Mastering Lean Six Sigma : advanced black belt concepts /

Lean Six Sigma is all about dramatically improving organizational performance. It requires a roadmap, mentoring, teaching, coaching, and training in Six Sigma methodologies. This book gives you those tools, along with practical examples and case studies to achieve the goals of improved customer sati...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Taghizadegan, Salman, 1957-
Formato: Electrónico eBook
Idioma:Inglés
Publicado: [New York, N.Y.] (222 East 46th Street, New York, NY 10017) : Momentum Press, 2013.
Temas:
Six sigma (Quality control standard)
Lean manufacturing.
Production management > Quality control.
Six Sigma.
Production allégée.
Production > Gestion > Qualité > Contrôle.
BUSINESS & ECONOMICS > Industrial Management.
BUSINESS & ECONOMICS > Management.
BUSINESS & ECONOMICS > Management Science.
BUSINESS & ECONOMICS > Organizational Behavior.
Lean manufacturing
Production management > Quality control
Mastering Lean Six Sigma
Advanced Black Belt concepts
Lean Six Sigma mastering
Six Sigma Define Concepts and Strategies
Six Sigma Measure Concepts and Strategies
Six Sigma Analysis Concepts and Strategies
Six Sigma improve Concepts and Strategies
Six Sigma Control Concepts and Strategies
Lean Six Sigma Roadmap
Acceso en línea:Texto completo
Tabla de Contenidos:
  • 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.

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