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6 sigma what is it

Six Sigma is a data-driven approach to process improvement that aims to reduce defects. It uses statistical methods and a structured strategy to identify and eliminate sources of errors and variation in manufacturing and business processes. The document discusses Six Sigma's scientific and practical approach, how it has been successfully implemented by companies like GE and Motorola to significantly reduce costs and improve quality, and barriers to its implementation.

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What is Six Sigma? Kingsley Nwagu University of Cumbria Feb 2012
Basics  A new way of doing business  Wise application of statistical tools within a structured methodology  Repeated application of strategy to individual projects  Projects selected that will have a substantial impact on the ‘bottom line’
A scientific and practical method to achieve improvements in a company Scientific: • Structured approach. • Assuming quantitative data. Practical: • Emphasis on financial result. • Start with the voice of the customer. “Show me the data” ”Show me the money” Six Sigma
Six Sigma Methods Production Design Service Purchase HRM Administration Quality Depart. Management M & S IT Where can Six Sigma be applied?
Knowledge Management The Six Sigma Initiative integrates these efforts
‘Six Sigma’ companies  Companies who have successfully adopted ‘Six Sigma’ strategies include:
GE “Service company” - examples  Approving a credit card application  Installing a turbine  Lending money  Servicing an aircraft engine  Answering a service call for an appliance  Underwriting an insurance policy  Developing software for a new CAT product  Overhauling a locomotive
“the most important initiative GE has ever undertaken”. Jack Welch Chief Executive Officer General Electric • In 1995 GE mandated each employee to work towards achieving 6 sigma • The average process at GE was 3 sigma in 1995 • In 1997 the average reached 3.5 sigma • GE’s goal was to reach 6 sigma by 2001 • Investments in 6 sigma training and projects reached 45MUS$ in 1998, profits increased by 1.2BUS$ General Electric
“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 cumulative manufacturing cost savings of over 11 billion dollars”*. Robert W. Galvin Chairman of the Executive Committee Motorola, Inc. MOTOROLA *From the forward to MODERN INDUSTRIAL STATISTICS by Kenett and Zacks, Duxbury, 1998
Positive quotations  “If you’re an average Black Belt, proponents say you’ll find ways to save $1 million each year”  “Raytheon figures it spends 25% of each sales dollar fixing problems when it operates at four sigma, a lower level of efficiency. But if it raises its quality and efficiency to Six Sigma, it would reduce spending on fixes to 1%”  “The plastics business, through rigorous Six Sigma process work , added 300 million pounds of new capacity (equivalent to a ‘free plant’), saved $400 million in investment and will save another $400 million by 2000”
Negative quotations  “Because managers’ bonuses are tied to Six Sigma savings, it causes them to fabricate results and savings turn out to be phantom”  “Marketing will always use the number that makes the company look best …Promises are made to potential customers around capability statistics that are not anchored in reality”  “ Six Sigma will eventually go the way of the other fads”
Barrier #1: Engineers and managers are not interested in mathematical statistics Barrier #2: Statisticians have problems communicating with managers and engineers Barrier #3: Non-statisticians experience “statistical anxiety” which has to be minimized before learning can take place Barrier # 4: Statistical methods need to be matched to management style and organizational culture Barriers to implementation
Technical Skills Soft Skills Statisticians Master Black Belts Black Belts Quality Improvement Facilitators BB MBB
Reality  Six Sigma through the correct application of statistical tools can reap a company enormous rewards that will have a positive effect for years or  Six Sigma can be a dismal failure if not used correctly  ISRU, CAMT and Sauer Danfoss will ensure the former occurs
Six Sigma  The precise definition of Six Sigma is not important; the content of the program is  A disciplined quantitative approach for improvement of defined metrics  Can be applied to all business processes, manufacturing, finance and services
Focus of Six Sigma* Accelerating fast breakthrough performance Significant financial results in 4-8 months Ensuring Six Sigma is an extension of the Corporate culture, not the program of the month Results first, then culture change! *Adapted from Zinkgraf (1999), Sigma Breakthrough Technologies Inc., Austin, TX.
Six Sigma: Reasons for Success The Success at Motorola, GE and AlliedSignal has been attributed to:  Strong leadership (Jack Welch, Larry Bossidy and Bob Galvin personally involved)  Initial focus on operations  Aggressive project selection (potential savings in cost of poor quality > $50,000/year)  Training the right people
The right way! Plan for “quick wins”  Find good initial projects - fast wins Establish resource structure  Make sure you know where it is Publicise success  Often and continually - blow that trumpet Embed the skills  Everyone owns successes
The Six Sigma metric
Consider a 99% quality level  5000 incorrect surgical operations per week!  200,000 wrong drug prescriptions per year!  2 crash landings at most major airports each day!  20,000 lost articles of mail per hour!
Not very satisfactory!  Companies should strive for ‘Six Sigma’ quality levels  A successful Six Sigma programme can measure and improve quality levels across all areas within a company to achieve ‘world class’ status  Six Sigma is a continuous improvement cycle
Scientific method (after Box) INDUCTION INDUCTION DEDUCTION DEDUCTION Data Facts Theory Hypothesis Conjecture Idea Model Check Plan DoAct
23 Improvement cycle  PDCA cycle Plan Do Check Act
Prioritise (D) Measure (M) Interpret (D/M/A) Problem (D/M/A) solve Improve (I) Hold gains (C) Alternative interpretation
Statistical background Target = m Some Key measure
+/- 3s Statistical background Target = m ‘Control’ limits
+/- 3s LSL USL Statistical background Required Tolerance Target = m
+/- 3s +/- 6s LSL USL Statistical background Tolerance Target = m Six-Sigma
+/- 3s +/- 6s LSL USL ppm 1350 ppm 1350 Statistical background Tolerance Target = m
+/- 3s +/- 6s LSL USL ppm 0.001 ppm 1350 ppm 1350 ppm 0.001 Statistical background Tolerance Target = m
Statistical background  Six-Sigma allows for un-foreseen ‘problems’ and longer term issues when calculating failure error or re-work rates Allows for a process ‘shift’
LSL 0 ppm ppm 3.4 1.5s USL ppm 3.4ppm 66803 m +/- 6s Statistical background Tolerance
Performance Standards 2 3 4 5 6 308537 66807 6210 233 3.4 s PPM 69.1% 93.3% 99.38% 99.977% 99.9997% Yield Process performance Defects per million Long term yield Current standard World Class
Number of processes 3σ 4σ 5σ 6σ 1 10 100 500 1000 2000 2955 93.32 50.09 0.1 0 0 0 0 99.379 93.96 53.64 4.44 0.2 0 0 99.9767 99.77 97.70 89.02 79.24 62.75 50.27 99.99966 99.9966 99.966 99.83 99.66 99.32 99.0 First Time Yield in multiple stage process Performance standards
Benefits of 6s approach w.r.t. financials s-level Defect rate (ppm) Costs of poor quality Status of the company 6 3.4 < 10% of turnover World class 5 233 10-15% of turnover 4 6210 15-20% of turnover Current standard 3 66807 20-30% of turnover 2 308537 30-40% of turnover Bankruptcy Financial Aspects
Six Sigma and other Quality programmes
Comparing three recent developments in “Quality Management”  ISO 9000 (-2000)  EFQM Model  Quality Improvement and Six Sigma Programs
ISO 9000  Proponents claim that ISO 9000 is a general system for Quality Management In fact the application seems to involve  an excessive emphasis on Quality Assurance, and  standardization of already existing systems with little attention to Quality Improvement  It would have been better if improvement efforts had preceded standardization
Critique of ISO 9000  Bureaucratic, large scale  Focus on satisfying auditors, not customers  Certification is the goal; the job is done when certified  Little emphasis on improvement  The return on investment is not transparent  Main driver is:  We need ISO 9000 to become a certified supplier,  Not “we need to be the best and most cost effective supplier to win our customer’s business”  Corrupting influence on the quality profession
EFQM Model  A tool for assessment: Can measure where we are and how well we are doing  Assessment is a small piece of the bigger scheme of Quality Management:  Planning  Control  Improvement  EFQM provides a tool for assessment, but no tools, training, concepts and managerial approaches for improvement and planning
The “Success” of Change Programs? “Performance improvement efforts … have as much impact on operational and financial results as a ceremonial rain dance has on the weather” Schaffer and Thomson, Harvard Business Review (1992)
Change Management: Two Alternative Approaches Activity Centered Programs Result Oriented Programs Change Management Reference: Schaffer and Thomson, HBR, Jan-Feb. 1992
Activity Centered Programs  Activity Centered Programs: The pursuit of activities that sound good, but contribute little to the bottom line  Assumption: If we carry out enough of the “right” activities, performance improvements will follow  This many people have been trained  This many companies have been certified  Bias Towards Orthodoxy: Weak or no empirical evidence to assess the relationship between efforts and results
No Checking with Empirical Evidence, No Learning Process ISO 9000 Data Hypothesis Deduction Induction
An Alternative: Result-Driven Improvement Programs  Result-Driven Programs: Focus on achieving specific, measurable, operational improvements within a few months  Examples of specific measurable goals:  Increase yield  Reduce delivery time  Increase inventory turns  Improved customer satisfaction  Reduce product development time
Result Oriented Programs  Project based  Experimental  Guided by empirical evidence  Measurable results  Easier to assess cause and effect  Cascading strategy
Why Transformation Efforts Fail!  John Kotter, Professor, Harvard Business School  Leading scholar on Change Management  Lists 8 common errors in managing change, two of which are: • Not establishing a sense of urgency • Not systematically planning for and creating short term wins
Six Sigma Demystified* Six Sigma is TQM in disguise, but this time the focus is:  Alignment of customers, strategy, process and people  Significant measurable business results  Large scale deployment of advanced quality and statistical tools  Data based, quantitative *Adapted from Zinkgraf (1999), Sigma Breakthrough Technologies Inc., Austin, TX.
Keys to Success*  Set clear expectations for results  Measure the progress (metrics)  Manage for results *Adapted from Zinkgraf (1999), Sigma Breakthrough Technologies Inc., Austin, TX.
Key personnel in successful Six Sigma programmes
Black Belts  Six Sigma practitioners who are employed by the company using the Six Sigma methodology  work full time on the implementation of problem solving & statistical techniques through projects selected on business needs  become recognised ‘Black Belts’ after embarking on Six Sigma training programme and completion of at least two projects which have a significant impact on the ‘bottom-line’
Black Belt required resources -Training in statistical methods. -Time to conduct the project! -Software to facilitate data analysis. -Permissions to make required changes!! -Coaching by a champion – or external support. Black Belt requirements
In other words the Black Belt is -Empowered. -In the sense that it was always meant! -As the theroists have been saying for years! Black Belt role!
Champions or ‘enablers’  High-level managers who champion Six Sigma projects  they have direct support from an executive management committee  orchestrate the work of Six Sigma Black Belts  provide Black Belts with the necessary backing at the executive level
Further down the line - after initial Six Sigma implementation package  Master Black Belts  Black Belts who have reached an acquired level of statistical and technical competence  Provide expert advice to Black Belts  Green Belts  Provide assistance to Black Belts in Six Sigma projects  Undergo only two weeks of statistical and problem solving training
Six Sigma instructors (ISRU)  Aim: Successfully integrate the Six Sigma methodology into a company’s existing culture and working practices  Key traits  Knowledge of statistical techniques  Ability to manage projects and reach closure  High level of analytical skills  Ability to train, facilitate and lead teams to success, ‘soft skills’
Six Sigma training package
Aim of training package To successfully integrate Six Sigma methodology into Sauer Danfoss’ culture and attain significant improvements in quality, service and operational performance
DMAIC Define Select a project Measure Prepare for assimilating information Analyze Characterise the current situation Improve Optimize the process Control Assure the improvements Six-Sigma - A “Roadmap” for improvement
Training (1 week) Work on project (3 weeks) Review Define Measure Analyze Improve Control Throughput time project 4 months (full time) Example of a Classic Training strategy
ISRU program content  Week 1 - Six Sigma introductory week (Deployment phase)  Weeks 2-5 - Main Black Belt training programme  Week 2 - Measurement phase  Week 3 - Analysis phase  Week 4 - Improve phase  Week 5 - Control phase  Project support for Six Sigma Black Belt candidates  Access to ISRU’s distance learning facility
Draft training schedule No. Black Belt work package tasks Start End Duration Jan 2003 Feb 2003 Mar 2003 Apr 2003 May 2003 Jun 2003 Jul 2003 1/5 1/12 1/19 1/26 2/2 2/9 2/16 2/23 3/2 3/9 3/16 3/23 3/30 4/6 4/13 4/20 4/27 5/4 5/11 5/18 5/25 6/1 6/8 6/15 6/22 6/29 7/6 7/13 7/20 7/27 1 1d03/02/0303/02/03Champions Day 2 3d06/02/0304/02/03Intial 3-day Black belt sessions 3 1d07/02/0307/02/03Administration Day 5 1w21/02/0317/02/03 Black Belt training (Measurement phase) 12 2d30/07/0329/07/03Project support (Follow up) 7 1w18/04/0314/04/03Black Belt training (Analysis phase) 9 11 1w30/05/0326/05/03Black Belt training (Improvement phase) 1w11/07/0307/07/03Black Belt training (Control phase) 6 1d25/03/0325/03/03Project support (Workshop2) 8 1d06/05/0306/05/03Project support (Workshop 3) 4 1d11/02/0311/02/03Project support (Workshop 1) 10 1d17/06/0317/06/03Project support (Workshop 4)
Training programme delivery  Lectures supported by appropriate technology  Video case studies  Games and simulations  Experiments and workshops  Exercises  Defined projects  Delegate presentations  Homework!
Measure Analyze Improve Control Define 5 weeks of training
Deployment (Define) phase  Topics covered include  Team Roles  Presentation skills  Project management skills  Group techniques  Quality  Pitfalls to Quality Improvement projects  Project strategies  Minitab introduction
Measurement phase Topics covered include:  Quality Tools  Risk Assessment  Measurements  Capability & Performance  Measurement Systems Analysis  Quality Function Deployment  FMEA
Example - QFD A method for meeting customer requirements Uses tools and techniques to set product strategies Displays requirements in matrix diagrams, including ‘House of Quality’ Produces design initiatives to satisfy customer and beat competitors
House Of Quality 6. Technical assessment and target values 1. Customer requirements 4. Relationship matrix 3. Product characteristics Importance 2. Competitive assessment 5. Tradeoff matrix
Lead-times - the time to market and time to stable production Start-up costs Engineering changes QFD can reduce
Analysis phase Topics include:  Hypothesis testing  Comparing samples  Confidence Intervals  Multi-Vari analysis  ANOVA (Analysis of Variance)  Regression
Improvement phase  Topics include:  History of Design of Experiments (DoE)  DoE Pre-planning and Factors  DoE Practical workshop  DoE Analysis  Response Surface Methodology (Optimisation)  Lean Manufacturing
Example - Design of Experiments What can it do for you? Minimum cost Maximum output
What does it involve? Brainstorming sessions to identify important factors Conducting a few experimental trials Recognising significant factors which influence a process Setting these factors to get maximum output
Control phase  Topics include:  Control charts  SPC case studies  EWMA  Poka-Yoke  5S  Reliability testing  Business impact assessment
Example - SPC (Statistical Process Control) - reduces variability and keeps the process stable Disturbed process Natural process Temporary upsets Natural boundary Natural boundary
Results of SPC An improvement in the process Reduction in variation Better control over process Provides practical experience of collecting useful information for analysis Hopefully some enthusiasm for measurement!
Project support  Initial ‘Black Belt’ projects will be considered in Week 1 by Executive management committee, ‘Champions’ and ‘Black Belt’ candidates  Projects will be advanced significantly during the training programme via:  continuous application of newly acquired statistical techniques  workshops and on-going support from ISRU and CAMT  delivery of regular project updates by ‘Black Belt’ candidates
Black Belt Training Application Review ISRU ISRU, Champion ISRU, Champion Project execution
Traditional Six Sigma -Project leader is obliged to make an effort. -Set of tools. -Focus on technical knowledge. -Project leader is left to his own devices. -Results are fuzzy. -Safe targets. -Projects conducted “on the side”. -Black Belt is obliged to achieve financial results. -Well-structured method. -Focus on experimentation. -Black Belt is coached by champion. -Results are quantified. -Stretched targets. -Projects are top priority. Conducting projects
The right support + The right projects + The right people + The right tools + The right plan = The right results
Champions Role • Communicate vision and progress • Facilitate selecting projects and people • Track the progress of Black Belts • Breakdown barriers for Black Belts • Create supporting systems
Champions Role • Measure and report Business Impact • Lead projects overall • Overcome resistance to Change • Encourage others to Follow
Define Select: - the project - the process - the Black Belt - the potential savings - time schedule - team Project selection
Projects may be selected according to: 1. A complete list of requirements of customers. 2. A complete list of costs of poor quality. 3. A complete list of existing problems or targets. 4. Any sensible meaningful criteria 5. Usually improves bottom line - but exceptions Project selection
Key Quality Characteristics “CTQs” How will you measure them? How often? Who will measure? Is the outcome critical or important to results?
Outcome Examples Reduce defective parts per million Increased capacity or yield Improved quality Reduced re-work or scrap Faster throughput
Key Questions Is this a new product - process? Yes - then potential six-sigma Do you know how best to run a process? No - then potential six-sigma
Key Criteria Is the potential gain enough - e.g. - saving > $50,000 per annum? Can you do this within 3-4 months? Will results be usable? Is this the most important issue at the moment?
Why is ISRU an effective Six Sigma practitioner?
Because we are experts in the application of industrial statistics and managing the accompanying change We want to assist companies in improving performance thus helping companies to greater success We will act as mentors to staff embarking on Six Sigma programmes Reasons
INDUSTRIAL STATISTICS RESEARCH UNIT We are based in the School of Mechanical and Systems Engineering, University of Newcastle upon Tyne, England
Mission statement "To promote the effective and widespread use of statistical methods throughout European industry."
The work we do can be broken down into 3 main categories:  Consultancy  Training  Major Research Projects All with the common goal of promoting quality improvement by implementing statistical techniques
Consultancy We have long term one to one consultancies with large and small companies, e.g. Transco Prescription Pricing Agency Silverlink To name but a few
Training In-House courses  SPC  QFD  Design of Experiments  Measurement Systems Analysis On-Site courses  As above, tailored courses to suit the company  Six Sigma programmes
European projects  The Unit has provided the statistical input into many major European projects Examples include -  Use of sensory panels to assess butter quality  Using water pressures to detect leaks  Assessing steel rail reliability  Testing fire-fighter’s boots for safety
European projects  Eurostat - investigating the multi-dimensional aspects of innovation using the Community Innovation Survey (CIS) II - 17 major European countries involved - determining the factors that influence innovation  Certified Reference materials for assessing water quality - validating EC Laboratories  New project - ‘Effect on food of the taints and odours in packaging materials’
Typical local projects  Assessment of environmental risks in chemical and process industries  Introduction of statistical process control (SPC) into a micro-electronics company  Helping to develop a new catheter for open-heart surgery via designed experiments (DoE)  ‘Restaurant of the Year’ & ‘Pub of the Year’ competitions!
Benefits Better monitoring of processes Better involvement of people Staff morale is raised Throughput is increased Profits go up
Examples of past successes Down time cut by 40% - Villa soft drinks Waste reduced by 50% - Many projects Stock holding levels halved - Many projects Material use optimised saving £150k pa - Boots Expensive equipment shown to be unnecessary - Wavin