6 Sigma and Reliability Engineering Integration Webinar · 6 Sigma and Reliability Engineering...

6 Sigma and Reliability Engineering Integration Webinar

byLouis LaValleeMike Silverman

5/7/2011 Ops A La Carte © 1


AgendaIntroductions and Agenda Review – 5 minutes

DFSS

DFR

Integrating the two techniques

Wrap-up

Q&A

DFSS / DFR Webinar Agenda

Wednesday 4 May 1011

Presenter’s Biographical

Sketch



Presenter’s Biographical Sketch – Lou LaVallee

◈ Lou is a Senior Reliability Consulting with Ops A La Carte.◈ Lou has over 30 years of experience as a sr. physicist,

systems engineering mgr. and design quality and reliability engineering mgr. at Xerox.

◈ Lou has strong validation experience of design quality and reliability through product reviews and customer interaction.

◈ Lou is a master black belt and has trained several thousand engineers in quality engineering, critical parameter management, robust design, six sigma methods, QFD, systems engineering, and reliability engineering.

◈ Lou works in the upstate New York area. ◈ Lou is a Certified Reliability Engineer (CRE).


Presenter’s Bio Sketch – Mike Silverman

◈Mike is founder and managing partner at Ops A La Carte◈ Through Ops A La Carte, Mike has had extensive experience

as a consultant to high-tech companies, and has consulted for over 500 companies in a variety of different industries including medical, defense, space, energy, consumer, telecom, and many others.

◈Mike just completed his first book on Reliability entitled “How Reliable Is Your Product: 50 Ways to Improve Product Reliability”

◈Mike has 25 years of reliability, quality, and compliance experience, the majority in start-up companies.

◈Mike is also an expert in accelerated reliability techniques, including HALT and HASS.

◈Mike and his team at Ops have authored and published over 50 papers and 30 seminars on reliability techniques and has presented these around the world including China, Germany, Japan, Taiwan, Korea, and Canada.

◈Mike is the IEEE Reliability Society Santa Clara Valley Chapter President.

◈Mike is a Certified Reliability Engineer (CRE)

Overviewof

Ops A La CarteReliability

Services and Training


COMPANY OVERVIEW

Confidence in Reliability5/7/2011 Ops A La Carte © 7

was named one of the top 10 fastest growing, privately-held companies in the Silicon Valley in 2006 and 2009 by the San Jose Business Journal.

Our Company

is a solid company that has been profitable every quarter since its inception due to its outstanding reputation, customer value and scalable business model.

is a privately-held professional reliability engineering firm founded in 2001 and headquartered in Santa Clara, California with offices in China, India and Singapore.


is made up of a group of highly accomplished Reliability Consultants.

Each of our consultants has 15+ years of Reliability Engineering and Reliability Management experience in various industries.

We tap a large network of labs, test facilities, and talented engineering professionals to quickly assemble resources to supplement your organization.

Our Team

Ops A La Carte ©5/7/2011 9

• Ops Solutions – Ops provides end-to-end solutions that target the corporate product reliability objectives • Ops Individual “A La Carte” Consulting – Ops identifies and solves the missing key ingredients needed for a fully integrated reliable product• Ops Training – Ops’ highly specialized leaders and experts in the industry train others in both standard and customized training seminars• Ops Testing – Ops’ state-of-the-artprovides comprehensive testing services

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assists clients in developing and executing any and all elements of Reliability through the Product Life Cycle.

has the unique ability to assess a product and understand the key reliability elements necessary to measure/improve product performance and customer satisfaction.

pioneered “Reliability Integration” – using multiple tools in conjunction throughout each client’s organization to greatly increase the power and value of any Reliability Program.


Ops A La Carte ©

Testing Services• Our own lab facility located in Northern California in the heart

of Silicon Valley. We provide HALT/HASS services on a world-wide basis, using partner labs for tests outside California.

• Second oldest HALT facility in the world, established in 1995(originally owned by QualMark)

• HALT equipment has all latest technology – only lab in region• Highly-experienced staff with over 100 years of combined

experience in HALT and HASS• Tested over 500 products in over 30 different industries• Our HALT/HASS services are fully integrated with our other

consulting services.5/7/2011 12

13

Ops’ New Reliability Book

How Reliable Is Your Product? 50 Ways to Improve Product Reliability

A new book by Ops A La Carte LLC® Founder/Managing Partner Mike Silverman

The book focuses on Mike’s experiences working with over 500 companies in his 25 year career as an engineer, manager, and consultant. It is a practical guide to reliability written for everyone in your organization. In the book we give tips and case studies rather than a textbook full of formulas. Available January 2011 in hardback for $44.95 or ebook for $19.95 @amazon.com or http://www.happyabout.com/productreliability.php For more info, go to www.opsalacarte.com

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Upcoming SeminarsMay 9-13

Santa Clara and via webinarTRACK 1: DFX TOOLS• Design for Reliability (DfR) – May 9-10• Design for Six Sigma (DFSS) – May 11• Design for Mechanical Reliability (DfMR) – May 12• Design for Warranty (DfW) – May 13• Design for Software Reliability (DfS) – May 13

TRACK 2: REL TOOLS: ALT/DOE/RCA• Design of Experiments – May 9-10• Best Accelerated Tests (BART) – May 11-12• Root Cause Analysis - May 13

Details for all are on the Ops Education Schedule for 20115/7/2011 Ops A La Carte © 14

FREE Webinars for 2011• Feb 17 – Medical Device Seminar/Webinar, San Jose• Mar 2 – Warranty Webinar (coincides with Warranty

Chain Management Workshop on March 17)• Mar 3 – Implantable Medical Seminar, Santa Clara• Mar 22 – Book signing for “How Reliable Is Your

Product”, Santa Clara• Apr 6 – Solar Reliability Challenges• May 4 – DfSS vs. DfR Webinar (tied with Symposium

and World Quality Conference)• Jun 1 – How to Use HALT with Prognostics (tied with

Prognostics Conference)

Details for all are on our site at www.opsalacarte.com5/7/2011 Ops A La Carte © 15

Upcoming Events• May 25 – SEMA (Solar) Event, San Jose. We will be

giving a reliability presentation• May 25 – ASQ Medical, Sunnyvale. We will be giving

a reliability presentation• June 6 – MD&M East, New York. We will be giving a

one day seminar on medical reliability testing• June 7-9 – ARS, San Diego. We will be exhibiting and

giving two presentations on reliability.• June 20-23 – PHM Conference, Denver. We will be

exhibiting and giving a presentation on reliability.

Details for all are on our site at www.opsalacarte.com

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6 Sigma and Reliability

Engineering Integration Webinar

byLouis LaValleeMike Silverman

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Attendees List Summary

Never used DFR 50%Early DFR User 18%Major DFR User 32%

Never used DFSS 42%Early DFSS User 33%Major DFSS User 25%

Never used DFSS & DFR integrated together 80%Early DFSS & DFR User (poorly integrated) 13% Major DFSS & DFR User 7%

Variation Discussion

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Variation for 6 and reliability• Variation Definition: A difference between two of more

similar things. • Ideally, two cheeseburgers from McDonalds are identical. The

first one in the morning and the last one in the evening are identical.

Much later

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Variation & its countermeasures

• Search for root cause & eliminate it• Screen out defectives (scrap and rework)• Feedback/feed‐forward control systems• Tighten tolerances (control, noise, signal factors)• Add a subsystem to balance the problem• Calibration & adjustment• Robust design (Parameter design/tolerance design)• Change the concept• Turn off the power

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Polling Question 1Have you used any of the previous variation

countermeasures?Yes, we have used 1 method

Yes, we have used > 1 methodsNo, but we have used other methodsNo, we have not used any methods

I don’t know5/7/2011 Ops A La Carte © 22

Standard Normal distribution (Probability density function)Mean = 0., std dev=1.0

Demarcations shown at 6 different standard deviation levels including fractional area under curve e.g. 68.26 % of the area under the curve is between +1 and ‐1

Point of Inflection

1

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USLLSL

target

All are ‘in spec’ . Which distribution is preferred to minimize quality loss

target target

2

22

/$_}){(

unittcoefficienlosskxkQ

LSL

target

Average Quality Loss Q for nominal the best measure

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freq

Brownian Motion & Variation

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Central Limit Theorem Simulation & Variation

What happens to shape of distribution when something nonrandom occurs? What does it mean when you don’t observe a normal distribution?

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Polling Question 2Have you ever experienced a non‐normal

distribution?Yes, I have seen that once

Yes, I see that oftenNo I have never seen that

I don’t know5/7/2011 Ops A La Carte © 27

DFSS &Reliability Integration“the process of seamlessly,

cohesively integrating reliability and 6 Sigma

processes together to maximize quality & reliability at the lowest

possible cost”5/7/2011 Ops A La Carte © 28

Design for Six Sigma

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Polling Question 3Does you current job require

increasing Quality engineering expertise?YesNo

I don’t know

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6Term originally comes from statistics, where is Greek symbol for standard

deviation. is scalar measurement of univariate variation. Six standard deviations between equal bilateral spec limits is implied. Statistics help us measure and understand both individual data points, averages, and variation. Primary focus is achieving improvements in quality and cost .

LeanFocus is on eliminating non‐customer value added waste in a product,

process or service. Result is reducing service cycle times, improving on‐time deliveryperformance, and reducing cost.

Lean 6Combines the speed and power of both Lean and 6

“Only a fast and responsive process is capable of achieving high quality,and only a high quality process can sustain high velocity”

Evolution of 6

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Six Sigma has evolved from product focus (defect reduction) to project focus (cost reduction) to customer value (productivity) to enterprise performance (bottom line growth) . Six sigma is always in a continuous improvement mode. Each time you look, a new best practice has been added.

DFSS Design for Six Sigma is a similar set of quality improvement tool used when the process or product has not yet been developed. Instead of fixing problems within existing process, DFSS is designed to prevent problems before they occur by creating a design based on the principles of Six Sigma.

DFR has evolved from industrial activities focused on problem solving downstream. It has evolved to support and model upstream engineering and scientific activities. Many products now have requirements defined for both reliability and maintainability.

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DMAIC Process Road Map

ACTIVITIES

•Identify Problem•Complete Charter•Develop SIPOC Map•Map Business Process•Map Value stream•Gather VOC & VO Business•Develop CCR & CBR’s•Finalize Product Focus

DEFINE MEASURE

• Identify Key Input, Process and output Metrics•Develop Operational Definitions•Develop Data Collection Plan•Validate Measurement System Collect Baseline Data•Determine ProcessPerformance/Capability Opportunity

ANALYZE

• Propose Critical X’s• Prioritize Critical X’s• Conduct Root CauseAnalysis on Critical X’s• Validate Critical X’s• Estimate the Impact of Each X on Y• QuantifyOpportunity• Prioritize Root Cause

IMPROVE

• Develop Potential Solutions• Develop Evaluation Criteria &Select Best Solutions• Evaluate Solution for Risk• Optimize Solution• Develop ‘To‐Be’ Process Map(s)and High‐Level ImplementationPlan• Develop Pilot Plan & Pilot Solution

ACTIVITIES in 1st four phases

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•Pareto Charts• Project Selection Tools• PIP Management Process• Value Stream Map• Various Financial Analysis• Charter Form• Stakeholder Analysis• Communication Plan• SIPOC Map• High‐Level Process Map• Non‐Value Added Analysis• VOC and Kano Analysis• RACI and Quad Charts

DEFINE MEASURE

• SIPOC Map• Operational Definitions• Data Collection Plan• Statistical Sampling• Measurement System Analysis(MSA), Gage R&R• Constraint Identification• Setup Reduction• Generic Pull• Kaizen• TPM• Control Charts• Process Capability

• Pareto Charts• C&E Matrix• C&E/Fishbone Diagrams• Brainstorming• Detailed ‘As‐Is’ Process Maps• Basic Statistical Tools• Supply Chain AcceleratorAnalysis• Non Value‐Added Analysis• Hypothesis Testing• FMEA• Box Plots• Interaction Plots• Simple & Multiple Regression• ANOVA (1 way & 2 way)• Logistic Regression• Analysis of Means• Box Cox Transformations• Chi Square Analysis• MultiVari Plots

ANALYZE

• Brainstorming• Benchmarking• Process ImprovementTechniques• Line Balancing• Process Flow Improvement• Replenishment Pull• Purchasing and SalesStrategy• Poka‐Yoke• FMEA• Solution Selection Matrix• ‘To‐Be’ Process Maps• Piloting and Simulation• Response surface Methodology• Queuing Theory

IMPROVE

TOOLS: 1st 4 phases

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Y = f(X)6 Fundamental Concept

Y’sDependentOutputEffectSymptomMonitor

X1, …XNIndependentInput‐processCauseProblemControl

In reliability engineering for example , Y is the stochastic variable, times to failure, and F(x) is the failure mechanism, or mechanistic model . Variation is implied, as well as response5/7/2011 Ops A La Carte © 35

Recent Newsworthy DFR & DFSS candidates

• Japan Nuclear Power Plant reactors and generators• BP deep water oil rig blowout preventer malfunction• Toyota accelerator pedal recall• GM, Ford, Chrysler automobile reliability & recall issues• Hurricane Katrina levee and flood wall failures• 20 Airline Crashes worldwide in 2010• Space Shuttle Challenger explosion• I‐35W Mississippi River bridge Collapse• San Bruno Ca. gas line explosion• Cruise ship engine failures off San Diego coa• Southwest Air/Boeing aluminum panel break away (rivet holes too big)

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Six Sigma with lean is the integration of two powerful Business Improvement Approaches

Precision + Accuracy + VOC Speed + Low Cost + Flexibility

On‐target Performance

LEANSIX SIGMA

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LEAN 6 SIGMA

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6 + Lean + Reliability• 6 approach is a compilation and integration of best quality

engineering practices, business processes, and tools from the past 80 years.

• Lean includes the 6approach plus additional efficiencyenhancements like reducing waste, creating higher speed processes, lower costs, and improved flexibility.

• Reliability engineering is a set of tools, processes, and activities to augment and complement the lean 6approach. It includes design for reliability (DFR) , reliability characterization, reliability optimization, life cycle cost minimization, forecasting, maximizing maintainability, durability, availability, safety, etc.

• There is overlap in some areas as might be expected, like the common use of quality function deployment (QFD) to capture and translate voice of customer, design of experiments (DOE), Modeling & Simulation, …

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Structure

Function Behavior

MappingSynthesis

Mapping

Mapping DysfunctionSymptomsFailure modesFailure mechanismsIdeally zero measures

Physics/ChemistryFundamental modelsTheoretical modelsEmpirical modelsSimulation modelsFlow down linkages

Geometry/shapeMaterials, indented listsBOM, eng. drawings

Function‐Structure‐Behavior Decomposition

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6 Sigma : The Importance of Measurement

Processes must be measured to establish a baseline (current condition) against which future improvements can be quantified

“If you can’t measure it, you can’t manage it.W. Edwards Deming (1900 ‐ 1993)

Can you prove that the data were produced by your measurement system without distortion or contamination ‐‐‐and without affecting the process being observed? Is data valid and meaningful?

Thousands of available measurement systems add to the complexity of experimentation.

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Measurements for ExperimentationWhat to measure: Measurements are selected not given.

Measurement Criteria: Continuous numbersCompleteFundamentalPracticalMonotonic with control factorsRelated to basic energy transfer mechanism of systemMeasurement capabilityEngineering FocusPicks up meaningful information about dysfunction

Types of Measurement Data:Binary (go/no go)Categorical (ordinal, nominal, ranks, …) Counts or frequenciesCounted fractions, percentagesScalar, Vector quantitiesComplex , matrix

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X

Stack 1

X

Stack 2

X

Stack 3

X

Stack 4

Lack of monotonicity : displacement response for paper stacks Many different ways to get the same number X

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Building reliability into concept selection5/7/2011 Ops A La Carte © 45

Original List of Criteria for car horn concepts

Ease of achieving 100 – 125 decibel (sound level) Ease of achieving 2000 – 5000 Hertz (sound frequency) * Resistance to corrosion (water, pollutants) * Resistance to vibration, shock, acceleration/deceleration, wear‐and‐tear * Resistance to temperature cycling and extremes * Low power consumption * Ease of maintenance Small size * Long service life Low manufacturing cost Ease of installa on * Long shelf lifeCriteria Added During the Round 1 Discussion Quick response me * Small number of parts—simplicity of design Ease of opera on (accessibility, emergency response) Ease of integra on into the automobile subsystems Low weight

* Reliability issues during concept selection

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DFSS Project Focus and Selection

1. Identify potential projects with high return/ease of implementation

2. Use accelerated approach on initial projects (1 week)

3. Use analytical methods to estimate potential benefits (ROI, NPV) and rank order alternate projects

4. Avoid project scope creep

5. Successfully complete projects, and fold them back into further training

6. Determine cost savings from project completion.

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Simple Metal Helical Compression SpringForce vs Displacement

Force F

x (mm)0,0

Ideally, all points fall on dashed lineOrigin 0,0Noise factors add variationVariation may exceed tolerable limits

Slope (sensitivity) and Root mean squared error parameters

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Case Study: Four hypothetical I‐V curves with two noise conditions

Q=charge density5/7/2011 Ops A La Carte © 49

I‐V staircase charging data

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Marginal Means Plot For Photoreceptor DOE

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Ideal function development was used successfully to improve robustness and reliability

Y= f(X) = X+

ANOVA & regression tools provided optimum conditions in 1/6 time of time‐to‐failure testing. +3 dB gain in S/N ratio 2x reliability improvement.

Development engineers and their management are always looking for efficient ways to reduce expenditures for system reliability testing. This method works well for many situations.

Take Aways from P/R experimental Design

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Polling Question 4Could you use DOE to improve your golf

game?YesNo

I don’t know

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Quality Function Deployment‘Whats’ become ‘Hows’

Matrix approach becomes a powerful framework for systems engineering, quality engineering and reliability engineering

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Copy qualityas good as Lithography

Line density, background density

VOC

Line density, background density

HOQ #1

System level

Transferred mass/areaPatch reflectanceToner dispense rate

Module level

HOQ #2

Printer Toner Dispenser

Toner Dispense rate

Auger speedAuger clearance

HOQ 3

Subsystem level

Drive gear pitch diamAuger diamHousing diam

Component level

HOQ 2Auger speedAuger clearance

Printer Toner Dispenser

Drive Gear Pitch diamAuger diameterHousing Diameter

PressureTem

peratureShot w

eight

HOQ # 5

Injection Molding Manufacturing Process Level

FromHOQ # 4

There may be many requirements and engineering specs. Only those that are new, difficult, extremely important, have a negative correlation, or offer/enable a competitive opportunity with be carried through.

Critical few only

House 1 Pencil example

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Successful Lean Six Sigma Deployment Requires Company Wide Involvement

Master Black Belts

•Train black belts/green belts•Coaching•Leads Lean 6 Sigma projects•Full time position

Deployment managers

•Leads BU performance Improvement•Prioritized Projects•Full time position

Operations Leadership

Project Sponsors

Green Belts

Project Team members

Black Belts

All Employees• Understand Vision• Apply concepts to job & work area

•Owns Vision, direction integration, business results•Lead Change

•Project owner•Implements solutions•Owns financial Results•Part time as part of job

•Leads six sigma projects•Trains and coaches project teams•Full time position

•Provides project specific support•Can be yellow or green belt•Part time on prrojects

•Participates on BB teams/ leads projects•Part time on projects

Centralized Coordination & Training

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DFR Design for Reliability

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Polling Question 5Does you current job require

increasing Reliability engineering expertise?

YesNo

I don’t know

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DFR is a process that describes the entire set of tools and activities that support the effort to increase a product’s reliability and are applied from the early concept stage of a design all the way through to product obsolescence.

Reliability Assessment Define Reliability Requirements early in design cycle. Think preventive

rather than reactive. Don’t create the problem. Technology readiness– no new inventions required so that a predictable

schedule can be maintained Control complexity and newness of work processes, modules, parts,

software, design rules, manufacturing processes, … to control initial reliability

Selection of activities and tools to enable delivery of good reliable products.

Training (and certification) for both management and engineers in deficient areas, eg. DFR.

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How Do You Set up a DfR Program?

A reliability assessment is our recommended first step in establishing a reliability program. This mechanism is the appropriate forum for selecting the best tools for each product life cycle phase.

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Reliability Program Assessment

A detailed evaluation of an organization’s approach and processes involved in creating reliable products. The assessment captures the current state and leads to an actionable reliability program plan.

• Initiate a Reliability Program• Determine next best steps• Reduce customer complaints • Select right tools• Improve reliability

Now

Goal

$ unreliability

$ Profits

Assessment Interviews

StatisticalData Analysis

Benchmarking

Gap Analysis

Program Plan

complaints

fieldfailures

satisfaction

marketshare

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Reliability Maturity MatrixMeasurement

Category Stage I:

Uncertainty Stage II:

Awakening Stage III:

Enlightenment Stage IV: Wisdom

Stage V: Certainty

Management Understanding and Attitude

No comprehension of reliability as a management tool. Tend to blame reliability engineering for ‘reliability problems’

Recognizing that reliability management may be of value but not willing to provide money or time to make it happen.

Still learning more about reliability management. Becoming supportive and helpful.

Participating. Understand absolutes of reliability management. Recognize their personal role in continuing emphasis.

Consider reliability management an essential part of company system.

Reliability status Reliability is hidden in manufacturing or engineering departments. Reliability testing probably not part of organization. Emphasis on initial product functionality.

A stronger reliability leader appointed, yet main emphasis is still on an audit of initial product functionality. Reliability testing still not performed.

Reliability manager reports to top management, with role in management of division.

Reliability manager is an officer of company; effective status reporting and preventive action. Involved with consumer affairs.

Reliability manager is on board of directors. Prevention is main concern. Reliability is a thought leader.

Problem handling Fire fighting; no root cause analysis or resolution; lots of yelling and accusations.

Teams are set up to solve major problems. Long-range solutions are not identified or implemented.

Corrective action process in place. Problems are recognized and solved in orderly way.

Problems are identified early in their development. All functions are open to suggestion and improvement.

Except in the most unusual cases, problems are prevented.

Cost of Reliability as % of net revenue

Warranty: unknown Reported: unknown Actual: 20%

Warranty: 3% Reported: unknown Actual: 18%

Warranty: 4% Reported: 8% Actual: 12%

Warranty: 3% Reported: 6.5% Actual: 8%

Warranty: 1.5% Reported: 3% Actual: 3%

Feedback process None. No reliability testing. No field failure reporting other than customer complaints and returns.

Some understanding of field failures and complaints. Designers and manufacturing do not get meaningful information.

Accelerated testing of critical systems during design. System level modeling and testing. Field failures analyzed and root causes reported.

Refinement of testing systems – only testing critical or uncertain areas. Increased understanding of causes of failure allow deterministic failure rate prediction models

The few field failures are fully analyzed and product designs or procurement specifications altered. Reliability testing done to augment reliability models.

DFR program status No organized activities. No understanding of such activities.

Organization told reliability is important. DFR tools and processes inconsistently applied and only ‘when time permits’.

Implementation of DFR program with thorough understanding and establishment of each tool.

DFR program active in all areas of division – not just design & mfg’ing. DFR normal part of R&D and manufacturing.

Reliability improvement is a normal and continued activity.

Summation of reliability posture

“We don’t know why we have problems with reliability”

“Is it absolutely necessary to always have problems with reliability?”

“Through commitment and reliability improvement we are identifying and resolving our problems.”

“Failure prevention is a routine part of our operation.”

“We know why we do not have problems with reliability.”

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Reliability Maturity Matrix

Measure-ment

Category

Stage I:Uncertainty

Stage II:Awakening

Stage III:Enlighten-

ment

Stage IV:Wisdom

Stage V:Certainty

Problem handling

Fire fighting; no root cause analysis or resolution; lots of yelling and accusations.

Teams are set up to solve major problems. Long-range solutions are not identified or implemented.

Corrective action process in place. Problems are recognized and solved in orderly way.

Problems are identified early in their development. All functions are open to suggestion and improvement.

Except in the most unusual cases, problems are prevented.

Lets look at one row to get a better understanding.

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Next Steps

• Determine current state of your organization (Summary of Assessment)

– Identify strong and weak areas

• Goal Setting–Market Analysis to gather requirements– Benchmarking

• Gap Analysis

• Develop plan and implement

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Ops A La Carte ©

RELIABILITY GOAL‐SETTING

Establish the target in an engineering meaningful manner

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Reliability Definition

Reliability is often considered quality over time.

Reliability is…

“The ability of a system or component to perform its required functions under stated conditions for a specified period of time”

IEEE 610.12-1990

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Reliability Goals & Metrics Summary

• Reliability Goals & Metrics tie together all stages of the product life cycle. Well crafted goals provide the target for the business to achieve, they set the direction.

• Metrics provide:– the milestones,– the “are we there, yet”, and– the feedbackthat all elements of the organization require to stay on track toward the goals.

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Ops A La Carte ©


• A reliability goal includes each of the five elements of the reliability definition.– Probability of product performance – Intended function– Specified life– Specified operating conditions– Customer expectations

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• A reliability metric is often something that organization can measure on a relatively short, periodic basis:– Predicted failure rate (during design phase)– Field failure rate– Warranty– Actual field return rate– Dead on Arrival rate

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Ops A La Carte ©

• A Reliability Program and Integration Plan is crucial at the beginning of the product life cycle because in this plan, we define:– What are the overall goals of the product and of each assembly that makes up the product ?

– What has been the past performance of the product ?– What is the size of the gap ?– What reliability elements/tools will be used ?– How will each tool be implemented and integrated to achieve the goals ?

– What is our schedule for meeting these goals ?

Reliability Program and Integration Plan

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Example of Design for Reliability (DfR) Tools

• Reliability Modeling and Prediction• Thermal Analysis• Derating Analysis• Failure Modes and Effects Analysis (FMEA)• Fault Tree Analysis (FTA)• Design of Experiments (DoE)• Human Engineering/Human Factors Analysis• Highly Accelerated Life Test (HALT)• Accelerated Life Test (ALT)• HALT vs. ALT• RDT and ORT• Highly Accelerated Stress Screen (HASS)• Root Cause Analysis (RCA)• Restriction of Hazardous Substances (RoHS)• Outsourced Engineering and Reliability• Field Data Analysis

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DfR Tools by Phase

Phase Activities Tools

ConceptDefine project reliability

requirements (Reliability Program and Integration Plan)

BenchmarkingInternal Goal SettingGap Analysis

DesignArchitecture

and High Level Design

Modeling & Predictions

Reliability ModelingSystem Failure

Predictive Analysis (FMECA & FTA)

Human Factors Analysis

Initial System Testing Defect Detection at System Level HALTDVT

Final System Testing Verify Reliability Metrics RDTV&V

Operations and Maintenance

Continuous assessment of product reliability

FRACASRCA

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GoalSetting

Assess-ment

Bench-mark

FTAFMEA

GoldenNuggets

Component Selection

Predict-ions

ThermalAnalysis

DeratingAnalysis

POF

DOE Tolerance Analysis

Preventive Mainten.

EOL Analysis

WarrantyAnalysis

TestPlan

HALT RDT ALT HALT-AFR Calculator

FEA SoftwareReliability

RCA CLCA

VendorAssessmt

HASS ORT OOBA

LessonsLearned

WarrantyReturns

ReliabilityReporting

Statistics EDA forObsolesc

Out-sourcing

Metrics

ReliabilityPlan

CO

NC

EPT

PHA

SED

ESIG

NPH

ASE

MA

NU

FAC

TU

RIN

G

PHA

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Gap Analysis

Block Diagrams


Ops A La Carte ©

Next Step

• Execute the Reliability Program in accordance with the Program Plan

• Use your metrics to check how you are doing along the way

• Feed information from each step forward to integrate the techniques together

• Modify the design as needed based on your findings• Release the product when you have satisfied your goals

• Closely monitor the product in production and in the field and feed misses back into this design and into the design process for future designs

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Polling Question 6How would you rate your product

development process on a scale of 1‐4 ?

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1 (uncertainty – no organized activity)2 (awakening – documented but not practiced)3 (enlightenment – implemented in key phases)4 (wisdom – implemented in all phases)I don’t know

DOE techniques can be used to systematically investigate the variables (factors) that influence the life of the product, thereby providing the analyst with information that can be used to improve reliability. Noise factors can be assigned to an orthogonal array to help identify which stresses are most detrimental to lifetime response.

DOE methods can be used in the production stage to estimate product reliability (e.g. warranty predictions). This can be done as a two‐step process in which DOE is used first to identify the control/noise factors that affect product reliability. Then the principles of accelerated life testing analysis can be used to create a model that enables predictions (under normal usage conditions)

Reliability Improvement using DOE

Problems: ‐‐The lifetime responses are usually not normally distributed, limiting traditional analysis. Censored/incomplete data, which are not uncommon, cannot be handled by traditional means. Homogeneous variances assumption across levels of response are mostly not valid.

Note pairwise matching of reliability activity and QE tools

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1 Low Resistance Failures (most common failure mode) ‐ Insulation resistance degrades over time or precipitous failure from environmental change , moisture, contamination

2 Mechanical Failures ‐ Inadequate lubrication, unbalance , vibration, and misalignment. (Gradual)

3 Overload failures ‐ Substantially more current drawn than rated load capacity. (Sudden)

windings

Experimental design example DC Electric Motor Schematic

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Factor and levels

Assignment to L16 Orthogonal array with coded levels as +/‐ 1

DC Electric Motor Experimental Design

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Layout with time to fail response data are shown in table below

Coded design variablesResponse: time to fail (hrs)

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2‐parameter Weibull PDF is selected, as it fits the data with larger log likelihood value (smallest model fit error)

ANALYSIS of Electric Motor Example

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The scale parameter in the Weibull PDF, above is usually selected for polynomial regression against the factors in the design:

The parameters i in the general linear model are determined using regression and used to predict and in the reliability prediction .

If time, cost and other resources allow, it is always recommended to conduct a follow‐up experiment to confirm the best settings for improved life. The gain in life from standard conditions can also be estimated.

Failure time prediction data analysis:

Results of the final model with significant factor effects

http://www.weibull.com/hotwire/issue88/hottopics88.htm

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DEFINE Phase (Reliability Activities) ACTIVITIES Decompose system into hierarchal functional elements (subsystems, subassemblies,

components) with comparable complexity Define high level product Reliability Goals and requirements Flow down of reliability requirements from system to components Identify potential Failure modes FRACAS initiated Measurement system selection Allocation process for reliability of subsystems Benchmarking Similar Product’s Reliability following decomposition Software reliability allocation Identify Reliability Software Tools (FRACAS, FMECA, ) FMEA for selected concepts Identify resources necessary for reliability engineering success Collect Voice of Customer Reliability data collection Identify potentially useful physics of failure models and update then to current situation Early predictions of future customer usage conditions Early prediction of future machine load profile Predictions of future environmental stresses. Mission defined, preliminary schedule defined, Mission statement published Human interactions effects prediction Liability management Major risks identified

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MEASURE Phase (Reliability Activities)

ActivitiesFailure mechanism evaluation Identify potential measures needed for failure analysisIdentify potential measures needed for CP degradation testing Identify potential measures for time to failure and tendency to failCollect & Understand measures made during previous life test Develop operational definitions of possible functional failuresMeasurement system & hardware reliability, maintainability, durability for life testingValidate cost opportunity for reliability improvementReliability data collection planIdentify Constraints for reliability testing (time, cost, samples)Safety measures identifiedWarranty measures identifiedBuilt in test measurement considerations definedMeasures for redundancy definedMeasures for prognostics definedPotential Critical parameters and critical specifications identifiedDownstream Manufacturing and service measurements identified considering lower cost and lower complexity

Data collection MethodsSelection of what to measure for reliability improvementValidation of measurements, Measurement errors/uncertainty

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Pre‐Training Assignment

Class Participation

Post Training

Continuing Education

Progressive steps

Content

Selecting Project to developStudy Material in advanceSME/Mgr Engagement

Attend the courseExercises in class

Register themeProject ImplementationConsult & direction by SMEProgress Documentation

Proceed to advanced levelsFollow up by dedicated staffBecome in‐house trainerAdvise other people

6 Roles & Responsibilities in Training

Trainee Manager Champion

Training Admin

SME

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• Design for reliability (DFR) and Design for six sigma (DFSS) are modern methods for both problem prevention and problem solving.

• Both have scientific , engineering, and statistical underpinnings.• Both have evolved over the past few decades from more humble beginnings.

• DFSS has evolved into a well architected system of management principles, analytical methodologies, and reporting systems.

• DFR is on a similar path. The DFR focus is on the preparation of a system or platform design to perform required functions for a specified period of time, but also to help solve problems associated with functional failures when they arise.

• Integration of DFSS methods with DFR methods will take some time and effort but it is inevitable.

• Engineering positions requiring both reliability and quality engineering skills are becoming more commonplace. This will force engineers and management to become proficient in both.

Summary

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Thank you to everyone who attended this afternoon's webinar. We hope you found it informative.

If you did not make it, make sure you go to our webinars page, where you can download the slides as a PDF and a recording of the session.

Further questions may be sent to:[email protected]@opsalacarte.com(408) 654‐0499www.opsalacarte.com

Contact Info

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The probability density function (pdf) is a mathematical function that describes the time to fail distribution. The pdf can be represented mathematically or on a plot where the x‐axis represents time, as shown above.

Time

frequency

One of the most popular life distribution is the 3‐parameter Weibulldistribution shown below:

the scale parameter, η, defines where the bulk of the distribution lies. The shape parameter, β, defines the shape of the distribution and the location parameter, γ, defines the location of the distribution in time. t is the time measure, e is exponential function

Weibull Life Distribution

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Model Example Application

Arrhenius Model failure mechanisms that depend on temperature (e.g., chemical reactions)

Eyring Model Model multiple stresses. Many other models are simplified versions of the Eyring model.

Inverse Power Rule for Voltage (simplified Eyring model)

Capacitor dielectric breakdown

Exponential Voltage Model

Capacitor dielectric breakdown

Electromigration Model Semiconductor metallization line failure

Coffin‐Manson Model Mechanical crack growth

Table 1: Common Acceleration Models

Variability & ALT Analysis

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Roadmap Comparison

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DMAIC DMEDI

Define – Determine Project Scope, Objectives, Resources, Constraint

Define – Very Similar to DMAIC

Measure – Determine Customer Groups, Determine CCR’s, Obtain Data to Quantify Existing Process Performance

Measure – Define Customers and Needs Using VOC and QFD, Determine CCR’s

Analyze – Analyze Data to Identify Tangible Root Causes of Defects

Explore – Develop Design Concepts, and High‐Level Design

Improve – Intervene in the Process to Improve Performance

Develop – Develop and Optimize Detailed Design

Control – Implement a Control System to Maintain Performance over Time

Implement – Validate Design with Pilot, Establish Controls, Full Scale Implementation

Sample Variance & Standard deviation

Propagation of variance

22

22

22

2 ... dbay dy

by

ay

Sensitivity terms

Taylor series expansion without covariance terms

Y=f(a,b,…d)

Six Sigma in PracticeWhat does it mean?

99% Performance 6 Sigma Performance99.999663% Meet Spec

202 Billion Pieces of Mail Delivered by USPS per year2.02 Billion pieces Lost per Year 680740 pieces lost per year

24/7 Power Delivery to Your Home87 Hours without Power every Year Less than two minutes without power

per year

510 Million Prescriptions Worldwide per year5.1 Million Wrong Prescriptions per Year 1719 Wrong Prescriptions per Year

27 Billion Credit Card Transactions per year0.27 Billion wrong transactions per year 90990 wrong transactions per Year

Ref: Scott Burr, 2005, “Design for Six Sigma” Hubenthal‐Burr Associates

6 Sigma and Reliability Engineering Integration Webinar · 6 Sigma and Reliability Engineering...

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