6sigma Design

8/8/2019 6sigma Design

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66--sigma &sigma &

Mech. DesignMech. Design

IIntroduction tontroduction to

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1. What is 6-sigma?

2. How to produce good products?3. 6-sigma process

4. Problem solving techniques5. Software tools and demo

6. Quality policy


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Whats wrong in this process?

Understand your CTQs

to your customers

Whats missing betweeneach steps?

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GoodProduct

Marketing

Shipping

Regulation

Design

Manufacturing

Sourcing

Service

Finance

Survey

Requirement

Strategy

Capability study

MP

QCP

Equip. V&V

Production plan

PA training

HAST

HALT

DFR

DFMDFSS

FMEA

Proto test

Risk Assm

Design Spec

ICV review

Resource

P&E review

Cost Analysis

ICV Reduction

Parts CostSupplier capability

Supplier quality

Customer SatisfactionWarranty

Serviceability

Training

IB

FRU

How to produce good products

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NPI - New Product Introduction

CDRS - Critical to Design Requirement and SpecificationCTQ - Critical to Quality CV - Change Validation

DHF - Design history Files DHR - Device history record

DFM - Design for Manufacturing DFR - Design for Reliability

FMEA - Failure Mode Effect Analysis FRU - Field Replaceable UnitHALT Highly Accelerated Life Test HASS - Highly Accelerated Stress Screening

HAST - Highly Accelerated Stress Test

HLB - High Level Buy ICV - Internal Cost Value

IB - Install Base OMS - Operation Manual and Spec.

PA - Production Associate P&E - Production and Equipment

QFD - Quality Flow Down QFU - Quality Flow Up

QFD Quality Function Deployment

ZST - Z short term (6-sigma term) ZLT - Z long term (6-sigma)

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Y = f(X)

Xs Y

How to increase the yield?

LSL USL

LSL USL

Transfer Function

(Process)

6

0- = 50% 1- = 15.87% 2- = 2.28% 3- = 0.13%


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How Six Sigma Fits Into Our Process

Opp

ortunity

Identification

Ma

rket

Ana

lysis

Com

petitive

An

alysis

Bus

iness

Ana

lysis

Opp

ortunity

Selection

Requirement

An

alysis

Co

ncept

D

esign

Detailed

De

sign

Integ

ration&

Test

Pro

totypes

Performance

Eva

luation

Pilot

Production

Full

Production

Customer

U

sage

MK M0 M3M1 M2 M4

D

M

A

D

V

Design for Six Sigma(Innovation)

D

I

D

O

V

Design for Six Sigma(Product & Process)

D

M

A

I

C

Six Sigma Methodology

DFSS-i DFSS-p

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SSM


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N/A

Business Case/Goal Statement

Define Project Scope

Integration with MGPP

Definition of Team

Develop Project Plan

Define CAP Plan

Estimate of benefits

Phase updated & approved

Used

ID CUSTOMER NEEDS

Measure

DEVELOP/EVALUATE HIGH-LEVEL DESIGN

Analyze

DETAILED DESIGN

Design

STATISTICAL CONTROL

Verify

PROGRAM DESCRIPTION

Define

N/A

Pilots complete/verified

Commercialization Plan

Implement CAP Plan

Control Plan in Place

Scorecards complete/approve


Used

N/A

Select High-Level Design

Product functions defined

Develop Transfer Functions

Design Models/Simulations

Determine Quality Gaps

Preliminary FMEA Complete

Scorecard Updates


Used

N/A

Us

ed

Flowdown/up CTQs

Determine and Measure CTPs

Predict/Improve Capability

Error Proofing applied to FMEA

Customer Feedback on Design

Prototype/Pilot Verified

Control Plan Developed

Scorecard UpdatesPhase updated & approved

N/A

Customer Identified/Prioritized

Customer Needs Prioritized

Determine/Prioritize CTQs

CTQ Measurements Determined

Measurement Sys Capability

Architectural models/simulations

First Pass Scorecards


Used

*Items in BOLD are required or strongly recommended for that phase

Phase Requirements*

Project Title: ProjectProjectNo.:

Date Approved_________ Date Approved_________ Date Approved_________ Date Approved_________ Date Approved_________

DFSS-i

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DFSSp/SSM

Phase Requirements*

Project Title: ProjectProjectNo.:

9

Solution in place

Z, COQ, PPM improvements

Documentation in place

Financials approved

Before and after distributions

Retolerance process

Used

Controls in place for Xs

Identify vital few Xs

Identify financial benefits

Plan confirmation run /

sample size

Identify EHS implications

Used PRACTICAL PROBLEM

Identify

STATISTICAL PROBLEM

Design

STATISTICAL SOLUTION

Optimize

STATISTICAL CONTROL

Verify

PRACTICAL PROBLEM

Define

N/A

Problem define with goalCustomers identified

Functional breakdown

Benefits determined

Project Funnel

Used

N/A

Solution in place

Confirmation run completeZ, COQ, PPM improvements

Documentation in place

Financial approved

Before and after distributions

Re-tolerance process

Used

N/A

Design concept selected

Exhaustive list of poss. XsPotential vital few Xs

Predict process capability Y

Anova/percent contribution

Advanced DoE optimization

employed

Used

N/A

Used

Optimized Xs

Design error proofingIdentify financial benefits

Identify gaps between

predicted and desired CTQs

Identify interactions/leverage

Improve solution developed

N/A

Customers needs identified

Prioritized needsCTQs and spec define

Target Zst

Process Map

*Items in BOLD are required or strongly recommended for that phase Note: This is Philips DFSS / ASQs procedure

PRACTICAL PROBLEM

Measure

STATISTICAL PROBLEM

Analyze

STATISTICAL SOLUTION

Improve

STATISTICAL CONTROL

Control

CTQs and spec define

Validated Specification

Meas. System Analysis

Estimate Z

Process Map

Cost of Un-quality

Statistical Problem Defined

Process capability measured

Exhaustive list of poss. xs

Potential vital few xs

Examination of distr. shape

Anova/percent contribution

N

/A

Used

N/A

N

/A

U

sed

N

/A

U

sed


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Problem solving technique

Poor comm.

with trucker

Lost parts

Otherhot job

Prod. Line

overload

Material

delivery

Order late from

customer

Poor

maintenance

Poor schedule

For trucker

Poor schedule

In general

Poor comm.Btw dept.

The causes of

production delay

RelationalTechnique

Here is the

Main causes

Equip.broke

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Which software

Is the best?PrioritizedTechnique

Criteria

Compatibility

25%

Cost

30%

Ease of

use

40%

Training

time

5%

A 4 1 3 3 2.65

B 1 4 2 2 2.35

C 3 2 4 4 3.15

D 2 3 1 1 1.85

Total cost

Software

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FMEA Technique Root causeanalysis

Car stall.

Electric problem Fuel problem

Low battery Ignition Mod Spark Plugfuses Fuel Inject Fuel pump No gasGas line

10% 20% 20%5% 15% 15% 10%5%

5 1 25 2 3 52

5 1 34 2 2 54

Chance

Ease

Cost

Total

1 5

Easer

Cheaper

Harder

Costly

1.0 0.4 1.00.45 0.6 0.75 1.00.3

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Design For 6-sigma

DFSS

Crystal ball Demo

& Case study


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Design For Reliability

Infant Mortality Useful Life Wear Out

TwTB

Prod / InstallDefects

ExternalStress Failures

WearoutFailures

Time

Hazard

Rate

CUSTOMER

CTQ (Y)

INITIAL QUALITY DISTRIBUTION

Z=6

LIMIT

No Failure

Failure

TIME

ReliabilityPDF

Weibull,Exponential etc

Performance

PDF

0.10

0.50

1.00

5.00

10.00

50.00

90.00

99.00

0.10

10.00 10000.00100.00 1000.00

Generated by: ReliaSoft's Weibull++ 5.0 - www.Weibull.com - 888-886-0410

Collimator Bulb Reliability

Time (hrs)

Unreliability,

F(t)

8:50:20 PM7/5/00GEUser's Name

WeibullSuspended

P=2, A=RRX-SF=64 | S=56CB/FM: 99.00%2 Sided-BC-Type 2

=0.74, =9132.27, =0.98

DFR

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HAST

10.00 1000.0100.00

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1.00

5.00

10.00

50.00

90.00

99.00

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0.5

0.6

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0.9

1.0

1.2

1.4

1.6

2.0

3.0

4.0

6.0

Mammo Detector Weibull Probability Plot

Time, (days)

Unreli

ability,

F(t)

12GVi

WM

W

F=C2-

Weibull Life Predictions

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Y = f(X)

YXs

This is the new process we have

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Continual improvements in the effectivenessContinual improvements in the effectiveness

of Quality Management System.of Quality Management System.

These commitments will be met throughThese commitments will be met through

documented and revieweddocumented and reviewedquality objectives, shared 6quality objectives, shared 6--sigma culture,sigma culture,

commitment to performance,commitment to performance,

and unyielding integrity.and unyielding integrity.

QQuality Policyuality Policy

17

6sigma Design

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