Siemens Electric Heating AS Bratsbergvegan 5 N-7493 TRONDHEIM Norway 21/6/2002

21/6/2002 1

PRO-ENBIS: G6RT-CT2001-05059

Siemens Electric Heating, Trondheim

Siemens Electric Heating ASSiemens Electric Heating ASBratsbergvegan 5

N-7493TRONDHEIM

Norway

21/6/2002Tel No +47 73 95 90 00

ENBIS industrial visit

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E: Introduction of the team - 5 mins E: Introduction to ENBIS - 10 minsS: Introduction to Siemens Trondheim - 15 minsE: SQM survey, Design of Experiments, 6-sigma - 45 minsS: Topics to be covered in visit - 15 mins

On Site Visit - 45 mins

Discussions on opportunities - 30 mins Conclusion - 15 mins

Proposed agenda

(S - Siemens, E - ENBIS team)

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Jon Tyssedal, [email protected] of Statistics, NTNUExpert in Statistics Maria Fernanda Ramalhoto, [email protected] of Statistics,Instituto Superior Tecnico, LisbonExpert in Reliability and Quality Improvement

Ron Kenett, [email protected] Management Consultant, CEO KPA Ltd.Expert in Industrial Statistics and Quality Management

ENBIS team

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ENBIS team

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ENBIS team

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Industrial StatisticsIndustrial StatisticsIndustrial StatisticsIndustrial Statistics Multivariate Quality ControlMultivariate Quality ControlMultivariate Quality ControlMultivariate Quality Control

Six SigmaSix SigmaSix SigmaSix Sigma

Internet SurveysInternet SurveysInternet SurveysInternet SurveysSoftware Process QualitySoftware Process QualitySoftware Process QualitySoftware Process Quality

ManagementManagementDashboardsDashboardsManagementManagementDashboardsDashboards

SPCSPCSPCSPC

Design of Design of ExperimentsExperimentsDesign of Design of

ExperimentsExperiments

OrganizationalOrganizationaleffectivenesseffectiveness

OrganizationalOrganizationaleffectivenesseffectiveness

Ron Kenett (25 yrs of experience, 4 books)25 yrs of experience, 4 books)

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ENBIS

European Network for Business and Industrial Statistics

www.enbis.org

Introduction to ENBIS

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ENBIS Mission

- Foster and facilitate the application and understanding of statistical methods to the benefit of European business and industry

- Provide a forum for the dynamic exchange of ideas and facilitate networking among statistical practitioners

- Nurture interactions and professional development of statistical practitioners regionally and internationally.

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- To promote the widespread use of sound science driven, applied statistical methods in European business and industry,

- That membership consists primarily of statistical practitioners from business and industry,

- To emphasize multidisciplinary problem solving involving statistics,

- To facilitate the rapid transfer of statistical methods and related technologies to and from business and industry

ENBIS Vision

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- To link academic teaching and research in statistics with industrial and business practice,

- To facilitate and sponsor continuing professional development,

- To keep its membership up to date in the field of statistics and related technologies,

- To seek collaborative agreements with related organizations.

- ENBIS is a web based society

ENBIS Vision – continued

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During the first International Symposium on Industrial Statistics, some 20 statisticians and practitioners agreed to push forward a European society for industrial statistics.

August 21, 1999, Linköping, Sweden

Meeting of the provisional executive committee. The name ENBIS was chosen for the new network.

Febr. 26-27, 2000, Eindhoven, NL

More than 80 persons participated in the founding conference.

December 11, 2000, Amsterdam, NL

ENBIS History

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- General assembly- Council- Executive committee- Permanent office (Amsterdam)

Administration

ENBIS Organization

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- Design of experiments- Reliability and safety- Data mining / warehousing- General statistical modelling

Working groups

- Process modelling and control

- Quality improvement- Statistical consultancy

- bENBIS (Belgium)- nENBIS (Netherlands)- iENBIS (Israel)

Local networks

ENBIS Organization

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- No membership fee (for the time being)- 560 members (May, 2002)

Members

- 500 Euros per annum- 7 Corporate members (May, 2002)

Corporate Members

ENBIS Organization

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ENBIS Membership benefits

ENBIS offers its members:-Network facilities-Conferences-Courses-Thematic network Pro-ENBIS

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ENBIS Networking facilities

The website www.enbis.org offers:-ENBIS News-General announcements-Event lists-Links to relevant websites-Information on other members-Forum facilities

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www.enbis.org

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Founding conference80 participants

December 11, 2000, Amsterdam, NL

First Annual Meeting on Business and Industrial Statistics101 participants43 submitted abstracts

September 17-18, 2001, Oslo, Norway

Second Annual Meeting on Business and Industrial Statistics105 submitted abstracts

September 23-24, 2002, Rimini, Italy

ENBIS Conferences

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Pro-ENBIS

Pro-ENBIS is a thematic network of organisations contracted for three years with the European Commission.

Its mission is “to promote the widespread use of sound science driven, applied statistical methods in European business and industry.”

Pro-ENBIS was granted a budget from the EC of about 800 000 Euros.

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Co-ordinator: University of Newcastle upon Tyne (UK).

Organisations from all over Europe, not just the EC.

Funding to achieve specific disemination outcomes, e.g., organising workshops, seminars, industrial industrial visitsvisits and publishing case-study based papers.

Pro-ENBIS

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Objectives of Industrial Visits

- Disseminate Statistical Best Practices in Europe

- Foster new research collboration

- “Listen to the customers”:

Learn from industry

indifies needs of industry

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E: Introduction of the team - 5 mins E: Introduction to ENBIS - 10 minsS: Introduction to Siemens Trondheim - 15 minsE: SQM survey, Design of Experiments, 6-sigma - 45 minsS: Topics to be covered in visit - 15 mins

On Site Visit - 45 mins

Discussions on opportunities - 30 mins Conclusion - 15 mins

Proposed agenda

(S - Siemens, E - ENBIS team)

21/6/2002 23



Reliability, Safety and Quality Improvement

Reliability is Quality over Time. Maintenance is a Reliability Function. Therefore “Reliability culture” and “Maintenance

Culture” clearly should be part of an “Extended Quality Culture”.

SQM SurveySQM SurveySQM SurveySQM Survey

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Workshops, Round Tables

Claims from industry


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ESREL’2001 Round Table

Industry: To find consultants is easy. They advertise. To find academics is not easy. The industry and the governmental institutions do not know what academics are doing.


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Industry: Do not have the time to read academic journals. The papers which shall be relevant are usually published in too many different journals. Even the multinational company is not able to follow what is going on in the academic world.


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Academics: We model such and the reliability is 99%.

Practitioners: The reliability 99% can be pushed to 99.8% if a certain specific change

is made, or if doing such the reliability drops to 98% and the cost will be, for

instance, cut to a 1/2. What matters is how to trigger on the design to improve it.


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A Survey on Reliability and Quality Improvement

The following questionnaire distributed in print (7 pages) for discussion and future collaboration. Material of the WP4 first Industrial Visit-Nestle-very briefly mentioned and made available at request.


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Questionnaire on SQM

Company Profile: Size; Individuals directly involved in SQM activities; Industry nature; Benchmarking activities.

1. Use of Reliability Techniques. 2. Use of Maintenance Techniques


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Questionnaire (cont.)

3. Use of Control Charts Techniques. 4. Use of Acceptance Sampling Plans. 5. Use of Economic Design Techniques. 6. Use of Cost-Benefit Analysis.


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7. Use of Inventory Control/Supply Chain Techniques.

8. Use of Data Quality Control Techniques.

9. Use of Periodicals.


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10. Problems in Practice:– List of most relevant problems reported by industry and business.– List of identified problems to close the gap between

industry/business and academia.


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Management Management ApproachApproach

Management Management ApproachApproach

Statistical Statistical MethodMethod

Statistical Statistical MethodMethod

Quality by DesignDesigned Experiments

and Reliability

Process Control & Process

Improvement

Control Charts

Inspection Sampling Plans

Fire FightingBasic

Statistical Thinking

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““At Motorola we use statistical methods daily At Motorola we use statistical methods daily throughout all of our disciplines to synthesize an throughout all of our disciplines to synthesize an abundance of data to derive concrete actions….abundance of data to derive concrete actions….How has the use of statistical methods within How has the use of statistical methods within Motorola Six Sigma initiative, across disciplines, Motorola Six Sigma initiative, across disciplines, contributed to our growth? Over the past decade we contributed to our growth? Over the past decade we have reduced in-process defects by over 300 fold, have reduced in-process defects by over 300 fold, which has resulted in a cumulative manufacturing which has resulted in a cumulative manufacturing cost savings of over 11 billion dollars”*.cost savings of over 11 billion dollars”*.

““At Motorola we use statistical methods daily At Motorola we use statistical methods daily throughout all of our disciplines to synthesize an throughout all of our disciplines to synthesize an abundance of data to derive concrete actions….abundance of data to derive concrete actions….How has the use of statistical methods within How has the use of statistical methods within Motorola Six Sigma initiative, across disciplines, Motorola Six Sigma initiative, across disciplines, contributed to our growth? Over the past decade we contributed to our growth? Over the past decade we have reduced in-process defects by over 300 fold, have reduced in-process defects by over 300 fold, which has resulted in a cumulative manufacturing which has resulted in a cumulative manufacturing cost savings of over 11 billion dollars”*.cost savings of over 11 billion dollars”*.

Robert W. GalvinChairman of the Executive Committee

Motorola, Inc.*From the forward to MODERN INDUSTRIAL STATISTICS by Kenett and Zacks, Duxbury, 1998*From the forward to MODERN INDUSTRIAL STATISTICS by Kenett and Zacks, Duxbury, 1998

Ron Kenett (KPAKPA Ltd.)

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Six Sigma Project Review Form

Black Belt Candidate: Date: 1 3 4 5

Project Name: Review er:

Six Sigma Black Belt Methodology Phases

Com

ple

ted

Incom

ple

te

Not sta

rted

N / A for

pro

ject

Action Items/Comments

A. MEASUREMENT

A1Problem identif ication. Key product/process selected, based on

business impact (DPU, Yield, COPQ, etc)3 2 1

A2 Project Customer, Mission, goals, metrics, client, measures of success established.

3 2 1

A3 Team members identif ied. 3 2 1

A4 Cashable return for Kodak identif ied (Return on investment) 3 2 1

A5 Potential barriers identif ied and listed. 3 2 1

Items above (A1-A5) should be complete by Week 1 review

A6 Team formed and fully functional 3 2 1

A7Project Baseline elements completed including scope, scale, analysis of

defects, cycle time, and costs3 2 1

A8 VOC collected, refined, and documented. 3 2 1

A9 Internal and external gaps identif ied through benchmarking 3 2 1

A10Detailed process map documented (inputs, outputs, product/ process

parameters, parameters classif ied, measurement points).3 2 1

A11Performance (key) parameters measured using basic Quality tools, basic

statistics, and Six Sigma measures3 2 1

A12Project Management plan established including milestone dates and

critical path3 2 1

Items above (A1-A12) should be complete by Week 3 review

B. ANALYSIS

B1Process/product data analyzed using control charts and other tools to

determine stability, capability, variability and process limits3 2 1

B2Failure Modes and Effects Analysis performed using identif ied steps

from product/process map.3 2 1 N/A

B3 Function Anaylsis Based Process Verif ication performed. 3 2 1 N/A

B4Systems Thinking tools applied (Reality Trees, Causal Loop Diagrams,

etc.).3 2 1 N/A

B5Key parameters prioritized based on capability analysis, defect pareto,

cost analysis, FMEA, FAB-PV, Value Analysis, etc.3 2 1

B6Measurement System Analysis performed on key measurement

processes (key parameters)3 2 1

B7"Measurement" phase elements updated (contract, baseline, metrics,

f low maps, etc.).3 2 1

B8Project Management plan updated w ith proposed improvement strategy

including milestone dates and critical path3 2 1

Items above (A and B) should be complete by Week 4 review

C. IMPROVEMENT

C1Key parameters selected for improvement. Response variables

documented.3 2 1

C2 Diagnostic studies completed (modeling, nested designs) 3 2 1

C3 Causal factor identif ication completed. Generate potential solutions. 3 2 1

C4Factor levels established, design selected and factors loaded, DOE plan

established3 2 1 N/A

C5 Experiment(s) conducted and data collected. 3 2 1 N/A

C6 DOE analysis. 3 2 1 N/A

C7 Select and test solution(s). Decision and risk analysis assessed. 3 2 1

C8 Implement solution(s). 3 2 1

C9"Measurement" phase elements updated (contract, baseline, metrics,

f low maps, etc.).3 2 1

Six Sigma project roadmapSix Sigma project roadmapSix Sigma project roadmapSix Sigma project roadmap

DEFINEDEFINE

MEASUREMEASURE

ANALYZEANALYZE

IMPROVEIMPROVE

CONTROLCONTROLwww.kpa.co.ilwww.kpa.co.il


Technical Technical SkillsSkills

Soft SkillsSoft Skills

StatisticiansStatisticians

Industrial Industrial EngineersEngineers

Master Master Black BeltsBlack Belts

Black BeltsBlack Belts

Quality Improvement Quality Improvement FacilitatorsFacilitators

BBBBBBBB

MBBMBB

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R&DR&DEngr.Engr.

ProductionProductionPurchasingPurchasing

Cust. SupportCust. Support

R&DR&DEngr.Engr.

ProductionProductionPurchasingPurchasing

Cust. SupportCust. Support

IdeaIdeaIdeaIdea ProductProductProductProduct

Reqts.Reqts. Spec.Spec.Product andProduct and

Process DesignProcess Design

Industrial StatisticsQuality Management

Industrial StatisticsQuality Management

Market Market ResearcResearc

hh

ProductProductEvaluatioEvaluatio

nn

ProductProductEvaluatioEvaluatio

nn

Satisfaction Satisfaction SurveysSurveys

Satisfaction Satisfaction SurveysSurveysProcess Process

ImprovementsImprovementsProcess Process

ImprovementsImprovements

www.kpa.co.ilwww.kpa.co.il


21/6/2002 37



"A Test for Detecting Outlying Cells in the Multinomial Distribution and Two-Way Contingency Tables", R. Kenett and C. Fuchs, Journal of the American Statistical Association , 75, pp. 395-398, 1980.

"Some Experiences Teaching Factorial Designs in Introductory Statistics

Courses", R. Kenett and D. Steinberg), Journal of Applied Statistics, 14, pp. 219-228, 1987.

"Two Methods for Comparing Pareto Charts", R. Kenett, Journal of Quality Technology, 23, pp. 27-31, 1991.

"Going Beyond Main-Effect Plots", R. Kenett and B. Vogel, Quality Progress, pp. 71-73, February 1991.

"Making Sense Out of Two Pareto Charts", R. Kenett, Quality Progress, pp. 71-74, May 1994.

Modern Industrial Statistics: Design and Control of Quality and Reliability ,R. Kenett and S. Zacks, Duxbury Press, San Francisco, 1998.

References

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My email:

[email protected]

Our website:

www.kpa.co.il

My email:

[email protected]

Our website:

www.kpa.co.il


21/6/2002 39



Pro-Enbis Acknowledgement

All joint authors - presenters - are members of:

Pro-Enbis and ENBIS.

This presentation is supported by Pro-Enbis a Thematic Network funded under the ‘Growth’ programme of the European Commission’s 5th Framework research programme - contract number G6RT-CT-2001-05059

All joint authors - presenters - are members of:

Pro-Enbis and ENBIS.

This presentation is supported by Pro-Enbis a Thematic Network funded under the ‘Growth’ programme of the European Commission’s 5th Framework research programme - contract number G6RT-CT-2001-05059

Documents

Siemens Electric Heating AS Bratsbergvegan 5 N-7493 TRONDHEIM Norway 21/6/2002