Six Sigma
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  • Companies with satisfied customers exhibit strong financial performance (positive correlation). In other words, knowing, and acting upon, customer requirements is profitable. The University of Michigan Business School’s National Quality Research Center has tracked the ACSI since 1994. ASCI does quarterly interviews with customers of over 200 companies in 35 industries. Customer Satisfaction scores are correlated positively with financial performance measures such as market value added, stock price, and ROI. Among the 73 companies surveyed, those that score in the top half of the ACSI score range generated about $42 bil in MVA, while companies in the bottom half totaled only $23 bil. Furthermore, in the companies surveyed with a mean capitalization of $27 bil, one point on the ASCI scale is worth on average $0.898 mil. in MVA and therefore a one point increase in customer satisfaction score translates into a 3% (0.9/27) increase in MVA. Sources: Claes Fornell, Harvard Business Review, 2001 and American Customer Satisfaction Index, University of Michigan.

Six Sigma Presentation Transcript

  • 1. Six Sigma Six Sigma: DMAIC; Y=f(x) Is it a Goal, a Measure, a Process, a Tool or an expletive deleted? By Lee Olson Presentation to INFORMS
  • 2. Objectives
    • Understand the Basics of the Six Sigma Program
    • Understand How Six Sigma Relates to Lean, TOC, TQM
      • (Theory Of Constraints; Total Quality Management)
    • Ability to Define a Strategy and Roadmap for Success
  • 3. Define
    • Is it a Goal, a Measure, a Process, a Tool or an expletive deleted?
    • Yes
  • 4. Define
    • Six Sigma
    • Is a management methodology
      • Customer focused
      • Data driven decisions
      • Breakthrough performance gains
      • Validated bottom line results
  • 5. Customer Focused Our Performance Compared to Competitors Importance to Customers We’re Better They’re Better High Moderate- to-’Low’
    • Price
    • Complaints
    • OTD
    • Quality
    • Training
    • Complete
    • Shared Goals
  • 6. Data Driven Decisions
    • Y
    • Dependent
    • Output
    • Effect
    • Symptom
    • Monitor
    • Response
    Why should we test or inspect Y, if we know this relationship?
    • X1 . . . XN
    • Independent
    • Input-Process
    • Cause
    • Problem
    • Control
    • Factor
    To get results, should we focus our behavior on the Y or X ? f (X) Y=
  • 7. Breakthrough performance gains Sigma is a statistical unit of measure which reflects process capability. The sigma scale of measure is perfectly correlated to such characteristics as defects-per-unit, parts-per million defective, and the probability of a failure/error. (Distribution Shifted ± 1.5  ) Process Capability Defects per Million Opportunities  PPM
  • 8. Validated bottom line results Impact on Bottom Line Assuming a 10% change in the factor Factors
  • 9. Define
    • Methodology
    • Define
    • Measure
    • Analyze
    • Improve
    • Control
  • 10. Roadmap Example Next Project Celebrate Project $
    • Define
      • Customers, Value, Problem Statement
      • Scope, Timeline, Team
      • Primary/Secondary & OpEx Metrics
      • Current Value Stream Map
      • Voice Of Customer (QFD)
    • Measure
      • Assess specification / Demand
      • Measurement Capability (Gage R&R)
      • Correct the measurement system
      • Process map, Spaghetti, Time obs.
      • Measure OVs & IVs / Queues
    • Analyze ( and fix the obvious)
      • Root Cause (Pareto, C&E, brainstorm)
      • Find all KPOVs & KPIVs
      • FMEA, DOE, critical Xs, VA/NVA
      • Graphical Analysis, ANOVA
      • Future Value Stream Map
    • Improve
      • Optimize KPOVs & test the KPIVs
      • Redesign process, set pacemaker
      • 5S, Cell design, MRS
      • Visual controls
      • Value Stream Plan
    • Control
      • Document process (WIs, Std Work)
      • Mistake proof, TT sheet, CI List
      • Analyze change in metrics
      • Value Stream Review
      • Prepare final report
    Validate Project $ Validate Project $ Validate Project $ Validate Project $
  • 11. PERFECTION Practical Solutions
    • Develop a focused Problem Statement and Objective
    • Develop a Process Map and/or FMEA
    • Develop a Current State Map
    • Identify the response variable(s) and how to measure them
    • Analyze measurement system capability
    • Assess the specification (Is one in place? Is it the right one?)
    MEASURE Practical Problem ANALYZE Problem Definition
    • Characterize the response, look at the raw data
      • Abnormal? Other Clues? Mean or Variance problem?
    • Time Observation • Spaghetti Diagram • Takt Time
    • Future State Maps • Percent Loading
    • Standard Work Combination
    • Use Graphical Analysis, Multi-Vari, ANOVA and basic statistical tools to identify the likely families of variability
    IMPROVE Problem Solution
    • Identify the likely X’s
    • 5S • Set Up Time Reduction (SMED)
    • Material Replenishment Systems
    • Level Loading / Line Leveling
    • Cell Design • Visual Controls
    • Use Design of Experiments to find the critical few X’s
    • Move the distribution; Shrink the spread; Confirm the results
    CONTROL Problem Control
    • Mistake Proof the process (Poka-Yoke)
    • Tolerance the process
    • Measure the final capability
    • Place appropriate process controls on the critical X’s
    • Document the effort and results
    • Standard Work • TPM
    DEFINE Identify Problem
    • Strategic Link to Business Plan defined in Project Selection Process
    • Defined Business Impact with Op Ex Champion support
    • Structured Brainstorming at all organizational levels
    • Cause and Effect Diagrams identifying critical factors
    • Primary and Secondary Metrics defined and charted
    • Multi-Level Pareto Charts to confirm project focus
    • What do you want to know?
    • How do you want to see what it is that you need to know?
    • What type of tool will generate what it is that you need to see?
    • What type of data is required of the selected tool?
    • Where can you get the required type of data?
    Problem Solving Plan Execute Execute Plan Crane Co. Op. Ex. Methodology Originated by MBBs; D. Braasch, J. Davis, R. Duggins, J. O’Callaghan, R. Underwood, I. Wilson Operational Excellence Methodology Based in part on Six Sigma Methodology developed by GE Medical Systems and Six Sigma Academy, Inc.
  • 12. Define Key Items
    • Customers, Value, Problem Statement
    • Scope, Timeline, Team
    • Primary/Secondary & OpEx Metrics
    • Current Value Stream Map
    • Voice Of Customer (QFD)
      • (Quality Function Deployment)
  • 13. Project Selection Impact
    • Business Impact
      • Revenue Growth
      • Cost Reduction
      • Capital Reduction
      • Key Business Objectives
      • On Time Delivery
      • Lead Time
      • Quality
      • Customer Satisfaction
    • Impact on Operational Excellence Metrics
  • 14. Evaluate and Rank Suggestions Effort and Risk
    • Effort required
      • People Resources
      • Capital Resources
      • Duration of Project
    • Probability of success
      • Technical Risk
        • Data available
        • Knowledge of process
      • Management Risk
        • Aligned with objectives
        • Support by value stream manager
    • Impact vs. Risk vs. Effort
      • Assess ROI (Return On Investment)
      • Assign priorities to projects
  • 15. Evaluate and Rank Suggestions
    • Example tool to rank projects
      • 0106-01 Project Rating.xls
  • 16.
    • Example chart to rank projects 0106-01 Project Rating.xls
  • 17. Measure
    • Establish measurement capability
      • Validate the database (transactional)
      • Gage R&R (Repeatability & Reproducibility)
      • Calibration is not enough
      • Many (or most) measurement systems are not capable
      • How good is the data you are using to make decisions?
    • Fix the measurement system
      • Enables calculation of process capability
      • Enables calculation of alpha & beta risks
      • This step is often skipped
  • 18. Analyze (and fix the obvious)
    • Find all KPOVs & KPIVs
      • (Key Process Output Variables; Key Process Input Variables)
    • FMEA, DOE, critical Xs, VA/NVA
      • (Failure Modes Effects Analysis; Design Of Experiment)
    • Graphical Analysis, ANOVA
      • (Analysis Of Variance)
    • Future Value Stream Map
  • 19. Improve
    • Optimize KPOVs & test the KPIVs
      • (Key Process Output Variables; Key Process Input Variables)
    • Redesign process, set pacemaker
    • 5S, Cell design, MRS
      • (Material Replenishment System)
    • Visual controls
    • Value Stream Plan
  • 20. Control
    • Management of Change
      • Owned by project champion and value stream manager
      • Critical to long term success of project
      • Physical and cultural changes
    • Measurement controls
      • On-going metrics
    • Visual Controls
      • Enable workers to self-manage the process
  • 21. Basic Implementation Roadmap Understand and Define Entire Value Streams Deploy Key Business Objectives - Measure and target (metrics) - Align and involve all employees - Develop and motivate Define, Measure, Analyze, Improve Identify root causes, prioritize, eliminate waste, make things flow and pulled by customers Control -Sustain Improvement -Drive Towards Perfection Identify Customer Requirements Vision (Strategic Business Plan) Continuous Improvement (DMAIC) Identify Customer Requirements
  • 22. Hoshin
  • 23.  
  • 24. Does it work?. Source: American Customer Satisfaction Index, U Michigan, HBR, 2001 1999 73 companies Ralston Purina Quaker Oats Hilton Hotels Coca-Cola Unilever etc. The top companies in Customer Satisfaction grow MVA at nearly twice the rate of their poor-performing counterparts. In Billions $
  • 25. What about Lean, TOC, TQM
    • Six Sigma
      • Remove defects, minimize variance
    • Lean
      • Remove waste, shorten the flow
    • TOC
      • Remove and manage constraints
    • TQM
      • Continuous Improvement
  • 26. Value Stream Map - Current State Customer Demand = 45 per day 2 shifts Stamping 342 CT=1sec Co=1 hr. Uptime=85% S. Weld # 1 CT=3 min Co=10 min. Uptime=70% I I I I Coils 5 days CT= 15 min Co=0 min. Uptime=100% 2 shifts CT= 67 min Co= 23 min FTY = 67% 2 shifts Shipping I I 81 202 122 Assembly Test 90 1X Daily 90/60/30 day Forecasts Order Entry Production Control MRP 6 WEEK Forecast Suppliers Weekly Fax WEEKLY SCHEDULE Lead Time - 34 Days 5 days 1 sec 7.6 days 3 min 1.8 days 15 min 2.7 days 67 min 4.5 days 4 min 2 days Lead Time =23.6 days 1 shift 1 shift CT= 4 min Co=0 Uptime=100% 2 shifts Competitive Lead Time = 3 Days Takt Time = 18.2 Minutes Orders/day = 36 Queue = 1.5 Days Touch Time = 89 min
  • 27. Customer Data On-Time Delivery Competitive LT = 3 days Takt Time = 18.2 min Demand = 45/day Customer Demand = 45 per day 2 shifts Stamping 342 CT=1sec Co=1 hr. Uptime=85% S. Weld # 1 CT=3 min Co=10 min. Uptime=70% I I I I Coils 5 days CT= 15 min Co=0 min. Uptime=100% 2 shifts CT= 67 min Co= 23 min FTY = 67% 2 shifts Shipping I I 81 202 122 Assembly Test 90 1X Daily 90/60/30 day Forecasts Order Entry Production Control MRP 6 WEEK Forecast Suppliers Weekly Fax WEEKLY SCHEDULE Lead Time - 34 Days 5 days 1 sec 7.6 days 3 min 1.8 days 15 min 2.7 days 67 min 4.5 days 4 min 2 days Lead Time =23.6 days 1 shift 1 shift CT= 4 min Co=0 Uptime=100% 2 shifts Competitive Lead Time = 3 Days Takt Time = 18.2 Minutes Orders/day = 36 Queue = 1.5 Days Touch Time = 89 min
  • 28. Inventory Raw = 5 days WIP = 12.1 days FG = 6.5 days Customer Demand = 45 per day 2 shifts Stamping 342 CT=1sec Co=1 hr. Uptime=85% S. Weld # 1 CT=3 min Co=10 min. Uptime=70% I I I I Coils 5 days CT= 15 min Co=0 min. Uptime=100% 2 shifts CT= 67 min Co= 23 min FTY = 67% 2 shifts Shipping I I 81 202 122 Assembly Test 90 1X Daily 90/60/30 day Forecasts Order Entry Production Control MRP 6 WEEK Forecast Suppliers Weekly Fax WEEKLY SCHEDULE Lead Time - 34 Days 5 days 1 sec 7.6 days 3 min 1.8 days 15 min 2.7 days 67 min 4.5 days 4 min 2 days Lead Time =23.6 days 1 shift 1 shift CT= 4 min Co=0 Uptime=100% 2 shifts Competitive Lead Time = 3 Days Takt Time = 18.2 Minutes Orders/day = 36 Queue = 1.5 Days Touch Time = 89 min
  • 29. Flow of Value Lead Time Touch Time = 89 min Lead Time = 23.6 days Customer Demand = 45 per day 2 shifts Stamping 342 CT=1sec Co=1 hr. Uptime=85% S. Weld # 1 CT=3 min Co=10 min. Uptime=70% I I I I Coils 5 days CT= 15 min Co=0 min. Uptime=100% 2 shifts CT= 67 min Co= 23 min FTY = 67% 2 shifts Shipping I I 81 202 122 Assembly Test 90 1X Daily 90/60/30 day Forecasts Order Entry Production Control MRP 6 WEEK Forecast Suppliers Weekly Fax WEEKLY SCHEDULE Lead Time - 34 Days 5 days 1 sec 7.6 days 3 min 1.8 days 15 min 2.7 days 67 min 4.5 days 4 min 2 days Lead Time =23.6 days 1 shift 1 shift CT= 4 min Co=0 Uptime=100% 2 shifts Competitive Lead Time = 3 Days Takt Time = 18.2 Minutes Orders/day = 36 Queue = 1.5 Days Touch Time = 89 min
  • 30. Constraints OTD, Lead Time CT (67) > Takt Time (18) Max Wip = 7.6 days Customer Demand = 45 per day 2 shifts Stamping 342 CT=1sec Co=1 hr. Uptime=85% S. Weld # 1 CT=3 min Co=10 min. Uptime=70% I I I I Coils 5 days CT= 15 min Co=0 min. Uptime=100% 2 shifts CT= 67 min Co= 23 min FTY = 67% 2 shifts Shipping I I 81 202 122 Assembly Test 90 1X Daily 90/60/30 day Forecasts Order Entry Production Control MRP 6 WEEK Forecast Suppliers Weekly Fax WEEKLY SCHEDULE Lead Time - 34 Days 5 days 1 sec 7.6 days 3 min 1.8 days 15 min 2.7 days 67 min 4.5 days 4 min 2 days Lead Time =23.6 days 1 shift 1 shift CT= 4 min Co=0 Uptime=100% 2 shifts Competitive Lead Time = 3 Days Takt Time = 18.2 Minutes Orders/day = 36 Queue = 1.5 Days Touch Time = 89 min
  • 31. Setup Times OP Margin, Lead Time CO = 23 min CO = Changeover CO = 1 hour Customer Demand = 45 per day 2 shifts Stamping 342 CT=1sec Co=1 hr. Uptime=85% S. Weld # 1 CT=3 min Co=10 min. Uptime=70% I I I I Coils 5 days CT= 15 min Co=0 min. Uptime=100% 2 shifts CT= 67 min Co= 23 min FTY = 67% 2 shifts Shipping I I 81 202 122 Assembly Test 90 1X Daily 90/60/30 day Forecasts Order Entry Production Control MRP 6 WEEK Forecast Suppliers Weekly Fax WEEKLY SCHEDULE Lead Time - 34 Days 5 days 1 sec 7.6 days 3 min 1.8 days 15 min 2.7 days 67 min 4.5 days 4 min 2 days Lead Time =23.6 days 1 shift 1 shift CT= 4 min Co=0 Uptime=100% 2 shifts Competitive Lead Time = 3 Days Takt Time = 18.2 Minutes Orders/day = 36 Queue = 1.5 Days Touch Time = 89 min
  • 32. Maintenance OTD, Lead Time Uptime = 70% Customer Demand = 45 per day 2 shifts Stamping 342 CT=1sec Co=1 hr. Uptime=85% S. Weld # 1 CT=3 min Co=10 min. Uptime=70% I I I I Coils 5 days CT= 15 min Co=0 min. Uptime=100% 2 shifts CT= 67 min Co= 23 min FTY = 67% 2 shifts Shipping I I 81 202 122 Assembly Test 90 1X Daily 90/60/30 day Forecasts Order Entry Production Control MRP 6 WEEK Forecast Suppliers Weekly Fax WEEKLY SCHEDULE Lead Time - 34 Days 5 days 1 sec 7.6 days 3 min 1.8 days 15 min 2.7 days 67 min 4.5 days 4 min 2 days Lead Time =23.6 days 1 shift 1 shift CT= 4 min Co=0 Uptime=100% 2 shifts Competitive Lead Time = 3 Days Takt Time = 18.2 Minutes Orders/day = 36 Queue = 1.5 Days Touch Time = 89 min
  • 33. Quality FTY = 67% Customer Demand = 45 per day 2 shifts Stamping 342 CT=1sec Co=1 hr. Uptime=85% S. Weld # 1 CT=3 min Co=10 min. Uptime=70% I I I I Coils 5 days CT= 15 min Co=0 min. Uptime=100% 2 shifts CT= 67 min Co= 23 min FTY = 67% 2 shifts Shipping I I 81 202 122 Assembly Test 90 1X Daily 90/60/30 day Forecasts Order Entry Production Control MRP 6 WEEK Forecast Suppliers Weekly Fax WEEKLY SCHEDULE Lead Time - 34 Days 5 days 1 sec 7.6 days 3 min 1.8 days 15 min 2.7 days 67 min 4.5 days 4 min 2 days Lead Time =23.6 days 1 shift 1 shift CT= 4 min Co=0 Uptime=100% 2 shifts Competitive Lead Time = 3 Days Takt Time = 18.2 Minutes Orders/day = 36 Queue = 1.5 Days Touch Time = 89 min
  • 34. Flow of Value OTD, Lead Time What is the pitch time? Who is setting the pace? Customer Demand = 45 per day 2 shifts Stamping 342 CT=1sec Co=1 hr. Uptime=85% S. Weld # 1 CT=3 min Co=10 min. Uptime=70% I I I I Coils 5 days CT= 15 min Co=0 min. Uptime=100% 2 shifts CT= 67 min Co= 23 min FTY = 67% 2 shifts Shipping I I 81 202 122 Assembly Test 90 1X Daily 90/60/30 day Forecasts Order Entry Production Control MRP 6 WEEK Forecast Suppliers Weekly Fax WEEKLY SCHEDULE Lead Time - 34 Days 5 days 1 sec 7.6 days 3 min 1.8 days 15 min 2.7 days 67 min 4.5 days 4 min 2 days Lead Time =23.6 days 1 shift 1 shift CT= 4 min Co=0 Uptime=100% 2 shifts Competitive Lead Time = 3 Days Takt Time = 18.2 Minutes Orders/day = 36 Queue = 1.5 Days Touch Time = 89 min
  • 35. Making it happen
    • Three major roles
    • Implementer
      • Learns the tools
      • Works the process
      • Solves day to day problems
    • Manager
      • Learns the methodology
      • Manages a value stream
      • Reviews project teams
    • Leader
      • Establishes the vision for the future
      • Sets priorities
      • Encourages
    Where do you need to focus?
  • 36. What Is a Sigma?
    • A metric that indicates how well a process is performing.
      • Higher is better
      • Measures the capability of the process to perform defect-free work
      • Also known as “z”, it is based on standard deviation for continuous data
      • For discrete data it is calculated from DPMO
  • 37. The Normal Curve and Capability Low Sigma High Sigma Units of Measure Units of Measure Units of Measure  Units of Measure Performance Limit Probability of a Defect Area of Yield