Cover image for Process quality control: troubleshooting and interpretation of data
Title:
Process quality control: troubleshooting and interpretation of data
Author:
Ott, Ellis R. (Ellis Raymond), 1906-
Edition:
Third edition.
Publication Information:
New York : McGraw Hill, [2000]

©2000
Physical Description:
xxiii, 596 pages : illustrations ; 24 cm + 1 computer laser optical disc (4 3/4 in.)
Language:
English
ISBN:
9780071350105
Format :
Book

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Central Library TS156 .O86 2000 Book and Software Set Central Closed Stacks
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Summary

Summary

Troubleshooting tool for manufacturing processes.A hands-on, solutions-oriented guide, Process QualityControl, Third Edition, by Ellis R, Ott, Edward G.Schilling, and Dean V. Neubauer, gives you a systematicapproach to gathering and analyzing data fortroubleshooting manufacturing processes. This classicemphasizes short term and long term variability, particularly with regard to process capability andperformance. The third edition gives you many newanalytical methods, insights into their application, andcase studies. These techniques include toleranceintervals, a test for the comparison of long term andshort term variation, simplified attribute sample sizedetermination, and an updated discussion of sampling.You'll also find an expanded discussion of control charts, including trend charts, manual adjustment charts, andshort run charts. While the emphasis is on processcontrol, you'll also find significant material on analysis of means.


Table of Contents

Case Historiesp. xiii
Preface to the Third Editionp. xv
Preface to the Second Editionp. xix
Preface to the First Editionp. xxiii
Part 1 Basics of Interpretation of Data
Chapter 1. Variables Data: An Introductionp. 3
1.1 Introduction--An Experience with Datap. 3
1.2 Variabilityp. 5
1.3 Organizing Datap. 7
1.4 Grouping Data When n is Largep. 8
1.5 The Arithmetic Average or Mean--Central Valuep. 11
1.6 Measures of Variationp. 12
1.7 Normal Probability Plotsp. 18
1.8 Prediction Regarding Sampling Variation: The Normal Curvep. 20
1.9 Series of Small Samples from a Production Processp. 27
1.10 Changes in Sample Size: Predictions about X and [sigma]p. 28
1.11 How Large a Sample Is Needed to Estimate a Process Average?p. 30
1.12 Sampling and a Second Method of Computing [sigma]p. 31
1.13 Some Important Remarks about the Two Estimatesp. 34
1.14 Stem-and-Leafp. 36
1.15 Box-Plotsp. 37
1.16 Tolerance Intervals for Populationsp. 39
1.17 A Note on Notationp. 41
1.18 Summaryp. 43
1.19 Practice Exercisesp. 43
Chapter 2. Ideas from Time Sequences of Observationsp. 53
2.1 Introductionp. 53
2.2 Data from a Scientific or Production Processp. 56
2.3 Signals and Risksp. 57
2.4 Run Criteriap. 59
2.5 Shewhart Control Charts for Variablesp. 65
2.6 Probabilities Associated with an X-Control Chart: Operating-Characteristic Curvesp. 74
2.7 Control Charts for Trendsp. 91
2.8 Practice Exercisesp. 99
Chapter 3. Ideas from Outliers--Variables Datap. 105
3.1 Introductionp. 105
3.2 Other Objective Tests for Outliersp. 109
3.3 Two Suspected Outliers on the Same End of a Sample of n (Optional)p. 111
3.4 Practice Exercisesp. 113
Chapter 4. Variability--Estimating and Comparingp. 115
4.1 Introductionp. 115
4.2 Statistical Efficiency and Bias in Variability Estimatesp. 115
4.3 Estimating [sigma] and [sigma superscript 2] from Data: One Sample of Size np. 117
4.4 Data from n Observations Consisting of k Subsets of n[subscript g] = r: Two Proceduresp. 118
4.5 Comparing Variabilities of Two Populationsp. 120
4.6 Summaryp. 129
4.7 Practice Exercisesp. 131
Chapter 5. Attributes or Go No-Go Datap. 133
5.1 Introductionp. 133
5.2 Three Important Problemsp. 133
5.3 On How to Samplep. 143
5.4 Attributes Data Which Approximate a Poisson Distributionp. 145
5.5 Practice Exercisesp. 153
Part 2 Statistical Process Control
Chapter 6. On Sampling to Provide a Feedback of Informationp. 157
6.1 Introductionp. 157
6.2 Scientific Sampling Plansp. 159
6.3 A Simple Probabilityp. 160
6.4 Operating-Characteristic Curves of a Single Sampling Planp. 160
6.5 But Is it a Good Plan?p. 161
6.6 Average Outgoing Quality (AOQ) and Its Maximum Limit (AOQL)p. 163
6.7 Computing the Average Outgoing Quality (AOQ) of Lots from a Process Producing P Percent Defectivep. 164
6.8 Other Important Concepts Associated with Sampling Plansp. 167
6.9 Risksp. 167
6.10 Tabulated Sampling Plansp. 168
6.11 Feedback of Informationp. 169
6.12 Where Should Feedback Begin?p. 172
6.13 Outgoing Product Quality Rating (OPQR)p. 173
6.14 Practice Exercisesp. 190
Chapter 7. Narrow-Limit Gauging in Process Controlp. 191
7.1 Introductionp. 191
7.2 Outline of an NL-Gauging Planp. 192
7.3 Selection of a Simple NL-Gauging Sampling Planp. 193
7.4 Sequential NL-Gauging Plansp. 198
7.5 OC Curves of NL-Gauge Plansp. 201
7.6 Hazardsp. 204
7.7 Selection of an NL-Gauge Planp. 208
7.8 Practice Exercisesp. 209
Chapter 8. On Implementing Statistical Process Controlp. 211
8.1 Introductionp. 211
8.2 Key Aspects of Process Quality Controlp. 212
8.3 Process Controlp. 213
8.4 Uses of Control Chartsp. 215
8.5 Rational Subgroupsp. 216
8.6 Special Control Chartsp. 216
8.7 Median Chartp. 216
8.8 Standard Deviation Chartp. 220
8.9 Acceptance Control Chartp. 221
8.10 Modified Control Limitsp. 224
8.11 Arithmetic and Exponentially Weighted Moving Average Chartsp. 226
8.12 Cumulative Sum Chartsp. 229
8.13 Precontrolp. 243
8.14 Narrow Limit Control Chartsp. 246
8.15 How to Apply Control Chartsp. 246
8.16 Other Control Chartsp. 250
8.17 Process Capabilityp. 262
8.18 Process-Optimization Studiesp. 262
8.19 Capability and Specificationsp. 264
8.20 Process Performancep. 268
8.21 Process Improvementp. 271
8.22 Process Changep. 271
8.23 Problem Identificationp. 272
8.24 Prioritizationp. 273
8.25 Summaryp. 275
8.26 Practice Exercisesp. 276
Part 3 Troubleshooting and Process Improvementp. 280
Chapter 9. Some Basic Ideas and Methods of Troubleshootingp. 281
9.1 Introductionp. 281
9.2 Some Types of Independent and Dependent Variablesp. 282
9.3 Some Strategies in Problem Finding, Problem Solving, and Troubleshootingp. 284
9.4 Bicking's Checklistp. 289
9.5 Practice Exercisesp. 289
Chapter 10. Some Concepts of Statistical Design of Experimentsp. 293
10.1 Introductionp. 293
10.2 Effectsp. 294
10.3 Sums of Squaresp. 297
10.4 Yates Methodp. 299
10.5 Blockingp. 304
10.6 Fractional Factorialsp. 304
10.7 Graphical Analysis of 2[superscript p] Designsp. 307
10.8 Conclusionp. 312
10.9 Practice Exercisesp. 315
Chapter 11. Troubleshooting with Attributes Datap. 319
11.1 Introductionp. 319
11.2 Ideas from Sequences of Observations over Timep. 320
11.3 Decision Lines Applicable to k Points Simultaneouslyp. 321
11.4 Analysis of Means for Proportionsp. 329
11.5 Example--Proportionsp. 330
11.6 Analysis of Means for Count Datap. 330
11.7 Example--Count Datap. 331
11.8 Introduction to Case Historiesp. 332
11.9 One Independent Variable with k Levelsp. 333
11.10 Two Independent Variablesp. 342
11.11 Three Independent Factorsp. 354
11.12 A Very Important Experimental Design: 1/2 [times] 2[superscript 3]p. 367
11.13 Case History Problemsp. 371
11.14 Practice Exercisesp. 376
Chapter 12 Special Strategies in Troubleshootingp. 379
12.1 Ideas from Patterns of Datap. 379
12.2 Disassembly and Reassemblyp. 383
12.3 A Special Screening Program for Many Treatmentsp. 387
12.4 Other Screening Strategiesp. 393
12.5 Relationship of One Variable to Anotherp. 393
12.6 Use of Transformations and ANOMp. 397
12.7 Practice Exercisesp. 405
Chapter 13. Comparing Two Process Averagesp. 407
13.1 Introductionp. 407
13.2 Tukey's Two-Sample Test to Duckworth's Specificationsp. 407
13.3 Analysis of Means, k = 2, n[subscript g] = r[subscript 1] = r[subscript 2] = rp. 409
13.4 Student's t and F Test Comparison of Two Stable Processesp. 411
13.5 Magnitude of the Difference between Two Meansp. 413
13.6 Practice Exercisesp. 422
Chapter 14. Troubleshooting with Variables Datap. 425
14.1 Introductionp. 425
14.2 Suggestions in Planning Investigations--Primarily Remindersp. 426
14.3 A Statistical Tool for Process Changep. 427
14.4 Analysis of Means for Measurement Datap. 428
14.5 Example--Measurement Datap. 430
14.6 Analysis of Means: A 2[superscript 2] Factorial Designp. 431
14.7 Three Independent Variables: A 2[superscript 3] Factorial Designp. 438
14.8 Computational Details for Two-Factor Interactions in a 2[superscript 3] Factorial Designp. 444
14.9 A Very Important Experimental Design: 1/2 [times] 2[superscript 3]p. 445
14.10 General ANOM Analysis of 2[superscript p] and 2[superscript p-1] Designsp. 451
14.11 Practice Exercisesp. 453
Chapter 15. More Than Two Levels of an Independent Variablep. 457
15.1 Introductionp. 457
15.1 An Analysis of k Independent Samples--Standard Given--One Independent Variablep. 458
15.3 An Analysis of k Independent Samples--No Standard Given--One Independent Variablep. 459
15.4 Analysis of Means--No Standard Given--More Than One Independent Variablep. 464
15.5 Analysis of Two-Factor Crossed Designsp. 465
15.6 The Relation of Analysis of Means to Analysis of Variance (Optional)p. 472
15.7 Analysis of Fully Nested Designs (Optional)p. 474
15.8 Analysis of Means for Crossed Experiments--Multiple Factorsp. 479
15.9 Nested Factorial Experiments (Optional)p. 493
15.10 Multifactor Experiments with Attributes Datap. 493
15.11 Analysis of Means When the Sample Sizes Are Unequalp. 499
15.12 Comparing Variabilitiesp. 500
15.13 Nonrandom Uniformityp. 505
15.14 Development of Analysis of Meansp. 508
15.15 Practice Exercisesp. 517
Chapter 16. What's on the CDp. 519
Chapter 17. Epiloguep. 531
Appendix Tablesp. 539
Indexp. 575

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