World Class Quality

World Class Quality
اسم المؤلف
Keki R. Bhote, Adi K. Bhote
التاريخ
24 سبتمبر 2021
المشاهدات
التقييم
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World Class Quality
SECOND EDITION
Using Design of Experiments to Make It Happen
Keki R. Bhote, Adi K. Bhote
Contents
List of Figures ix
List of Tables xiii
Foreword by Bob Galvin xvii
Preface to the Second Edition xix
Acknowledgments xxiii
Part I Introduction

  1. The Need for and Objectives and Benefits of
    Design of Experiments 3
  2. Fads, Potions, Nostrums of the Quality
    Movement in the Last 50 Years 10
  3. A Powerful Tool Kit for the 21st Century 19
    Part II Preamble to the Design of Experiments
  4. The Measurement of Process Capability 51
  5. Variation: An Industrial Epidemic 65
  6. The Three Approaches to DOE: Classical,
    Taguchi, and Shainin 73
  7. A Synopsis of the 10 Powerful DOE Tools 86
    Part III ‘‘Talking to the Parts’’—A Set of Clue-Generating
    Tools
  8. The Multi-Vari Analysis: Homing In on the
    Red X 107
    vvi Contents
  9. The Concentration Chart: Pinpointing
    Locations of Repetitive Problems 147
  10. Components Search: Simple, Smooth
    Swapping 157
  11. Paired Comparisons: An Elegant, Versatile
    Tool 194
  12. Product/Process Search: Pinpointing Process
    Variables 217
    Part IV Formal Design of Experiments Techniques to
    Characterize a Product/Process
  13. Variables Search: The Rolls Royce in the Search
    for the Red X 233
  14. The Full Factorial: Purest Technique for
    Separating and Quantifying Each Interaction
    Effect 282
  15. B versus C: An Excellent Validation Technique 309
    Part V DOE Optimization
  16. Scatter Plots to Achieve Realistic Specifications
    and Tolerances 335
  17. Response Surface Methodology (RSM): To
    Optimize Interactions 355
    Part VI The Transition From DOE to SPC: Vital
    Disciplines
  18. Positrol: Freezing Process Gains 369
  19. Process Certification: Eliminating Peripheral
    Causes of Poor Quality 378
    Part VII Statistical Process Control: For Monitoring
    Quality
  20. Control Charts: A Technique Whose Time Has
    Gone 393
  21. Pre-Control: A Technique Whose Time Has
    Come 399Contents vii
    Part VIII Linkage of DOE to Reliability
  22. Multiple Environment Over Stress Tests: As
    Effective for Reliability as DOE Is for Quality 421
    Part IX A Logical Sequence in the Use of DOE Tools
  23. Case Studies in Sequential DOE Tools to Solve
    Chronic Problems 445
    Part X From Classroom Instruction to True Learning on
    the Job
  24. Learning by Doing 467
    References 479
    Index 4
    Contents
    List of Figures ix
    List of Tables xiii
    Foreword by Bob Galvin xvii
    Preface to the Second Edition xix
    Acknowledgments xxiii
    Part I Introduction
  25. The Need for and Objectives and Benefits of
    Design of Experiments 3
  26. Fads, Potions, Nostrums of the Quality
    Movement in the Last 50 Years 10
  27. A Powerful Tool Kit for the 21st Century 19
    Part II Preamble to the Design of Experiments
  28. The Measurement of Process Capability 51
  29. Variation: An Industrial Epidemic 65
  30. The Three Approaches to DOE: Classical,
    Taguchi, and Shainin 73
  31. A Synopsis of the 10 Powerful DOE Tools 86
    Part III ‘‘Talking to the Parts’’—A Set of Clue-Generating
    Tools
  32. The Multi-Vari Analysis: Homing In on the
    Red X 107
    vvi Contents
  33. The Concentration Chart: Pinpointing
    Locations of Repetitive Problems 147
  34. Components Search: Simple, Smooth
    Swapping 157
  35. Paired Comparisons: An Elegant, Versatile
    Tool 194
  36. Product/Process Search: Pinpointing Process
    Variables 217
    Part IV Formal Design of Experiments Techniques to
    Characterize a Product/Process
  37. Variables Search: The Rolls Royce in the Search
    for the Red X 233
  38. The Full Factorial: Purest Technique for
    Separating and Quantifying Each Interaction
    Effect 282
  39. B versus C: An Excellent Validation Technique 309
    Part V DOE Optimization
  40. Scatter Plots to Achieve Realistic Specifications
    and Tolerances 335
  41. Response Surface Methodology (RSM): To
    Optimize Interactions 355
    Part VI The Transition From DOE to SPC: Vital
    Disciplines
  42. Positrol: Freezing Process Gains 369
  43. Process Certification: Eliminating Peripheral
    Causes of Poor Quality 378
    Part VII Statistical Process Control: For Monitoring
    Quality
  44. Control Charts: A Technique Whose Time Has
    Gone 393
  45. Pre-Control: A Technique Whose Time Has
    Come 399Contents vii
    Part VIII Linkage of DOE to Reliability
  46. Multiple Environment Over Stress Tests: As
    Effective for Reliability as DOE Is for Quality 421
    Part IX A Logical Sequence in the Use of DOE Tools
  47. Case Studies in Sequential DOE Tools to Solve
    Chronic Problems 445
    Part X From Classroom Instruction to True Learning on
    the Job
  48. Learning by Doing 467
    References 479
    Index
    acceptable quality level (AQL), 10
    accuracy, of measurement, 97–102
    affinity diagram, 26
    alpha () risk, 313, 315, 404
    analysis of variance (ANOVA), 83
    arrow diagram, 27
    attributes, conversion from, 102
    B versus C: 309–22; alpha () risk, 313,
    315; applications in administrative
    services, 329; beta () risk, 313–17;
    confidence, risk, and end-count,
    317; importance of validation, 309;
    increasing sample sizes to reduce
    B and C separation, 320; more than
    two alternatives, 323; opinion surveys, 330; overlap and no overlap
    rules, 316; stress test to failure, 327;
    when C is worse than B, 323
    baby sigma practices, 17
    balance, in experimentation, 283
    ball park stage, 161
    benchmarking, 34–36
    beta () risk, 313, 315, 317, 406
    Bhote, Keki, 14, 477, 478
    Big Q (Bhote) Quality System, 14
    brainstorming, 4, 16, 22
    business excellence, 17
    business process engineering, 40
    capability, process, 51–64, 401
    case studies: appliance servicer, 278;
    automotive styling, 330; bubbles in
    glass, 223; bushing, 394; car com-
    481
    pany’s ice cream fiasco, 178–82;
    contact lens, 266; cracked epoxy,
    260, 317; customer loyalty/satisfaction/profit, 351; customer services at hotel, 141; dairy farm
    bacteria levels, 211; Dendermonde,
    Belgium, 475–76; die casting, 376;
    disc brake, 309; dome tweeter sensitivity, 457–64; edge defects in
    contact lenses, 336; electric razor,
    103; foam leaks in refrigerator
    door, 148; Ford versus Mazda, 52;
    four megabit dynamic RAM, 203;
    F-16 fighter jet, 53; gear train
    motor, 327; hospital billing errors,
    140; hourmeter, 165; ignition amplifier, 343; instrument intermittency, 274; lettuce bag leakage,
    220; maximizing Schottky diode
    yields, 357; micro-motor noise,
    199; moire effect minimization,
    295; Motorola six sigma, 76–79;
    Nippon Telegraph & Telephone
    (NTT), 53; non-firing burner, 177;
    operator performance differences,
    189; pick and place machine, 273;
    plastic injection molding machine,
    373; press brake, 250, 320; radio
    ‘‘no trouble found,’’ 126; refrigerator door gaps, 187; rotor shaft, 121;
    SCAP metallization, 384; sensor
    capacitance, 396; shorted horizontal output transistor, 154; software
    applications, 271; spring torque482 Index
    difference, 189; ‘‘tombstone’’ defects, 139, 265; travel motor, 273;
    university recruitment drive, 155;
    wave solder defects, 148, 288,
    447–57
    cause and effect diagrams: CEDAC, 23,
    24; futility, 109, 110; Ishikawa, 109,
    110
    circuit analysis, 3
    classical DOE, 70, 73–85, 235
    combination formula, 197, 312
    commodity teams, 42
    comparison of three DOE approaches,
    73–85
    Components Search: 157–93; applications in administrative work, 196;
    applications in processes/lines,
    188; applications when disassembly/re-assembly not repeatable,
    186; bypassing the Multi-Vari, 158;
    capping run, 162, 164; decision
    limits, 167; determining correct
    specifications, 176; factorial analysis, 173; four stages of, 161; graphical plots, 167; main and interaction
    effects, 171; prerequisites, 162; procedure in 12 steps, 163–64; quiz:
    ‘‘find the Red X ball,’’ 190–92
    computer simulation: 3, 5, 69, 73;
    Monte Carlo, 70, 73
    Concentration Chart: 147–56; applications in administrative work,
    154–55; construction of, 147–48;
    ‘‘measles’’ chart, 147
    confounding, 235–36
    control charts: disadvantages vis-a`-vis
    Pre-Control, 412, 413; history, 393;
    slip-shod practices, 397–98; weaknesses, 393–97
    correlation, 351–53
    cost of poor quality, 7, 54, 76
    cost reduction, 7, 8, 78
    C
    p, Cpk: 5, 7, 12, 54–64; calculations, formulas, 54–59; correction factor, K,
    57; pitfalls to avoid, 59–60; relationship between Cp, ppm, and
    sigma, 56
    culture, problem solving: 467–78; conversion of the design engineer,
    472; energizing, 468; learning by
    doing, 467–75; line worker contribution, 475; managing complex
    change, 468; practice, practice,
    practice, 467; skunk works, 475;
    top management commitment, 469
    customer: internal customer, 39, 40;
    loyalty/satisfaction, 7, 9, 351–53;
    mass customization, 32; Next Operation as Customer, 3, 5, 36, 39,
    40; quality function deployment,
    29, 32
    cycle-time reduction: 6–9, 39–46; flow
    charting, 40, 42; MRP II, 45, 46;
    push-pull, 45
    data collection/analysis, 20
    decision limits, 167
    Deming, Dr. W. Edwards, 65, 380, 476,
    477
    design engineering: conversion of, 472,
    473; DOE in design, 233–81,
    335–54; importance of DOE to, 7,
    8; ‘‘parts are smarter than the engineers,’’ 7, 8; product/process characterization, 5, 233–81; product/
    process optimization, 5, 335–54;
    traditional approach to problem
    solving, 28
    Design of Experiments (DOE): benefits,
    7–9; block diagram, 87; case studies, see case studies; classical DOE,
    74–85; clue generation techniques,
    105–6; comparison of three DOE
    approaches, 73–85; Components
    Search, see Components Search;
    continuum of linked tools, 445–64;
    C
    p, Cpk, see Cp, Cpk; Evolutionary
    Operation (EVOP), 351–61; fraction factorials: weaknesses,
    234–40; Full Factorials, see Full
    Factorial; generic problem-solving
    framework, 89; Green Y, 93; instrumentation accuracy, 109–13; logical sequence in DOE, 445–64;Index 483
    Multi-Vari analysis, see Multi-Vari
    analysis; need for, 3–5; objectives,
    6, 7; Paired Comparisons, see
    Paired Comparisons; Pale Pink X,
    93; Pink X, 93; Positrol, see Positrol;
    problem-solving roadmap, 95;
    Process Certification, see Process
    Certification; product/process
    characterization, 3, 5, 33, 317, 318;
    product/process optimization, 3,
    5, 33, 429; Product/Process Search,
    see Product/Process Search; randomization, 81, 284; Red X, 93;
    replication, 283; Response Surface
    Methodology, see Response Surface Methodology; root cause
    identification, 445; simplex,
    361–63; Taguchi DOE, see Taguchi
    DOE; ten DOE tools summary,
    90–92; three approaches to DOE,
    74–85; Variables Search, see Variables Search; workshop exercises,
    see workshop exercises; workshops in DOE, 470–72
    destruct limits, 429
    early supplier involvement (ESI), 42
    8-D, see under Ford
    elimination stage, 161
    employees: brain fertility, 474; error
    cause removal, 379; human shortcomings, 380, 383; involvement,
    28, 77; joy in the workplace, 476,
    477; Kaizen, 28; morale, 6, 8, 9,
    473–77; Quality Circles, 28; skunk
    works, 475; Total Customer Satisfaction competition, 78
    end-counts, 196, 201
    environmental neglect, 379, 382
    equipment inattention, 379, 382
    error cause removal (ECR), 379
    errors: type I and II, 313
    European Quality Award, 11, 12, 15
    Evolutionary Operation (EVOP),
    351–61
    excellence, business, 14, 17
    factorial analysis, 173, 246
    factory overall efficiency (FOE), 33
    failure mode effects analysis, 5, 6, 422
    Fisher, Sir Ronald, 74
    flow chart, 40
    Ford: 25, 52–53, 74, 88; 8-D, 25, 74, 88;
    versus Mazda, 52; fraction factorials: weaknesses, 234–40
    frequency distributions, 21
    Full Factorial: 234, 287–308; balance,
    283; fraction factorials: weaknesses, 234–40; limitations, 282;
    methodology, 287; objectives, 283;
    principles, 283; randomization, 81,
    284; replication, 287
    fundamental weaknesses of classical
    and Taguchi DOE, 78–85
    Galvin, Robert W., 76, 77, 468
    glass wall management, 381
    good manufacturing practices, 379, 381
    graphics, 20
    Green Y, 93
    Highly Accelerated Life Tests (HALT),
    427–30, 437–39
    Highly Accelerated Stress Screens
    (HASS), 430, 437–39
    histograms, 21
    House of Quality, 30, 31
    improvement, quality, 5, 7, 8, 9
    improvement, reliability, 5, 7
    Institute of Environmental Science
    guidelines, 422
    interaction effects, 393–98
    internal customer, 39, 40
    ISO-9000, 11, 381
    Japanese, 19, 28
    Japanese seven management tools, 19,
    25–27
    Juran, Dr. Joseph M., 65, 89
    Kaizen, 19, 381
    Kepner-Tragoe, 4, 74, 78484 Index
    leadership, of Bob Galvin, 76, 77, 468
    learning by doing, 467–77
    Likert scale, 102–4, 114
    log, Positrol, 370
    logical sequence of DOE tools, 443–64
    main effects, 393–98
    Malcolm Baldrige National Quality
    Award, 11, 15
    management: commitment and
    involvement, 469–72; comparison
    of three quality systems, 15–18;
    poor management, 65, 66, 379–81;
    production management, 473, 474;
    quality management, 473; seven
    tools of Japanese management, 19,
    25–27, 70
    manufacturing management: 379–82,
    473, 474; actions required, 473, 474;
    poor manufacturing practices, 65–
    68, 379–82
    mass customization, 32
    matrix diagram, 27
    Mazda versus Ford, 52
    ‘‘measles’’ chart, 147
    measurement: accuracy check list, 101,
    116–18; bias, precision, discrimination, 98; Likert scale, 102–4
    measurement accuracy, 97–102
    Motorola: cost of poor quality, 76; Galvin, Bob, 76–77; quality improvement 10:1 to 1,000:1, 76–78; six
    sigma, 12, 75–78
    Multiple Environment Over Stress Test
    (MEOST): HALT/HASS versus
    MEOST, 437–39; history, objectives, benefits, 430–33; maximum
    practical over stress limit, 430;
    methodology, a roadmap, 433–34;
    seven stages, 434–38; tie-in with
    DOE, 438, 440
    multiple regression analysis, 351
    Multi-Vari analysis: 107–46; applications in administrative work, 140;
    card trick analogy, 107–9; constructing a Multi-Vari chart,
    119–21; designing/conducting a
    Multi-Vari study, 112–14; family
    tree, 113–16; principles, 107–9;
    sample sizes and frequency,
    114–16; three families of variation,
    111–12
    Next Operation As Customer (NOAC),
    39, 40
    nonparametric experiments, 309–22
    no overlap technique, 316
    null hypothesis, 311
    numeric scale, converting attributes to,
    102–4
    operator certification, 381
    operator errors, 71
    optimization of products/processes,
    335–54
    orthogonal array, 79, 234
    out-of-box thinking, 40
    overlap technique, 316
    Paired Comparisons: 194–216; applications in administrative services,
    210; combination formulas, 197,
    312; methodology: A and B, 195;
    Tukey test, 196, 207
    Pale Pink X, 89, 93
    Pareto’s law/principle, 22, 89, 90, 94
    Peterson, Don, 53
    Pink X, 89, 93
    Plan, do, check, act (PDCA), 20
    positional variation, 111
    Positrol: 89, 369–77; chart, 370; concept,
    369; plan, 369
    Pre-Control: 6, 399–418; advantages
    over control charts, 410; alpha ()
    risk, 404; beta () risk, 406; charting, 408; discovery, 399; mechanics, 400; modifications, 403;
    opposition to, 409; theory, 404
    problem solving: chronic, 6; culture,
    468–469; energizing a culture for,
    468; engineering approach, 28; generic process for, 97; prevention, 6,
    7; roadmap, 95; three approaches
    to, 73–85; worker involvement, 28Index 485
    process capability, 51–64, 402
    Process Certification: 378–90; audits,
    383; environmental neglect, 382;
    error cause removal (ECR), 381;
    good manufacturing practices violation, 381; methodology, 383;
    Murphy’s law, 378; operator certification, 381; peripheral causes of
    poor quality, 378–80; plant/equipment inattention, 382; scrubs, 383
    process mapping, 40
    productivity, 6
    product/process characterization, 3, 5,
    33, 317, 318
    product/process optimization, 3, 5, 33,
    429
    Product/Process Search: 217–30; methodology, 218; principles, 217;
    when individual process parameters cannot be measured, 219
    profitability, 6, 7, 8
    quality: acceptable quality level (AQL),
    10; ‘‘baby’’ six sigma system, 13,
    17; big Q (Bhote) quality system,
    14; cost of poor quality, 7, 54, 76;
    fads, 10–15; Ford 8-D, 25, 74, 88;
    House of Quality, 30, 31; improvement, 5, 7–9; ISO-9000, 11, 15;
    parts per billion (ppb) defects, 6;
    parts per million (ppm) defects, 6;
    poor systems and tools, 70; Quality Circles, 28; quality function deployment, 29–32; quality
    management, 473; QS-9000, 12, 15;
    relationship: Cp, sigma, and defect
    levels, 56; sampling plans, 10; six
    sigma systems, 12, 13, 16, 17; systems, comparisons of three, 17;
    Total Quality Management (TQM),
    12, 13, 17; ultimate six sigma, 13,
    17; yields, 6; zero defects movement, 10, 18
    Random Evolutionary Operation
    (REVOP), 363
    randomization, 81, 284
    rank order, 102, 196
    Rath and Strong, 399
    R chart, 394–96
    realistic tolerances, 335–54
    Red X, 89, 93
    reliability: failure mode effects analysis
    (FMEA), 5, 6, 422; fault tree analyses (FTA), 5; Highly Accelerated
    Life Tests (HALT), 427–30; importance of, 8, 9, 421; mass life testing,
    3, 422; Miner’s equation, 424; Multiple Environment Over Stress Test
    (MEOST), see MEOST; relationship
    of failure to stress, 424; reliability
    prediction studies, 5, 422; revolutionary test principles, 423–27;
    shortcomings in traditional reliability, 421; thermal cycling, 425;
    versus quality, 421; vibration,
    425–27
    Response Surface Methodology (RSM):
    355–66; approaches, 355; Evolutionary Operation (EVOP),
    356–61; objectives, 355; Random
    Evolutionary Operation (REVOP),
    363; simplex, 361–63
    Scatter Plots: 335–54; administrative
    applications, 350; correlations, 339;
    methodology, 337; multiple regression analysis, 351; objective,
    335; realistic specifications/tolerances, 335
    Shainin, Dorian, 75
    Shainin DOE, strengths, 74–85
    Shewhart, Walter, 393
    sigma, 56
    simplex, 361–63
    six sigma systems, 12, 13, 16, 17
    space reduction, 7, 8
    specifications: determining correct,
    176; determining realistic, 335–54;
    poor component, 68–70; poor
    product, 68–70; target values, 52,
    53; worst case tolerances, 4
    spider chart, 8, 9
    statistical process control (SPC): 6, 74,486 Index
    78, 391–418; control charts, 393–98;
    Pre-Control, 399–418; transition
    to, 391–418; stress test to failure,
    95, 438–41
    supply management: benefits, 7; commodity teams, 42; early supplier
    involvement (ESI), 42; importance
    of, 7–9; poor suppliers, 71–73
    support services, 39, 40
    table, of random numbers, 286
    Taguchi, Dr. Genichi, 75
    Taguchi DOE: 70, 75, 297, 298; comparisons with classical and Shainin
    DOE, 74–85; fundamental weaknesses, 78–85; orthogonal array,
    79, 234
    tally sheets, 21
    thermal cycling, 425
    tolerances: build-up, of, 54; geometric,
    4; important/unimportant parameters, 3; loose/tight, 40; realistic, 4,
    438–41; worst case, 4
    tools: awareness, implementation, 47;
    benchmarking, 35–36; brainstorming, 4, 16, 22; cause and effect diagrams, 23, 109, 110; CEDAC, 24;
    check sheets, 21; classical DOE, 70,
    73–85, 235; control charts, see control charts; cycle-time reduction,
    45–46; data collection/analysis,
    20; Design of Experiments (DOE),
    see Design of Experiments; Ford 8-
    D, 25, 74, 78, 88; graphs/charts, 20;
    histograms/frequency distributions, 21; interrelationship diagram, 26; Kepner-Tragoe, 4, 78;
    matrix diagram, 27; Multiple Environment Over Stress Test
    (MEOST), see MEOST; Next Operation As Customer (NOAC), see
    NOAC; Pareto charts, 22, 89, 92, 94;
    plan, do, check, act (PDCA), 20;
    Poka-Yoke, 36–38; Pre-Control, see
    Pre-Control; process decision program chart, 27; quality function
    deployment, 29–32; seven management tools, 19, 25–27, 70; seven
    tools of Q.C., 4, 19–24, 70; Shainin
    DOE, 74–85; statistical process
    control (SPC), see SPC; supply
    management, see supply management; Taguchi DOE, 70–75, 297,
    298; tally sheets, 21; tool kit for the
    21st century, 28–47; Total Productive Maintenance, 7, 8, 9, 32–34;
    transition from DOE to SPC, 95,
    369–90; tree diagram, 27; value engineering, total, 42–44
    Total Productive Maintenance (TPM),
    7, 8, 9, 32–34
    total quality management, 12–15
    Tukey test, 196, 207
    type I and II errors, 313
    ultimate six sigma, 13–14
    validation, 309
    value engineering, 42–44
    variation: evil, 48; industrial epidemic,
    65–72; poor management of,
    65–68; poor manufacturing practices, 70; poor specifications,
    68–70; poor suppliers, 71; target
    value, 50; temporal, 112
    Variables Search: 233–81; advantages
    over fraction factorials, 9, 234–40,
    283; analogy with medical/pharmaceutical work, 276; binary
    search, 240; capping run, 246; common mistakes, 254; decision limits,
    245; factorial analysis, 246; four
    stages, 241; graphical plots, 254;
    interaction effects, 247; methodology, 241; objectives, 239; product/
    process characterization, 248; software applications, 271; test of significance, 244; Variable Search plus
    Paired Comparisons, a derivative
    DOE technique, 271
    vibration tests, 425–27
    white-collar quality, cost, cycle time,
    35, 39, 40Index 487
    workers, see employees
    workshop exercises: belt passivator,
    133; bushing, 414; car company ice
    cream fiasco, 178; choice between
    four suppliers, 324; CNC lathe,
    374; contact lens, 201; digital circuit, 350; drilling operation, 298;
    engine control module, 256; infrared soldering, 345; light emitting
    diodes (LED), 63; memory chips,
    386; oscillator time delay, 183; outof-square grills, 204; paint defects
    on washing machine tub, 151;
    paint yield optimization, 293; plastic injection molding machine, 226;
    porcelain paint process, 385; press
    brake, 60; printed circuit board
    soldering, 374; Red X ball nos. 1
    and 2, 190; screen print, 261; semiconductor wafer, 116; sensor capacitance, 415; shaft distortion
    after heat treat, 153; spot welding,
    268; tile adhesion, 129; walking
    machine, 187; wire bond strength,
    319
    X bar charts, 394–96
    zero defects movement, 10–11, 18

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