Transcript No Slide Title

PRO-ENBIS: G6RT-CT2001-05059
ENBIS industrial visit
Siemens Electric Heating AS
Bratsbergvegan 5
N-7493
TRONDHEIM
Norway
21/6/2002
Tel No +47 73 95 90 00
21/6/2002
Siemens Electric Heating, Trondheim
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PRO-ENBIS: G6RT-CT2001-05059
Proposed agenda
E: Introduction of the team - 5 mins
E: Introduction to ENBIS - 10 mins
S: Introduction to Siemens Trondheim - 15 mins
E: SQM survey, Design of Experiments, 6-sigma - 45 mins
S: Topics to be covered in visit - 15 mins
On Site Visit - 45 mins
Discussions on opportunities - 30 mins
Conclusion - 15 mins
(S - Siemens, E - ENBIS team)
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PRO-ENBIS: G6RT-CT2001-05059
ENBIS team
Jon Tyssedal, [email protected]
Professor of Statistics, NTNU
Expert in Statistics
Maria Fernanda Ramalhoto, [email protected]
Professor of Statistics,Instituto Superior Tecnico, Lisbon
Expert in Reliability and Quality Improvement
Ron Kenett, [email protected]
International Management Consultant, CEO KPA Ltd.
Expert in Industrial Statistics and Quality Management
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PRO-ENBIS: G6RT-CT2001-05059
ENBIS team
Jon Tyssedal, [email protected]
Professor of Statistics, NTNU
Expert in Statistics
Maria Fernanda Ramalhoto, [email protected]
Professor of Statistics,Instituto Superior Tecnico, Lisbon
Expert in Reliability and Quality Improvement
Ron Kenett, [email protected]
International Management Consultant, CEO KPA Ltd.
Expert in Industrial Statistics and Quality Management
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PRO-ENBIS: G6RT-CT2001-05059
ENBIS team
Jon Tyssedal, [email protected]
Professor of Statistics, NTNU
Expert in Statistics
Maria Fernanda Ramalhoto, [email protected]
Professor of Statistics,Instituto Superior Tecnico, Lisbon
Expert in Reliability and Quality Improvement
Ron Kenett, [email protected]
International Management Consultant, CEO KPA Ltd.
Expert in Industrial Statistics and Quality Management
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PRO-ENBIS: G6RT-CT2001-05059
Ron Kenett (25 yrs of experience, 4 books)
Industrial Statistics
Organizational
effectiveness
Multivariate Quality Control
Six Sigma
SPC
Internet Surveys
Design of
Experiments
Software Process Quality
Management
Dashboards
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PRO-ENBIS: G6RT-CT2001-05059
Introduction to ENBIS
ENBIS
European Network for Business and Industrial Statistics
www.enbis.org
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PRO-ENBIS: G6RT-CT2001-05059
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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PRO-ENBIS: G6RT-CT2001-05059
ENBIS Vision
- 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
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PRO-ENBIS: G6RT-CT2001-05059
ENBIS Vision – continued
- 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
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PRO-ENBIS: G6RT-CT2001-05059
ENBIS History
August 21, 1999, Linköping, Sweden
During the first International Symposium on Industrial
Statistics, some 20 statisticians and practitioners agreed to
push forward a European society for industrial statistics.
Febr. 26-27, 2000, Eindhoven, NL
Meeting of the provisional executive committee. The name
ENBIS was chosen for the new network.
December 11, 2000, Amsterdam, NL
More than 80 persons participated in the founding
conference.
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PRO-ENBIS: G6RT-CT2001-05059
ENBIS Organization
-
21/6/2002
Administration
General assembly
Council
Executive committee
Permanent office (Amsterdam)
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PRO-ENBIS: G6RT-CT2001-05059
ENBIS Organization
Working groups
-
Design of experiments
- Process modelling and
Reliability and safety
control
Data mining / warehousing
- Quality improvement
General statistical modelling - Statistical consultancy
Local networks
- bENBIS (Belgium)
- nENBIS (Netherlands)
- iENBIS (Israel)
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PRO-ENBIS: G6RT-CT2001-05059
ENBIS Organization
Members
- No membership fee (for the time being)
- 560 members (May, 2002)
Corporate Members
- 500 Euros per annum
- 7 Corporate members (May, 2002)
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PRO-ENBIS: G6RT-CT2001-05059
ENBIS Membership benefits
ENBIS offers its members:
-Network facilities
-Conferences
-Courses
-Thematic network Pro-ENBIS
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PRO-ENBIS: G6RT-CT2001-05059
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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PRO-ENBIS: G6RT-CT2001-05059
www.enbis.org
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PRO-ENBIS: G6RT-CT2001-05059
ENBIS Conferences
December 11, 2000, Amsterdam, NL
Founding conference
80 participants
September 17-18, 2001, Oslo, Norway
First Annual Meeting on Business and Industrial Statistics
101 participants
43 submitted abstracts
September 23-24, 2002, Rimini, Italy
Second Annual Meeting on Business and Industrial Statistics
105 submitted abstracts
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PRO-ENBIS: G6RT-CT2001-05059
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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PRO-ENBIS: G6RT-CT2001-05059
Pro-ENBIS
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
visits and publishing case-study based papers.
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PRO-ENBIS: G6RT-CT2001-05059
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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PRO-ENBIS: G6RT-CT2001-05059
Proposed agenda
E: Introduction of the team - 5 mins
E: Introduction to ENBIS - 10 mins
S: Introduction to Siemens Trondheim - 15 mins
E: SQM survey, Design of Experiments, 6-sigma - 45 mins
S: Topics to be covered in visit - 15 mins
On Site Visit - 45 mins
Discussions on opportunities - 30 mins
Conclusion - 15 mins
(S - Siemens, E - ENBIS team)
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PRO-ENBIS: G6RT-CT2001-05059
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”.
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SQM Survey
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PRO-ENBIS: G6RT-CT2001-05059
Workshops, Round Tables

Claims from industry
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SQM Survey
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PRO-ENBIS: G6RT-CT2001-05059
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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SQM Survey
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PRO-ENBIS: G6RT-CT2001-05059
ESREL’2001 Round Table
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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SQM Survey
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PRO-ENBIS: G6RT-CT2001-05059
ESREL’2001 Round Table
 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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SQM Survey
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PRO-ENBIS: G6RT-CT2001-05059
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-Nestlevery briefly mentioned and made available at
request.
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SQM Survey
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PRO-ENBIS: G6RT-CT2001-05059
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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SQM Survey
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PRO-ENBIS: G6RT-CT2001-05059
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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SQM Survey
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PRO-ENBIS: G6RT-CT2001-05059
Questionnaire (cont.)
7.
Use of Inventory Control/Supply Chain
Techniques.
8. Use of Data Quality Control
Techniques.
9. Use of Periodicals.
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SQM Survey
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PRO-ENBIS: G6RT-CT2001-05059
Questionnaire (cont.)
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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SQM Survey
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PRO-ENBIS: G6RT-CT2001-05059
Management
Approach
Quality by Design
Process Control
& Process
Improvement
Inspection
Fire Fighting
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Statistical
Method
Designed Experiments
and Reliability
Control Charts
Sampling Plans
Basic
Statistical Thinking
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PRO-ENBIS: G6RT-CT2001-05059
Ron Kenett (KPA Ltd.)
“At Motorola we use statistical methods daily
throughout all of our disciplines to synthesize an
abundance of data to derive concrete actions….
How has the use of statistical methods within
Motorola Six Sigma initiative, across disciplines,
contributed to our growth? Over the past decade we
have reduced in-process defects by over 300 fold,
which has resulted in a cumulative manufacturing
cost savings of over 11 billion dollars”*.
Robert W. Galvin
Chairman of the Executive Committee
Motorola, Inc.
*From the forward to MODERN INDUSTRIAL STATISTICS by Kenett and Zacks, Duxbury, 1998
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PRO-ENBIS: G6RT-CT2001-05059
Ron Kenett (KPA Ltd.)
Six Sigma Project Review Form
Six Sigma project roadmap
Black Belt Candidate:
Date:
N
/A for
project
Not started
Six Sigma Black Belt Methodology Phases
Incomplete
Review er:
Completed
Project Name:
Action Items/Comments
A. MEASUREMENT
A
Problem identif ication. Key product/process selected, based on
business impact (DPU, Yield, COPQ, etc)
A
Project Customer, Mission, goals, metrics, client, measures of success
established.
A
Team members identif ied.
A
Cashable return f or Kodak identif ied (Return on investment)
A
Potential barriers identif ied and listed.
Items above (A -A ) should be complete by Week
Statisticians
review
A
Team f ormed and f ully f unctional
A
Project Baseline elements completed including scope, scale, analysis of
def ects, cycle time, and costs
A
A
VOC collected, ref ined, and documented.
Technical
Skills
Internal and external gaps identif ied through benchmarking
A
Detailed process map documented (inputs, outputs, product/ process
parameters, parameters classif ied, measurement points).
A
Perf ormance (key) parameters measured using basic Quality tools , basic
statistics, and Six Sigma measures
A
Project Management plan established including milestone dates and
critical path
Items above (A -A
) should be complete by Week
DEFINE
Industrial
Engineers
BB
Master MBB
Black Belts
Black Belts
review
B. ANALYSIS
B
Process/product data analyzed using control charts and other tools to
determine stability, capability, variability and process limits
Failure Modes and Ef f ects Analysis perf ormed using identif ied steps
f rom product/process map.
N/A
B
Function Anaylsis Based Process Verif ication perf ormed.
N/A
B
Systems Thinking tools applied (Reality Trees, Causal Loop Diagrams,
etc.).
N/A
B
Key parameters prioritized based on capability analysis , def ect pareto,
cost analysis, FMEA, FAB-PV, Value Analysis, etc.
B
MEASURE
B
Measurement System Analysis perf ormed on key measurement
processes (key parameters)
B
"Measurement" phase elements updated (contract, baseline, metrics,
f low maps, etc.).
B
Project Management plan updated w ith proposed improvement strategy
including milestone dates and critical path
ANALYZE
Items above (A and B) should be complete by Week
C. IMPROVEMENT
C
review
Quality Improvement
Facilitators
Soft Skills
Key parameters selected f or improvement. Response variables
documented.
C
Diagnostic studies completed (modeling, nested designs)
C
Causal f actor identif ication completed. Generate potential solutions.
C
Factor levels established, design selected and f actors loaded, DOE plan
established
N/A
C
Experiment(s) conducted and data collected.
N/A
C
DOE analysis.
N/A
C
Select and test solution(s). Decision and risk analysis assessed.
IMPROVE
C
Implement solution(s).
C
"Measurement" phase elements updated (contract, baseline, metrics,
f low maps, etc.).
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CONTROL
Siemens Electric Heating, Trondheim
www.kpa.co.il
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PRO-ENBIS: G6RT-CT2001-05059
Ron Kenett (KPA Ltd.)
Market
Researc
h
Idea
Reqts.
R&D
Engr.
Production
Purchasing
Cust. Support
Product
Evaluatio
n
Product
Spec.
Product and
Process Design
Process
Improvements
Industrial Statistics
Quality Management
Satisfaction
Surveys
www.kpa.co.il
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PRO-ENBIS: G6RT-CT2001-05059
References
"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.
Siemens Electric Heating, Trondheim
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PRO-ENBIS: G6RT-CT2001-05059
Ron Kenett (KPA Ltd.)
My email:
[email protected]
Our website:
www.kpa.co.il
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PRO-ENBIS: G6RT-CT2001-05059
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
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