Professor for a Day for Dr. Chang Quality Control and Industrial Statistics College of Engineering University of Missour

1. Professor for a Dayfor Dr. ChangQuality Control and Industrial StatisticsCollege of EngineeringUniversity of MissouriMarch 13, 2013 By John A. Conte, P.E.

2. Objectives • Share my excitement to be here! • Students, faculty, engineers • Share my engineering career • Graduate of Mizzou • Quality and Reliability engineering • Semi-retirement • Share my thoughts on Six Sigma • As a Body of Knowledge • As a Process Improvement Methodology • As a Business Metric

3. How Did I Get Here? • Graduated from Grandview HS, MO 1962 • Graduated from University of Missouri with BSIE in 1966 • Winner of IIE technical writing contest 1965 • Lived in Kansas City, Denver, Dallas • Worked for AT&T Western Electric for 25 years • Worked for DSC Communications for 10 years • ASQ CQE and SSBB Exam Prep Instructor for past 10 years • Met John Drage, campus pastor of the Mizzou Rock 2007 • May 2008 responded to “my story” request • August 2008 presented Engineering Seminar • Professor for a Day Dr. Chang’s class in March 2011 and 2012

4. Most valuable course • The most valuable course during my four years here was “Quality Control and Industrial Statistics” • Lead to my job with AT&T Western Electric • Served me the first 15 years at AT&T • The basis for 20 years of using Bayesian Metrics • The focus for the courses I currently teach • ASQ CQE Exam Preparation • ASQ BB Quality Engineering Statistics • Villanova University Lean Six Sigma MBB (on-line)

5. September 1962 Defoe Hall McNair House

6. Some differences then and now • Cost of things • A year of college • Books • cars • ROTC and the Draft • Women in the College of Engineering • Women on campus (dress code, hours, PDA) • Grade points, negative hours, total hours

10. Where’s John Conte?1966 Savitar – AIIE Student Chapter

11. Job Offer upon graduation • In an interview I was told “I am sorry but we do not have any current openings for an industrial engineer but we do have an opening for a quality engineer. I see from your college transcript that you have taken a course entitled Quality Control and Industrial Statistics. Would you like to work for us as a Quality Control Engineer?”

12. 35 Years in Quality Engineering • AT&T Western Electric (25 years) • Shop Floor Statistical Process Control • AT&T Bell Labs QAC Information Systems Engineer • Nationwide Quality Information System (60 locations) • Unix based, reporting graphics, using networked computers • Bayesian Assessments • DSC Communications (10 years) • Quality Information Systems Manager • Corporate Quality Information Systems • Bayesian Assessments • Reliability Reporting using Bayesian Assessments

13. Semi-Retirement • Courses Taught for the American Society for Quality • ASQ CQE Exam Preparation • Six Sigma Engineering Statistics • Statistical Process Control • Introduction to Quality Engineering • CQPA, CQI, CSSGB Exam Preparation • Website www.contesolutions.com • Published Papers on Bayesian Metrics • Teach on-line course SS MBB for Villanova University

14. What is Six Sigma? • Body of Knowledge (BoK) • Process Improvement Methodology • Business Metric

15. Six Sigma as a BOK • American Society for Quality www.asq.org • www.isixsigma.com • www.sixsigmacouncil.org • www.iassc.org • Various levels (Belts) • SS Yellow Belt • SS Green Belt • SS Black Belt • SS Master Black Belt

16. Testing to the BoK example • American Society for Quality • Green Belt, Black Belt, and Master Black Belt Exams • Black Belt is 4 hours • With 150 questions (open book) • Multiple choice

17. Six Sigma as a BOK • Quality Engineering without using the words Quality or Engineering • DMAIC - A defined methodology for Process Improvement • Define phase • Measure phase • Analyze phase • Improve phase • Control phase • Project selection, initiation, and completion

18. Enterprise-Wide Deployment (9 Questions) • Enterprise-wide view • History of continuous improvement • Value and foundations of Six Sigma and Lean • Enterprise leadership responsibilities • Organizational roadblocks • Change management • Six Sigma projects and Kaizen events • Six Sigma roles and responsibilities • Impact on stakeholders • Benchmarking • Business performance and Financial measures

19. Team Management [16 Questions] • Team formation • Team facilitation and dynamics • Time management for teams • Team decision-making tools • Management and planning tools • Team performance evaluation and reward • Management and planning tools • Team performance evaluation and reward

20. Define [15 Questions] • Voice of the customer • Customer identification • Customer feedback • Customer requirements • Project charter • Problem statement • Project scope • Goals and objectives • Project performance measures • Project tracking

21. Measure [26 Questions] • Process characteristics • Input and output variables • Process flow metrics • Process analysis tools • Data collection • Types of data • Measurement scales • Sampling methods • Collecting data

22. Measure [26 Questions] continued • Measurement systems • Measurement methods • Measurement systems analysis • Metrology • Basic statistics • Central limit theorem • Descriptive statistics • Graphical methods • Valid statistical conclusions

23. Measure [26 Questions] continued • Probability • Basic concepts • Commonly used distributions • Process capability • Process capability indices • Process performance indices • Process capability studies

24. Analyze [24 Questions] • Measuring and modeling relationships between variables • Correlation coefficient • Regression • Multivariate tools • Attributes data analysis

25. Analyze [24 Questions] continued • Hypothesis testing • Terminology • Statistical vs. practical significance • Sample size • Point and interval estimates • Tests for means, variances and proportions • Analysis of variance (ANOVA) • Goodness-of-fit (chi square) tests • Contingency tables

26. Analyze [24 Questions] • Failure mode and effects analysis (FMEA) • Additional analysis methods • Gap analysis • Root cause analysis • Waste analysis

27. Improve [23 Questions] • Design of experiments (DOE) • Terminology • Design principles • Planning experiments • One-factor experiments • Two-level fractional factorial experiments • Full factorial experiments • Waste elimination • Cycle-time reduction • Kaizen and kaizen blitz • Risk analysis and mitigation

28. Control [21 Questions] • Statistical process control (SPC) • Objectives • Selection of variables • Rational subgrouping • Control chart selection • Control chart analysis • Other control tools • Total productive maintenance (TPM) • Visual factory • Maintain controls • Measurement system re-analysis • Control plan

29. Control [21 Questions] continued • Sustain improvements • Lessons learned • Training plan deployment • Documentation • Ongoing evaluation

30. Design for SS Methodologies [7 Questions] • Common DFSS methodologies • DMADV (define, measure, analyze, design and validate) • DMADOV (define, measure, analyze, design, optimize and validate) • Design for X (DFX) • Robust design and process • Special design tools • Strategic • Tactical

31. Six Sigma as a Methodology • Is it different from Quality Engineering? • DMAIC • Define • Measure • Analyze • Improve • Control • Project Champion, Project Management • Team Approach • Documentation of Phases • Focus on Minimizing Variation • Test of Hypothesis

32. Juran and Six Sigma

34. Process Excellence:“A path to a higher performing organization” Define Tollgate Review Project Name: Review Date:

35. Identify and Implement Quick Improvements with Kaizen Kaizen, 5S, NVA Analysis, Generic Pull Systems, Four Step Rapid Setup Method Lean Six SigmaDMAIC Improvement Process Road Map Define Measure Analyze Improve Control Activities Tools • Review Project Charter • Validate Problem Statement and Goals • Validate Voice of the Customer and Voice of the Business • Validate Financial Benefits • Validate High-Level Value Stream Map and Scope • Create Communication Plan • Select and Launch Team • Develop Project Schedule • Complete Define Gate • Project Charter • Voice of the Customer and Kano Analysis • SIPOC Map • Project Valuation/ROIC Analysis Tools • RACI and Quad Charts • Stakeholder Analysis • Communication Plan • Effective Meeting Tools • Inquiry and Advocacy Skills • Time Lines, Milestones, and Gantt Charting • Pareto Analysis • Belbin Analysis

36. Charter Summary Brief Project Desc.-Problem Statement Business Impact • Customer Impact: The automatch rate for SBG is low & many of the receivers remain unmatched until the merchandise accounting group becomes involved to find the reason, as well as many of the unmatched invoices that need a POD or a PO to match. • This issue causes many hours of manual work, late payments to vendors and results in a large balance sheet accrual. • Strategic Links: List project’s strategic links • Estimated Annual Benefits: List annualized dollar savings for the project • Savings Re-Invested - TBD Problem: SBG processed X orders for Staples product YTD P10’07 for $x. The automatch rate for these orders was x% vs a company average of x%. The low automatch rate results in xhours of manual work to match orders and invoices on both merchandise accounting and A/P associates as well late vendor payments Scope: List starting/end point of project focus Goals: Improve the automatch rate from x% to x% of SBG internal vendor and 3rd party SBG vendor and in turn reduce the manual labor hours necessary to match the UMR’s and UMI’s. Core Team/Stakeholders Tollgate Review Schedule

37. SIPOC Map Suppliers Inputs Process Outputs Customers Start Step1 Step 2 Step 3 Step 4 • ? • ? • ? • ? • ? • ? • ? • ? • ? • ? • ? • ? Stop Step 8 Step 7 Step 6 Step 5 Input Metrics Process Metrics Output Metrics • ? • ? • ? • ? • ? • ? • ? • ? • ? Quality • ? • ? • ? • ? • ? • ? • ? • ? • ? Speed • ? • ? • ? • ? • ? • ? Cost • ? • ? • ?

38. Voice of Customer/Business (VOC/VOB) Voice of Customer Input Key Customer Issue Customer Requirement

39. Audience Media Purpose Topics of Discussion/ Key Messages Owner Frequency Notes/Status Communication Plan

40. RACI Chart

41. Current Status • Key actions completed • Issues • Lessons learned • Communications, team building, organizational activities

42. Next Steps • Key actions planned • Planned Six Sigma tool use • Questions to answer

43. Define Tollgate Authorization • The scope is well-defined and mapped with a high-level process map or SIPOC map • The project team has been identified and launched, with clear expectations for all members • All aspects of the Project Charter have been validated, including: • Financial benefits have been estimated • Project timeline is achievable • The Opportunity/Problem Statement clearly identifies the process performance metrics or the Y • The Goal Statement focuses on the performance metrics or the Y and the goals are realistic • VOC and VOB Requirements have been gathered that validate • A Stakeholder Analysis and Communication plan have been completed • Potential Project risks have been identified and documented

44. Deliverable Map

45. Six Sigma as a Metric • A z-score is nothing more than a distance measure - in all cases it represents the number of standard deviations between the mean of the data set and some target value or point of interest. • If the point of interest is the nearest specification limit, the z score can be called a Sigma level!

46. Six Sigma and PPM defects or failures • Sigma level to PPM failures without 1.5 sigma shift • Sigma Level 1.00 ------- 317,300 • Sigma Level 2.00 -------- 45,500 • Sigma Level 3.00 -------- 2,700 • Sigma Level 4.00 --------- 63 • Sigma Level 4.50 ----------3.4 • Sigma Level 5.00 --------- 0.6 • Sigma Level 6.00 --------- 0.002

47. The Basis of Six Sigma Metric • A defined and stable process • Data to compute a process average • Data to compute process standard deviation • A specification or goal (nearest, if two sided)

48. Question for Practicing Black Belts • How many processes have you defined, collected enough data to estimate a process average and process standard deviation, and have established specification limits? • 0, 1, 3, 20, 300, 1000+ ? • What is your definition of “defined”? • How much data was collected for your process average? • How current is the estimate of the process average? • How did you determine your specifications? • What is the sigma level for each process? • What is your average sigma level? • What is your average PPM failure rate?

49. Sigma level = (nearest Spec limit – process mean) / process standard deviation