Mastering Lean Six Sigma advanced black belt concepts /
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| Format: | Electronisk eBog |
| Sprog: | engelsk |
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[New York, N.Y.] (222 East 46th Street, New York, NY 10017) :
Momentum Press,
2013.
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| Online adgang: | An electronic book accessible through the World Wide Web; click to view |
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Indholdsfortegnelse:
- Part I. Design and develop the required processes (the need)
- 1. Mastering Lean Six Sigma principles
- 1.1 Lean Six Sigma: theory and constraints
- 1.1.1 What is Lean Six Sigma and what Lean Six Sigma can do for you?
- 1.1.2 Statistically what is Six Sigma?
- 1.1.3 What is lean concept?
- 1.2 Lean Six Sigma master black belt
- 1.3 Lean Six Sigma black belt overview
- 1.3.1 Define
- 1.3.2 Measure
- 1.3.3 Analyze
- 1.3.4 Improve
- 1.3.5 Control and sustain
- 2. Lean Six Sigma and master black belt roles (who is the leader?)
- 2.1 Master black belt roles in the organization
- 2.2 Master black belt (MBB) qualification
- 2.2.1 Leadership roles
- 2.2.2 Technical activity roles
- 2.2.3 MBB job description
- 2.2.4 Completion of curriculums
- 2.3 MBB program development
- 2.4 Decision-making solutions, evaluating alternatives
- 2.5 Developing and utilizing a professional network
- 2.6 Employee empowerment and motivation techniques
- 2.7 Efficient and effective coaching, training, and mentoring, self-directed
- 2.8 Advanced presentation skills
- 2.9 Rewards and recognition
- 3. Lean Six Sigma infrastructure: designing and engineering (Lean Six Sigma deployment)
- 3.1 Initiate financial growth need projects
- 3.2 Elements of successful Six Sigma implementation
- 3.2.1 Management system support and commitment
- 3.2.2 Well-trained belts
- 3.2.3 Well-defined projects and infrastructure
- 3.2.4 Lean Six Sigma success models
- 3.3 Roadmap for deployment phase
- 3.3.1 Envision financial growth needs projects
- 3.3.2 Launch the project initiative
- 3.3.3 Engineer, execute, and manage the project
- 3.3.4 Continuous progress and maintaining the momentum
- 3.3.5 Changing the way organizations work
- 3.4 Strategies to overcome organizational resistance to changes
- 3.5 Converting goals/objectives into actionable projects
- Part II. Launching the objectives
- 4. Launching the Lean Six Sigma project initiative: what works and what doesn't
- 4.1 SWOT analysis
- 4.1.1 Strength
- 4.1.2 Weakness
- 4.1.3 Opportunities
- 4.1.4 Threats
- 4.2 Project selection criteria
- 4.3 Making the others buy in and support for your projects
- 4.3.1 Identify project stakeholders
- 4.3.2 Analyze project stakeholders
- 4.3.3 Create project stakeholder plan
- 4.4 Six Sigma teaming
- 4.4.1 Barriers to a Six Sigma culture
- 4.4.2 Why team?
- 4.5 Six Sigma teaming: forming/storming/norming/performing model
- 4.5.1 Forming or orientation
- 4.5.2 Storming of dissatisfaction
- 4.5.3 Norming or resolution
- 4.5.4 Performing or production
- 4.5.5 Adjourning
- 4.6 Conflict management: the five conflict handling modes
- 4.6.1 Avoiding
- 4.6.2 Accommodating
- 4.6.3 Collaborating
- 4.6.4 Competing or controlling
- 4.6.5 Compromising
- 4.7 Conflict resolution
- 4.7.1 Effective conflict resolution behaviors
- 4.7.2 Key conflict points to consider
- 4.7.3 Conflict and power
- 4.8 Leadership decision-making processes and tools
- 4.8.1 Decision-making approaches
- 4.8.2 Decision-making tools
- 4.8.3 Team decision through consensus
- 4.9 Project and process assessment matrix
- 4.10 Six Sigma financial reporting (using financial measurement to analyze performance)
- 4.10.1 Plan of action
- 4.10.2 Financial accountabilities
- Part III. Leading the effort
- 5. Leading and engineering multiple Lean Six Sigma projects
- 5.1 Managing multiple project and project reviews
- 5.1.1 Project management and reviews
- 5.1.2 Why review?
- 5.1.3 Holding reviews
- 5.1.4 Lean Six Sigma black belts: the criteria for selection
- 5.2 How to master the skills of Lean Six Sigma facilitation
- 5.2.1 How to become an effective facilitator
- 5.2.2 Strategic roles of the facilitator in the organization
- 5.2.3 Effective elements of communication strategies and skills
- 5.2.4 Time your time from time to time
- 5.2.5 Building team commitment and interactions
- 5.3 Communication planning
- 5.3.1 Six Sigma project communication
- 5.3.2 Communication plan considerations
- 5.4 Project closure
- 5.5 Lean Six Sigma master black belt deployment plan
- 5.6 Case study: Lean Six Sigma deployment plan
- 5.6.1 Strategy and goals for Six Sigma
- 5.6.2 Performance metrics (overall program)
- 5.6.3 Project selection criteria
- 5.6.4 Project identification/prioritization
- 5.6.5 Organization structure/roles
- 5.6.6 Training requirements
- 5.6.7 Management review process
- 5.6.8 Communication plan
- 6. Design and develop organizational Lean Six Sigma roadmap: delivering continuous breakthrough performance
- 6.1 Roadmap for successful corporate results
- 6.2 Design for Lean Six Sigma process
- 6.3 Vision of Lean Six Sigma process
- 6.3.1 Where and when do we use Lean Six Sigma?
- 6.3.2 Why use Lean Six Sigma?
- 6.4 Design for Lean Six Sigma roadmap
- 6.4.1 Phase 0: concept and ideation
- 6.4.2 Phase 1: define, feasibility, and planning
- 6.4.3 Phase 2: designing and developing
- 6.4.4 Phase 3: verifying and validating the developed design
- 6.4.5 Phase 4: production and commercializing
- 6.4.6 Phase 5: control and sustaining
- 6.5 Lean Six Sigma continuous process improvement roadmap
- 6.5.1 Phase 0: concept
- 6.5.2 Phase 1: define
- 6.5.3 Phase 2: measure
- 6.5.4 Phase 3: analyze
- 6.5.5 Phase 4: improve
- 6.5.6 Phase 5: control and sustaining
- 6.6 Leading the efforts
- 6.6.1 Project report and reviewing progress
- 6.6.2 Communication
- 6.6.3 Awards and appreciation
- 6.7 Maintaining and gaining the momentum
- 6.8 Tollgate review
- 6.8.1 Develop a RACI matrix
- 6.9 Lean Six Sigma culture and the way it works
- 7. Define concepts and strategies
- 7.1 Concepts, vision, and ideation phase
- 7.2 What is Six Sigma "define phase"
- 7.3 Lean Six Sigma variation
- 7.3.1 Positional variation
- 7.3.2 Cyclical variation
- 7.3.3 Temporal variation
- 7.4 Lean Six Sigma project selection process
- 7.4.1 Business strategy
- 7.4.2 Financial impact analysis
- 7.4.3 Operational engineering
- 7.5 Lean Six Sigma process management and project life cycle
- 7.5.1 Business process management
- 7.5.2 BPM project life cycle
- 7.6 Who is a customer?
- 7.7 Voice of customer
- 7.8 Kano model of quality
- 7.9 SWOT (strength, weaknesses, opportunities, threats) analysis
- 7.9.1 Strength
- 7.9.2 Weakness
- 7.9.3 Opportunities
- 7.9.4 Threats
- 7.10 Project scope, charter, and goals
- 7.11 Lean Six Sigma metrics and performance measures
- 7.11.1 Critical to quality
- 7.11.2 Critical to business and voice of business
- 7.11.3 Cost of quality
- 7.12 Specific, measureable, attainable, realistic, time-phased
- 7.12.1 Specific
- 7.12.2 Measurable
- 7.12.3 Attainable (achievable)
- 7.12.4 Realistic
- 7.12.5 Time-phased
- 7.13 Force field analysis
- 7.13.1 Define the current process problem
- 7.13.2 Define the improvement goals
- 7.13.3 Define the driving forces
- 7.13.4 Define the restraining forces
- 7.13.5 Establishing the comprehensive change strategy
- 7.13.6 Force field analysis example
- 7.14 Tollgate review and checklist for define phase
- 7.14.1 Define phase deliverables and checklists
- 8. Measure concepts and strategies
- 8.1 The seven quality control tools for measurement
- 8.1.1 Cause-and-effect diagram (Fishbone or Ishikawa) y = f(x)
- 8.1.2 Data collection (process measurement and characterization): voice of customer (VOC)
- 8.1.3 Pareto chart
- 8.1.4 Histogram
- 8.1.5 Scatter diagram and correlation
- 8.1.6 Control charts
- 8.1.7 Stratification (trent, flow, or run chart)
- 8.2 The design of seven management/planning tools
- 8.2.1 Affinity diagram
- 8.2.2 Interrelationship diagram
- 8.2.3 Tree diagram
- 8.2.4 The matrix diagram or matrix chart
- 8.2.5 Matrix data analysis
- 8.2.6 Process decision program chart (PDPC)
- 8.2.7 Arrow diagram (the activity network diagram)
- 8.3 Process mapping
- 8.3.1 SIPOC chart (supply, inputs, process, output, customer)
- 8.3.2 Value stream mapping
- 8.4 Kaizen events: planning and execution
- 8.5 Lean: improves efficiency/Six Sigma and improves effectiveness
- 8.6 Quality function deployment
- 8.6.1 What is QFD quality?
- 8.6.2 Building a "house of quality"
- 8.7 Measurement system analysis (MSA)
- 8.8 Process measurement
- 8.8.1 Data collection
- 8.8.2 Principles of variation
- 8.8.3 Type of variation
- 8.8.4 Type of data
- 8.8.5 Science of statistics
- 8.8.6 Classification of numerical data
- 8.8.7 Qualitative data (nominal or ordinal)
- 8.8.8 Quantitative data (interval or ratio)
- 8.8.9 Sampling strategy
- 8.8.10 Data analysis
- 8.9 Tollgate review and checklist for measure phase
- 8.9.1 Measure phase deliverables and checklists
- 9. Analysis of concepts and strategies: advanced statistical analysis, achieving ultimate performance scientifically
- 9.1 Descriptive statistics
- 9.1.1 Descriptive statistics techniques and graphing: stem and leaf
- 9.1.2 Histogram
- 9.1.3 Measure of center tendency
- 9.1.4 Measures of variability
- 9.2 Descriptive measures
- 9.2.1 Measurement system analysis
- 9.2.2 Accuracy/bias
- 9.2.3 Stability (consistency)
- 9.2.4 Linearity
- 9.2.5 Gage repeatability and reproducibility (or Gage R&R)
- 9.2.6 Measurement system components
- 9.3 Probability distributions and concepts
- 9.3.1 Definition, experiment, outcome, and sample space
- 9.3.2 Probability of event (EI) as relative frequency
- 9.3.3 Marginal and conditional probabilities
- 9.3.4 The rules of probability (union of events)
- 9.3.5 The rules of probability (intersection of events)
- 9.4 Discrete random variables: probability distribution
- 9.4.1 Binomial probability distribution
- 9.4.2 Poisson probability distribution
- 9.4.3 The hypergeometric probability distribution
- 9.5 Continuous random variables probability distributions
- 9.5.1 Normal probability distribution
- 9.5.2 t-distribution
- 9.5.3 Normality test
- 9.5.4 Exponential distribution
- 9.5.5 Reliability engineering
- 9.6 Inferential statistics and sampling distribution
- 9.6.1 Random sampling and the distribution of the sample mean
- 9.6.2 Central limit theorem (CLT)
- 9.6.3 Confidence interval for the mean [mu] of normal population ([theta] is known)
- 9.6.4 Confidence interval for the mean [mu] of normal
- Population (([theta] is unknown)
- 9.6.5 Selecting the necessary sample size
- 9.7 Hypothesis testing, inferences procedures, and proportions testing
- 9.7.1 Hypothesis testing for the mean [mu] and variance ([theta]2) of the population
- 9.7.2 P-value application
- 9.7.3 Hypothesis testing using p-value approach (using equal mean)
- 9.7.4 Hypothesis testing on the mean [mu] of a normal population for small sample
- 9.7.5 Inference procedures for two populations: applying the concepts
- 9.7.6 Comparing two normal population means ([mu]1 - [mu]2) using two small, independent samples: apply the mechanics
- 9.7.7 Comparing the variance of two normal populations ([theta]12-[theta]22) using independent samples-f test (small sample size): apply the mechanics
- 9.7.8 Estimation and testing for population proportions
- 9.7.9 Confidence interval for a population proportion: large sample
- 9.7.10 Hypothesis testing for a population proportion
- 9.7.11 Comparing population proportion: two large independent samples
- 9.8 Advanced analysis of variance (ANOVA)
- 9.8.1 One-way analysis of variance
- 9.8.2 Randomized block design and analysis of variance
- 9.8.3 Two-way analysis of variance
- 9.9 Linear regression analysis
- 9.9.1 Scatter plots and correlation analysis
- 9.9.2 Simple linear regression model and analysis
- 9.9.3 Linear regression model
- 9.9.4 Least square criteria
- 9.9.5 Inferences on the slope [beta]1, concept: t-test
- 9.9.6 Confidence interval for B1 slope
- 9.9.7 Prediction by regression analysis: confidence interval for an individual y, given x
- 9.10 Multiple regression analysis
- 9.10.1 Multiple linear regression model building
- 9.10.2 Hypothesis testing and confidence interval
- 9.10.3 Polynomial and nonlinear regression model building
- 9.11 Tollgate review and deliverables for analysis phase
- 9.11.1 Analysis phase deliverables and checklist
- 10. Improve concepts and strategies
- 10.1 Advanced Lean Six Sigma experimental design
- 10.1.1 Experimental design terminology
- 10.1.2 Elements of an experimental design
- 10.2 One-factor-at-a-time design (OFATD) x1, x2, ... xk
- 10.3 Full factorial design
- 10.3.1 How to calculate the effects
- 10.4 Fractional (reduced) factorial design (FFD)
- 10.5 Robust engineering design and analysis
- 10.6 Response surface designs and process/product optimization
- 10.7 Central composite design (CCD): optimum design
- 10.8 Failure mode effect analysis (FMEA)
- 10.9 Poka-yoke (Japanese term for mistake proofing, pronounced Poh-kah yoh-kay)
- 10.10 5S Kaizen principles
- 10.11 Tollgate review and deliverables for improve phase
- 10.11.1 Improve phase deliverables and checklist
- 11. Control concepts and strategies
- 11.1 Process control strategy
- 11.2 Process control objectives
- 11.3 Sustaining the improved process
- 11.4 Ten essential process/quality control tools
- 11.5 Control chart types
- 11.5.1 X-bar (x) and r-chart
- 11.5.2 R-chart limits models
- 11.5.3 Steps for developing x and r charts
- 11.6 P-chart: attribute control chart
- 11.7 C-chart
- 11.8 Control limits versus specification limits
- 11.9 Process capability ratio, Cp and Cpk
- 11.10 Tollgate review and deliverables for control phase
- 11.10.1 Control phase deliverables and checklist
- 12. Case studies: Lean Six Sigma applications
- 12.1 Defect reduction in injection molding production components
- 12.1.1 Define phase
- 12.1.2 Measure phase
- 12.1.3 Analyze phase
- 12.1.4 Improve phase
- 12.1.5 Control phase
- 12.2 Overall equipment effectiveness: a process analysis
- 12.2.1 Define phase
- 12.2.2 Measure phase
- 12.2.3 Analyze phase
- 12.2.4 Improve phase
- 12.2.5 Control phase
- 12.3 Powder coat improvement
- 12.3.1 Define phase
- 12.3.2 Measure phase
- 12.3.3 Analyze phase
- 12.3.4 Improve phase
- 12.3.5 Control phase
- Appendices
- Appendix I. Highlights of symbols and abbreviations
- Appendix II. Statistical tables and formulas
- Appendix III. Values of y = exp(-[nu])
- Appendix IV. DPMO to sigma to yield% conversion table
- Appendix V. Standard normal distribution
- Appendix VI. Critical values of T (T -distribution)
- Appendix VII. Critical values of chi-square distribution with degrees of freedom
- Appendix VIII. Upper critical values of the f-distribution
- Appendix IX. Cumulative Poisson probability distribution table
- Appendix X. Cumulative binomial probability distribution
- Appendix XI. Confidence interval for population proportion: small sample
- Appendix XII. Scorecard for performance reporting
- Bibliography
- Index.