sigma trained employees

Distribution of Six Sigma Trained Employees

SJSU Bus. 142 - David Bentley


Six sigma tools

Six Sigma Tools

DMAIC, Taguchi Method, Design for Six Sigma

SJSU Bus. 142 - David Bentley


Dmaic

DMAIC

SJSU Bus. 142 - David Bentley


Dmaic dmaic overview

DMAICDMAIC Overview

SJSU Bus. 142 - David Bentley


D maic define 1

DMAICDefine – (1)

SJSU Bus. 142 - David Bentley


D maic define 2

DMAICDefine – (2)

SJSU Bus. 142 - David Bentley


D maic define 3

DMAICDefine – (3)

SJSU Bus. 142 - David Bentley


D m aic measure 1

DMAICMeasure – (1)

SJSU Bus. 142 - David Bentley


D m aic measure 2

DMAICMeasure – (2)

SJSU Bus. 142 - David Bentley


D m aic measure 3

DMAICMeasure – (3)

SJSU Bus. 142 - David Bentley


D m aic measure 4

DMAICMeasure – (4)

SJSU Bus. 142 - David Bentley


D m aic repeatability reproducibility

DMAICRepeatability & Reproducibility

SJSU Bus. 142 - David Bentley


Measurement system d m aic evaluation

Measurement System DMAIC Evaluation

  • Variation can be due to:

    • Process variation

    • Measurement system error

      • Random

      • Systematic (bias)

    • A combination of the two

SJSU Bus. 142 - David Bentley


D m aic metrology 1

DMAICMetrology - 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

SJSU Bus. 142 - David Bentley


D m aic metrology 2

DMAICMetrology - 2

  • Repeatability

    • Instrument variation

    • Variation in measurements using same instrument and same individual

  • Reproducibility

    • Operator variation

    • Variation in measurements using sameinstrument and different individual

SJSU Bus. 142 - David Bentley


D m aic r r studies

DMAICR&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

SJSU Bus. 142 - David Bentley


D m aic r r spreadsheet template

DMAICR&R Spreadsheet Template

SJSU Bus. 142 - David Bentley


D m aic r r evaluation

DMAICR&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

SJSU Bus. 142 - David Bentley


D m aic calibration

DMAICCalibration

  • Compare 2 instruments or systems

    • 1 with known relationship to national standards

    • 1 with unknown relationship to national standards

SJSU Bus. 142 - David Bentley


Dm a ic analyze 1

DMAICAnalyze – (1)

SJSU Bus. 142 - David Bentley


Dm a ic analyze 2

DMAICAnalyze – (2)

SJSU Bus. 142 - David Bentley


Dm a ic analyze 3

DMAICAnalyze–(3)

SJSU Bus. 142 - David Bentley


Dm a ic analyze 4

DMAICAnalyze–(4)

SJSU Bus. 142 - David Bentley


Dma i c improve

DMAICImprove

SJSU Bus. 142 - David Bentley


Dmai c control phase

DMAICControl Phase

SJSU Bus. 142 - David Bentley


The taguchi method

The Taguchi Method

SJSU Bus. 142 - David Bentley


The taguchi method provides

The Taguchi Method provides:

SJSU Bus. 142 - David Bentley


Design of experiments doe

Design of Experiments (DOE)

SJSU Bus. 142 - David Bentley


The taguchi process

The Taguchi Process

SJSU Bus. 142 - David Bentley


Taguchi quality loss function

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

SJSU Bus. 142 - David Bentley


Design for six sigma

Design for Six Sigma

DFSS

SJSU Bus. 142 - David Bentley


Design for six sigma dfss

Design for Six-Sigma (DFSS)

SJSU Bus. 142 - David Bentley


Dmadv

DMADV

SJSU Bus. 142 - David Bentley


Lecture 11 six sigma management and tools

IDOV

SJSU Bus. 142 - David Bentley


Reasons for six sigma failure

Reasons for Six Sigma Failure

SJSU Bus. 142 - David Bentley


Reasons for six sigma failure 1

Reasons for Six-Sigma Failure - (1)

SJSU Bus. 142 - David Bentley


Reasons for six sigma failure 2

Reasons for Six-Sigma Failure - (2)

SJSU Bus. 142 - David Bentley


Summary

Summary

SJSU Bus. 142 - David Bentley