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谢宁DOE

谢宁DOE

qsconsult www.qsconsult.be

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Willy Vandenbrande

Shainin: A concept for problem

solving

Lecture at the Shainin conference

Amelior

11 December 2009

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Dorian Shainin (1914 –2000)

?Aeronautical engineer (MIT –1936)

?Design Engineer for United Aircraft Corporations ?Mentored by his friend Joseph M. Juran

?Reliability consultant for Grumman Aerospace (Lunar Excursion Module)?Reliability consultant for Pratt&Whitney (RL-10 rocket engine)?Developed over 20 statistical engineering techniques for problem solving and reliability ?Started Shainin Consultants in 1984, his son Peter is current

谢宁DOE

CEO.

Dorian Shainin and ASQ

?15th ASQ Honorary Member (1996)?First person to win all four major ASQ medals

?In 2004 ASQ created the Dorian Shainin Medal

–For outstanding use of unique or creative

applications of statistical techniques in the

solving of problems related to the quality of a

product or service.

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Dorian Shainin

?Not very well known outside USA (compared to Deming, Juran)

?1991: Publication of first edition of

“World Class Quality”by Keki Bothe ?2000: Second edition (Keki and Adi Bothe)?Books brought attention to Shainin methods, but are very biased.

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Problem Solving ?Focus is on variation reduction

LSL USL

LSL = Lower Specification Limit USL = Upper Specification Limit

Before

After

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Problem Solving

?But also …

LSL

After

Before

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Basic Shainin assumption

?The pareto principle of vital few and trivial many.?Only a few input variables are responsible for a large part of the output behavior.

–Red X TM

–Pink X TM

–Pale Pink X TM

?Problem solving becomes the hunt for the Red X TM

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Shainin tools

?Recipe like methods / statistics in the background

?Comparing extremes allows easier detection of causes

–BOB Best of Best

–WOW Worst of Worse

?Non parametrics with ranking tests in stead of calculations with hypothesis tests

?Graphical Methods

?Working with small sample sizes

?The truth is in the parts, not in the drawing: let the parts talk!

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Preliminary activities

?Define the critical output variable(s) to be improved (called problem Green Y?)?Determine the quality of the Measurement System used to evaluate the Green Y?

–A bad measurement system can in itself be

responsible for excessive variation

–Improvements can only be seen if they can be

measured

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Overview of Shainin tools

Components Search Multi-Vari chart Paired Comparisons Variables Search Full Factorials

B vs C

Scatter Plots Precontrol

Product / Process

Search

RSM methods

Positrol

Process Certification

Clue generating

Formal Doe tools

Validation

Optimization Assurance

Ongoing control

Control

20 –1000 variables

5 –20 variables

4 or less variables

No interactions

Interactions

General comments

?Gradually narrowing down the search

?Clear logic

–Analyzing

–Improving

–Controlling

?Not all tools are “Shainin”tools

?“What’s in a name?”

–Positrol versus Control Plan

–Process Certification versus Process Audit

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Tool details

?Overview of methods

?More info on B vs C TM and Scatter Plots in workshops

?Some more detail on

–Multi-Vari chart

–Paired Comparison TM and Product/Process

Search

–Pre Control

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Clue Generating / Multi-Vari Chart

Very useful tool and best applied before brainstorming causes on excess variation

Comments

Samples taken in production on current process Could be a big measurement investment Sample Size Divide total variation in categories

Search for causes of variation in the biggest category first

Principles Problem type: excess variation Wide applicability

Application Understand the pattern of variation

Define areas where not to look for problems Allow a more specific brainstorm Objective

Multi-Vari Chart

?Breakdown of variation in 3 families:

–Positional(within piece, between cavities, …)

–Cyclical(consecutive units, batch-to-batch, lot-to-

lot)

–Temporal (hour-to-hour, shift-to-shift, …)

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Multi-vari Chart

?If one family of variation contains a large part of total variation, we can concentrate on

investigating variables related to this family of variation.

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Clue Generating / Component Search

TM Disassembly / reassembly requirement limits application.

Comments

2 = 1 BOB and 1 WOW

Sample Size Select BOB and WOW unit

Exchange components and observe behavior.

Components that change behavior are Red X comp Principles Problem type: assembly does not perform to spec Limitation: Disassembly / Reassembly must be possible without product change

Application Find the component(s) of an assembly that is (are)

responsible for bad behavior

Objective

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Clue Generating / Paired Comparison

TM Practical application of “let the parts talk”Comments

5 to

6 pairs of 1 BOB and 1 WOW

Sample Size

Select pairs of BOB and WOW units Look for differences

Consistent differences to be investigated further Principles Problem type: occasional problems in production

flow

Application Find directions for further investigation

Objective

Paired Comparisons TM: method

?Step1: take1 good and 1 bad unit

–As close as possible in time

–Aim for BOB and WOW units

?Step2: note the differences between these units (visual, dimensional, mechanical, chemical, …). Let the parts talk!

?Step3: take a second pair of good and bad units.

Repeat step2

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Paired Comparisons TM: method ?Step4: repeat this process with third, fourth, fith, …

pair until a pattern of differences becomes apparent. ?Step5: don’t take inconsistent differences into account. Generally after the fith or sixth pair the

consistent differences that cause the variation

become clear.

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