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Produktbild: The Lean Six Sigma Pocket Toolbook
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The Lean Six Sigma Pocket Toolbook A Quick Reference Guide to 70 Tools for Improving Quality and Speed

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19,99 € UVP 23,75 €

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

16.08.2004

Abbildungen

Illustrations

Verlag

McGraw-Hill Education Ltd

Seitenzahl

282

Maße (L/B/H)

20,3/12,6/1,7 cm

Gewicht

286 g

Farbe

Weiß / Ozeanblau

Sprache

Englisch

ISBN

978-0-07-144119-3

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

16.08.2004

Abbildungen

Illustrations

Verlag

McGraw-Hill Education Ltd

Seitenzahl

282

Maße (L/B/H)

20,3/12,6/1,7 cm

Gewicht

286 g

Farbe

Weiß / Ozeanblau

Sprache

Englisch

ISBN

978-0-07-144119-3

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: gpsr@libri.de

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  • Produktbild: The Lean Six Sigma Pocket Toolbook

  • Chapter 1: Using DMAIC to Improve Speed, Quality, and Cost
    Define
    Measure
    Analyze
    Improve
    Control
    Kaizen DMAIC
    Project selection
    Chapter 2: Working With Ideas
    Brainstorming
    Affinity diagrams
    Multivoting
    Chapter 3: Value Stream Mapping and Process Flow Tools
    Process mapping
    Process observation
    SIPOC
    Process mapping steps
    Transportation and spaghetti (workflow) diagrams
    Swim-lane (deployment) flowcharts
    Value stream maps (basic)
    Flowchart and value stream symbols
    Value-add (VA) vs. non-value-add (NVA) analysis
    Time value maps
    Value-add chart (task time or takt time chart)
    Chapter 4: Voice of the Customer (VOC)
    Customer segmentation
    Sources of customer data
    Collecting VOC: Interviews
    Collecting VOC: Point-of-use observation
    Collecting VOC: Focus groups
    Collecting VOC: Surveys
    Kano analysis
    Developing critical-to-quality requirements
    Chapter 5: Data Collection
    Types of data
    Input vs. output data
    Data collection planning
    Measurement selection matrix
    Stratification factors
    Operational definitions
    Cautions on using existing data
    Making a checksheet
    Basic checksheets
    Frequency plot checksheet
    Traveler checksheet
    Location checksheet
    Sampling basics
    Factors in sample selection
    Stable process (and population) sampling
    Formulas for determining minimum sample size (population or stable process)
    Measurement System Analysis (MSA) and Gage R&R Overview
    Gage R&R: Collecting the data
    Interpreting Gage R&R Results
    MSA: Evaluating bias
    MSA: Evaluating stability
    MSA: Evaluating discrimination
    MSA for attribute/discrete data
    Chapter 6: Descriptive Statistics and Data Displays
    Statistical term conventions
    Measures of central tendency (mean, median, mode)
    Measures of spread (range, variance, standard deviation)
    Boxplots
    Frequency plot (histogram
    Normal distribution
    Non-normal distributions and the Central Limit Theorem
    Chapter 7: Variation Analysis
    Review of variation concepts
    Time series plots (Run charts)
    Run chart table
    Control chart basics
    Selecting a control chart
    Control charts for continuous data
    Subgrouping for continuous data
    Control limit formulas for continuous data
    Factors for Control Chart Formulas
    Creating an ImR Chart
    Creating X,R charts or X,S charts
    Control charts for attribute data
    Creating p-, np-, c-, and u-charts
    Control limit formulas for attribute data
    Assumptions for interpreting control charts
    Interpreting control charts (Tests for Special Cause Variation)
    Background on process capability calculations
    Confusion in short-term vs. long-term process capability calculations
    Calculating process capability
    Chapter 8: Identifying and Verifying Causes
    PART A: Identifying potential causes
    Pareto charts
    5 Whys
    Cause-and-effect diagrams (fishbone or Ishikawa diagrams)
    C&E Matrix
    PART B: Tools for confirming causal effects
    Stratified data charts
    Testing quick fixes or obvious solutions
    Scatter plots
    Hypothesis testing overview
    Confidence intervals
    Type I and Type II errors, Confidence, Power, and p-values
    Confidence intervals and sample size
    t-test Overview
    1-Sample t-test
    2-Sample t-test
    Overview of correlation
    Correlation statistics (coefficients)
    Regression overview
    Simple linear regression
    Multiple regression
    ANOVA (ANalysis Of VAriance)
    One-way ANOVA
    Degrees of Freedom
    ANOVA assumptions
    Two-way ANOVA
    Chi-Square test
    Design of Experiments (DOE) notation and terms
    Planning a designed experiment
    DOE: Full-factorial vs.
    Fractional-factorials (and notations)
    Interpreting DOE results
    Chapter 9: Reducing Lead Time and Non-Value-Add Cost
    Basic Lean concepts
    Metrics of time efficiency
    Time Traps vs. Capacity Constraints
    Identifying Time Traps and Capacity Constraints
    5S Overview
    Implementing 5S
    Generic Pull System
    Replenishment Pull Systems
    Two-Bin Replenishment System
    Computing minimum safe batch sizes
    Four Step Rapid Setup Method
    Adapting Four Step Rapid Setup for service processes
    Total Productive Maintenance (TPM)
    Mistake proofing & prevention (Poka-yoke)
    Process balancing design principles
    Work cell optimization
    Visual Process Controls
    Chapter 10: Complexity Value Stream Mapping and Complexity Analysis
    Product/service family grid
    Complexity Value Stream Map (CVSM)
    Process Cycle Efficiency (PCE)
    The Complexity Equation
    Complexity matrix
    PCE destruction calculations (for a Complexity Matrix)
    Substructure analysis
    "What-if" analyses with Complexity Matrix data
    Chapter 11: Selecting and Testing Solutions
    Sources of solution ideas
    Benchmarking
    Tips on solution selection
    Developing and using evaluation criteria
    Solution selection matrix
    Pairwise ranking
    Cost evaluation
    Impact/effort matrix
    Pugh matrix
    Other evaluation techniques
    Controls assessment matrix
    Failure Modes and Effects Analysis (FMEA)
    Pilot testing
    Index