Operational Excellence Six Sigma Six Sigma: DMAC; Y=f(x) s it a Goal, a Measure, a Process, a Tool or an expletive deleted? mprove By Lee Olson Presentation to NFORMS
Objectives mprove 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
Define mprove s it a Goal, a Measure, a Process, a Tool or an expletive deleted? Yes
Define mprove Six Sigma s a management methodology Customer focused Data driven decisions Breakthrough performance gains Validated bottom line results
Customer Focused mprove ON TME DELVERY (sample) The percentage of sales order line items that ship complete on or before the original customer promise date, for all line items shipped in the month. mportance to Customers Our Performance Compared to Competitors Shared Goals Training Quality OTD Price Complaints Complete High 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% Moderateto- Low 0% Top 5 Action tems Original Due Current Driver Action Description Status Status Description Owner Date Due Date Late Supplier Deliveries Monthly reporting to suppliers on delivery & On Report Cards mplemented. Adam 5/21 5/21 quality metrics. track Late Supplier Deliveries Late Supplier Deliveries xyz Cell Always Late Unrealistic Promise Date On-Time Delivery Target Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Arrange face to face meetings with top offenders. Review and approve supplier's corrective action plan. Kaizen Event to focus on improving throughput by 40% and improve labor efficiency by 35% Focus on custom products to provide realistic ATP based on inventory and leadtime of components. % mpact 100% On track Meetings Complete with top 10 Suppliers. Caution Corrective Action Plan in Place for 2 major Suppliers On track 75% 50% 25% 0% Late Supplier Deliveries xyz Cell Always Late Event held 5/1. 25% throughput improvement in May. Labor Efficiency ncrease of 30% Problem Continued lack of progress. Restructured and focused team. Developing detailed plan. Pareto of Drivers Unrealistic Promise Date Reason Orders on Credit Hold Low Yield on part abc Engineering Change Orders Beth 6/15 6/15 Carlos 7/15 9/15 Doreen 5/21 5/21 Earnest 6/15 8/15 We re Better They re Better
Data Driven Decisions mprove Y= f (X) To get results, should we focus our behavior on the Y or X? Y Dependent Output Effect Symptom Monitor Response X1... XN ndependent nput-process Cause Problem Control Factor Why should we test or inspect Y, if we know this relationship?
Breakthrough performance gains mprove (Distribution Shifted ± 1.5σ) σσ PPM 2 308,537 3 66,807 4 6,210 5 233 6 3.4 Process Process Capability Defects Defects per per Million Million Opportunities 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.
Validated bottom line results Assuming a 10% change in the factor mprove Price ncrease Material Costs Volume nc. with Leverage Manufacturing SG&A Volume nc. No Leverage Taxes Labor Working Capital General-5% Price Reduction Factors mpact on Bottom Line
Define mprove Methodology Define Measure Analyze mprove Control
Roadmap Example mprove Celebrate Project $ Next Project Control Document process (Ws, Std Work) Mistake proof, TT sheet, C List Analyze change in metrics Value Stream Review Prepare final report Validate Project $ Define Customers, Value, Problem Statement Scope, Timeline, Team Primary/Secondary & OpEx Metrics Current Value Stream Map Voice Of Customer (QFD) Validate Project $ Measure Assess specification / Demand Measurement Capability (Gage R&R) Correct the measurement system Process map, Spaghetti, Time obs. Measure OVs & Vs / Queues Validate Project $ mprove Optimize KPOVs & test the KPVs Redesign process, set pacemaker 5S, Cell design, MRS Visual controls Value Stream Plan Validate Project $ Analyze (and fix the obvious) Root Cause (Pareto, C&E, brainstorm) Find all KPOVs & KPVs FMEA, DOE, critical Xs, VA/NVA Graphical Analysis, ANOVA Future Value Stream Map
Operational Excellence Methodology Plan dentify Problem Practical Problem Problem Definition Problem Solution Problem Control Execute Execute Plan Strategic Link to Business Plan defined in Project Selection Process Defined Business mpact 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 Develop a focused Problem Statement and Objective Develop a Process Map and/or FMEA Develop a Current State Map dentify the response variable(s) and how to measure them Analyze measurement system capability Assess the specification (s one in place? s it the right one?) 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 dentify 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 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 Problem Solving ❶ What do you want to know? ❷ How do you want to see what it is that you need to know? ❸ What type of tool will generate what it is that you need to see? ❹ What type of data is required of the selected tool? ❺ Where can you get the required type of data? Based in part on Six Sigma Methodology developed by GE Medical Systems and Six Sigma Academy, nc. Crane Co. Op. Ex. Methodology Originated by MBBs; D. Braasch, J. Davis, R. Duggins, J. O Callaghan, R. Underwood,. Wilson
Define Key tems mprove Customers, Value, Problem Statement Scope, Timeline, Team Primary/Secondary & OpEx Metrics Current Value Stream Map Voice Of Customer (QFD) (Quality Function Deployment)
Project Selection mpact mprove Business mpact Revenue Growth Cost Reduction Capital Reduction Key Business Objectives On Time Delivery Lead Time Quality Customer Satisfaction mpact on Operational Excellence Metrics
Evaluate and Rank Suggestions Effort and Risk mprove 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 mpact vs. Risk vs. Effort Assess RO (Return On nvestment) Assign priorities to projects
Evaluate and Rank Suggestions mprove Project nformation mpact Effort Risk # Mfg (M) or Admin (A) Revenue Growth Cost Reduction Capital Reduction Key Business Objective On Time Delivery Lead Time Project Description Variable weightings 20% 15% 10% 15% 20% 5% 5% 10% 100% 50% 20% 30% 100% 40% 60% 100% 1 A Customer Billing Errors 0 2 0 4 4 2 2 5 2.4 2 1 3 2.1 1 4 2.8 2 M Warranty scrap warranty vs sales 0 2 0 1 1 0 3 3 1.1 4 4 5 4.3 4 2 2.8 3 A Vendor Delivery Performance 0 2 2 2 5 4 3 0 2.2 1 1 3 1.6 1 2 1.6 4 M On Time Shipping Performance 2 1 2 4 5 0 1 5 2.9 4 1 2 2.8 1 3 2.2 5 A Hiring and Retention 20% - 24% Turnover 0 3 0 2 1 0 3 2 1.3 3 2 4 3.1 1 4 2.8 Quality Customer Satisfaction Total mpact People Resources Capital Resources Duration of Project Total Effort Technical Risk Management Risk Total Risk 6 A New Product Development Cycle Time 3 4 2 5 3 3 4 5 3.6 5 3 5 4.6 5 5 5.0 7 M Manufacturing Maintenance Tooling Maintenance 0 3 0 1 2 3 1 0 1.2 1 4 1 1.6 1 1 1.0 8 A Day Sales Outstanding (DSO) 0 0 4 2 0 0 0 0 0.7 1 0 2 1.1 1 1 1.0 9 M FTY of 65% on product 123 4 4 2 5 4 4 5 5 4.1 2 1 1 1.5 2 1 1.4 Example tool to rank projects 0106-01 Project Rating.xls
Project Ranking Risk = Ball Size Project Number n 5 4 9 6 mpact 3 2 3 1 4 1 8 7 5 2 0 1 2 3 4 5 Effort Example chart to rank projects 0106-01 Project Rating.xls
Measure mprove 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
Analyze (and fix the obvious) mprove Find all KPOVs & KPVs (Key Process Output Variables; Key Process nput Variables) FMEA, DOE, critical Xs, VA/NVA (Failure Modes Effects Analysis; Design Of Experiment) Graphical Analysis, ANOVA (Analysis Of Variance) Future Value Stream Map
mprove mprove Optimize KPOVs & test the KPVs (Key Process Output Variables; Key Process nput Variables) Redesign process, set pacemaker 5S, Cell design, MRS (Material Replenishment System) Visual controls Value Stream Plan
Control mprove 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
Basic mplementation Roadmap mprove dentify Customer Requirements Vision (Strategic Business Plan) Continuous mprovement (DMAC) 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, mprove dentify root causes, prioritize, eliminate waste, make things flow and pulled by customers Control -Sustain mprovement -Drive Towards Perfection
Hoshin mprove Key: mpact Owner Support Type in --> 4 l m 1.2 6 Establish tracking of OTD in every cell 1.1 5 mprove On Time Delivery to 98% 3.2 4 Train workers in how our products are used by our major customers 3.1 3 Conduct interviews with top 10 customers 2.2 2 Train functional leaders as LGBs 2.1 1 Train leadership team as Lean Green Belts (LGB) Resource 3.0 2.0 1.0 Leaders have ability to map a value stream Metrics module in all appropriate training sequences Training projects demonstrate flowdown of metics to operational level Your Annual Breakthrough mprove Customer Focus Educate/Get Everyone nvolved mprove the Metrics Complete 1 Leadership LGB training course Develop culture of teams Trainees participate in customer survey Complete 3 functional LGB training courses Bring reps from top 10 customers in for plant tours mplement lean concepts in top 3 volume lines Objectives 100% Completion of LGB Projects establish pareto of drivers for OTD T Operations Quality Engineering Maintenance Marketing Training Your Manager's 1-Year Breakthrough Objectives ndicator's and Goals Benefits 1 2 3 4 5 6 7 8
ON TME DELVERY (sample) The percentage of sales order line items that ship complete on or before the original customer promise date, for all line items shipped in the month. 100% 90% On-Time Delivery 100% Pareto of Drivers 80% 70% 60% 50% 40% 30% % mpact 75% 50% 25% 0% 20% 10% 0% Target Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Late Supplier Deliveries xyz Cell Always Late Unrealistic Promise Date Reason Orders on Credit Hold Low Yield on part abc Engineering Change Orders Top 5 Action tems Original Due Current Driver Action Description Status Status Description Owner Date Due Date Late Supplier Deliveries Report Cards mplemented. Adam 5/21 5/21 Monthly reporting to suppliers on delivery & quality metrics. On track Late Supplier Deliveries Arrange face to face meetings with top offenders. On track Meetings Complete with top 10 Suppliers. Beth 6/15 6/15 Late Supplier Deliveries Review and approve supplier's corrective action plan. Caution Corrective Action Plan in Place for 2 major Suppliers Carlos 7/15 9/15 xyz Cell Always Late Kaizen Event to focus on improving throughput by 40% and improve labor efficiency by 35% On track Event held 5/1. 25% throughput improvement in May. Labor Efficiency ncrease of 30% Doreen 5/21 5/21 Unrealistic Promise Date Focus on custom products to provide realistic ATP based on inventory and leadtime of components. Problem Continued lack of progress. Restructured and focused team. Developing detailed plan. Earnest 6/15 8/15
Does it work?. mprove The top companies in Customer Satisfaction grow MVA at nearly twice the rate of their poor-performing counterparts. 1999 73 companies Ralston Purina Quaker Oats Hilton Hotels Coca-Cola Unilever etc. Market Value Added 50 40 30 20 10 0 n Billions $ $23 Low $42 High Customer Satisfaction ndex Score Source: American Customer Satisfaction ndex, U Michigan, HBR, 2001
What about Lean, TOC, TQM mprove Six Sigma Remove defects, minimize variance Lean Remove waste, shorten the flow TOC Remove and manage constraints TQM Continuous mprovement
Value Stream Map - Current State 6 WEEK Forecast Production Control 90/60/30 day Forecasts Customer Suppliers Lead Time - 34 Days Weekly Fax MRP WEEKLY SCHEDULE Order Entry Orders/day = 36 Queue = 1.5 Days Demand = 45 per day Takt Time = 18.2 Minutes Competitive Lead Time = 3 Days 1X Daily Coils 5 days Stamping CT=1sec Co=1 hr. Uptime=85% 1 shift 342 S. Weld # 1 CT=3 min Co=10 min. Uptime=70% 1 shift 81 Assembly CT= 15 min Co=0 min. Uptime=100% 122 Test CT= 67 min Co= 23 min FTY = 67% 202 Shipping CT= 4 min Co=0 Uptime=100% 90 Lead Time =23.6 days Touch Time = 89 min 5 days 7.6 days 1.8 days 2.7 days 4.5 days 2 days 1 sec 3 min 15 min 67 min 4 min
Suppliers Lead Time - 34 Days Demand = 45/day Takt Time = 18.2 min 6 WEEK Forecast Competitive LT = 3 days Weekly Fax Production Control MRP WEEKLY SCHEDULE Customer Data On-Time Delivery Order Entry Orders/day = 36 Queue = 1.5 Days 90/60/30 day Forecasts Customer Demand = 45 per day Takt Time = 18.2 Minutes Competitive Lead Time = 3 Days 1X Daily Coils 5 days Stamping CT=1sec Co=1 hr. Uptime=85% 1 shift 342 S. Weld # 1 CT=3 min Co=10 min. Uptime=70% 1 shift 81 Assembly CT= 15 min Co=0 min. Uptime=100% 122 Test CT= 67 min Co= 23 min FTY = 67% 202 Shipping CT= 4 min Co=0 Uptime=100% 90 Lead Time =23.6 days Touch Time = 89 min 5 days 7.6 days 1.8 days 2.7 days 4.5 days 2 days 1 sec 3 min 15 min 67 min 4 min
Suppliers Raw = 5 days WP = 12.1 days FG = 6.5 days Lead Time - 34 Days Weekly Fax 6 WEEK Forecast Production Control MRP WEEKLY SCHEDULE Order Entry Orders/day = 36 Queue = 1.5 Days 90/60/30 day Forecasts nventory Customer Demand = 45 per day Takt Time = 18.2 Minutes Competitive Lead Time = 3 Days 1X Daily Coils 5 days Stamping CT=1sec Co=1 hr. Uptime=85% 1 shift 342 S. Weld # 1 CT=3 min Co=10 min. Uptime=70% 1 shift 81 Assembly CT= 15 min Co=0 min. Uptime=100% 122 Test CT= 67 min Co= 23 min FTY = 67% 202 Shipping CT= 4 min Co=0 Uptime=100% 90 Lead Time =23.6 days Touch Time = 89 min 5 days 7.6 days 1.8 days 2.7 days 4.5 days 2 days 1 sec 3 min 15 min 67 min 4 min
Suppliers Lead Time = 23.6 days Touch Time = 89 min Lead Time - 34 Days Weekly Fax 6 WEEK Forecast Production Control MRP WEEKLY SCHEDULE Order Entry Orders/day = 36 Queue = 1.5 Days Flow of Value Lead Time 90/60/30 day Forecasts Customer Demand = 45 per day Takt Time = 18.2 Minutes Competitive Lead Time = 3 Days 1X Daily Coils 5 days Stamping CT=1sec Co=1 hr. Uptime=85% 1 shift 342 S. Weld # 1 CT=3 min Co=10 min. Uptime=70% 1 shift 81 Assembly CT= 15 min Co=0 min. Uptime=100% 122 Test CT= 67 min Co= 23 min FTY = 67% 202 Shipping CT= 4 min Co=0 Uptime=100% 90 Lead Time =23.6 days Touch Time = 89 min 5 days 7.6 days 1.8 days 2.7 days 4.5 days 2 days 1 sec 3 min 15 min 67 min 4 min
Suppliers Max Wip = 7.6 days CT (67) > Takt Time (18) Lead Time - 34 Days Weekly Fax 6 WEEK Forecast Production Control MRP WEEKLY SCHEDULE Order Entry Orders/day = 36 Queue = 1.5 Days Constraints OTD, Lead Time 90/60/30 day Forecasts Customer Demand = 45 per day Takt Time = 18.2 Minutes Competitive Lead Time = 3 Days 1X Daily Coils 5 days Stamping CT=1sec Co=1 hr. Uptime=85% 1 shift 342 S. Weld # 1 CT=3 min Co=10 min. Uptime=70% 1 shift 81 Assembly CT= 15 min Co=0 min. Uptime=100% 122 Test CT= 67 min Co= 23 min FTY = 67% 202 Shipping CT= 4 min Co=0 Uptime=100% 90 Lead Time =23.6 days Touch Time = 89 min 5 days 7.6 days 1.8 days 2.7 days 4.5 days 2 days 1 sec 3 min 15 min 67 min 4 min
Suppliers CO = 1 hour CO = 23 min CO = Changeover Lead Time - 34 Days Weekly Fax 6 WEEK Forecast Production Control MRP WEEKLY SCHEDULE Setup Times OP Margin, Lead Time Order Entry Orders/day = 36 Queue = 1.5 Days 90/60/30 day Forecasts Customer Demand = 45 per day Takt Time = 18.2 Minutes Competitive Lead Time = 3 Days 1X Daily Coils 5 days Stamping CT=1sec Co=1 hr. Uptime=85% 1 shift 342 S. Weld # 1 CT=3 min Co=10 min. Uptime=70% 1 shift 81 Assembly CT= 15 min Co=0 min. Uptime=100% 122 Test CT= 67 min Co= 23 min FTY = 67% 202 Shipping CT= 4 min Co=0 Uptime=100% 90 Lead Time =23.6 days Touch Time = 89 min 5 days 7.6 days 1.8 days 2.7 days 4.5 days 2 days 1 sec 3 min 15 min 67 min 4 min
Uptime = 70% Maintenance OTD, Lead Time 6 WEEK Forecast Production Control 90/60/30 day Forecasts Customer Suppliers Lead Time - 34 Days Weekly Fax MRP WEEKLY SCHEDULE Order Entry Orders/day = 36 Queue = 1.5 Days Demand = 45 per day Takt Time = 18.2 Minutes Competitive Lead Time = 3 Days 1X Daily Coils 5 days Stamping CT=1sec Co=1 hr. Uptime=85% 1 shift 342 S. Weld # 1 CT=3 min Co=10 min. Uptime=70% 1 shift 81 Assembly CT= 15 min Co=0 min. Uptime=100% 122 Test CT= 67 min Co= 23 min FTY = 67% 202 Shipping CT= 4 min Co=0 Uptime=100% 90 Lead Time =23.6 days Touch Time = 89 min 5 days 7.6 days 1.8 days 2.7 days 4.5 days 2 days 1 sec 3 min 15 min 67 min 4 min
FTY = 67% Quality 6 WEEK Forecast Production Control 90/60/30 day Forecasts Customer Suppliers Lead Time - 34 Days Weekly Fax MRP WEEKLY SCHEDULE Order Entry Orders/day = 36 Queue = 1.5 Days Demand = 45 per day Takt Time = 18.2 Minutes Competitive Lead Time = 3 Days 1X Daily Coils 5 days Stamping CT=1sec Co=1 hr. Uptime=85% 1 shift 342 S. Weld # 1 CT=3 min Co=10 min. Uptime=70% 1 shift 81 Assembly CT= 15 min Co=0 min. Uptime=100% 122 Test CT= 67 min Co= 23 min FTY = 67% 202 Shipping CT= 4 min Co=0 Uptime=100% 90 Lead Time =23.6 days Touch Time = 89 min 5 days 7.6 days 1.8 days 2.7 days 4.5 days 2 days 1 sec 3 min 15 min 67 min 4 min
Suppliers Who is setting the pace? What is the pitch time? Lead Time - 34 Days Weekly Fax 6 WEEK Forecast Production Control MRP WEEKLY SCHEDULE Order Entry Orders/day = 36 Queue = 1.5 Days Flow of Value OTD, Lead Time 90/60/30 day Forecasts Customer Demand = 45 per day Takt Time = 18.2 Minutes Competitive Lead Time = 3 Days 1X Daily Coils 5 days Stamping CT=1sec Co=1 hr. Uptime=85% 1 shift 342 S. Weld # 1 CT=3 min Co=10 min. Uptime=70% 1 shift 81 Assembly CT= 15 min Co=0 min. Uptime=100% 122 Test CT= 67 min Co= 23 min FTY = 67% 202 Shipping CT= 4 min Co=0 Uptime=100% 90 Lead Time =23.6 days Touch Time = 89 min 5 days 7.6 days 1.8 days 2.7 days 4.5 days 2 days 1 sec 3 min 15 min 67 min 4 min
Making it happen mprove Three major roles mplementer 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?
What s a Sigma? mprove 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
The Normal Curve and Capability mprove Units of Measure Area of Yield Performance Limit Probability of a Defect µ µ Units of Measure Units of Measure Poor Process Capability Excellent Process Capability Very High Probability of Defects Very High Probability of Defects Very Low Probability of Defects Very Low Probability of Defects LSL USL LSL USL Low Low Sigma Sigma High High Sigma Sigma