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Montgomery D.C. — Introduction to Statistical Quality Control
Montgomery D.C. — Introduction to Statistical Quality Control



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Название: Introduction to Statistical Quality Control

Автор: Montgomery D.C.

Аннотация:

The trusted guide to the statistical methods for quality control.

Quality control and improvement is more than an engineering concern. Quality has become a major business strategy for increasing productivity and gaining competitive advantage. Introduction to Statistical Quality Control, Sixth Edition gives you a sound understanding of the principles of statistical quality control (SQC) and how to apply them in a variety of situations for quality control and improvement.

With this text, you'll learn how to apply state-of-the-art techniques for statistical process monitoring and control, design experiments for process characterization and optimization, conduct process robustness studies, and implement quality management techniques.

You'll appreciate the significant updates in the Sixth Edition including:
* In-depth attention to DMAIC, the problem-solving strategy of Six Sigma. It will give you an excellent framework to use in conducting quality improvement projects.
* New examples that illustrate applications of statistical quality improvement techniques in non-manufacturing settings. Many examples and exercises are based on real data.
* New developments in the area of measurement systems analysis
* New features of Minitab V15 incorporated into the text
* Numerous new examples, exercises, problems, and techniques to enhance your absorption of the material


Язык: en

Рубрика: Математика/

Статус предметного указателя: Готов указатель с номерами страниц

ed2k: ed2k stats

Издание: fifth edition

Год издания: 2005

Количество страниц: 759

Добавлена в каталог: 18.08.2008

Операции: Положить на полку | Скопировать ссылку для форума | Скопировать ID
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Предметный указатель
$2^{2}$ factorial design      567
$2^{3}$ factorial design      573 577
$2^{k-1}$ fractional factorial      595
$2^{k-p}$ fractional factorial      602
$2^{k}$ factorial design      573 585
$C_{pc}$      340 346
$C_{pk}$      338 341 345
$C_{pl}$      335 338
$C_{pm}$      34!
$C_{pn}$      335 338
$C_{p}$      203 333 334 336 337 344
$P_{pk}$      348
$P_{p}$      348
$s^{2}$ control chart      231
$\overline{x}$ and R chart for short runs      425
$\overline{x}$ control chart      180 194 196 197 200
100 percent inspection      647
Acceptable quality level (AQL)      654 673
Acceptance control charts      433
Acceptance number      648
Acceptance sampling      8 11 13 14 645
Accuracy of a gauge      357
Actions to improve a process      314
Actual process capability      338
Adaptive control charts      437 455
Addition of center points to a $2^{k}$ design      589
Aesthetics as a dimension of quality      3
Aliases      597 602
Alternate fraction      597
Alternative hypothesis      96
Analysis of variance (Anova)      128 130 131 135 136 358 560 579 580
Appraisal costs      30
Approximations to distributions      77—79 (see also “Normal distribution” “Binomial “Hypergeometric “Poisson
Assignable cause of variation      149
Attribute sampling plans      648 652 662 668 669 672 681
Attributes control charts      156 265 279 288 294 298 313 427
Attributes control charts for short runs      427
Attributes data      6 265 266 288 306 427 646
Attributes versus variables control chairs      306
audits      20 22
Autocorrelated process data      157 438 451 510 534
Autocorrelation function      440
Autoregrfessive integrated moving average (ARIMA) models      446 453
Average      see “Sample average” “Sample
Average outgoing quality (AOQ)      659
Average outgoing quality limit (AGQL)      661 681 682 703
Average run length (ARL)      160 218 220 236 287 288 386 395 396 398 411 412 435
Average sample number curve      665 672
Average time to signal (ATS)      161 221
Average total inspection (ATI)      661
Background noise in process      148
Bernoulli random variable      267
Bernoulli trials      57 92
Between-sample variability      207
Between/within control charts      246
Binomiai distribution      57 77 78 92 267 655
Black belts      26
Blocking      593
Bounded adjustment chart      536
Box plot      50
c chart      290
Cause-and-effect diagram      148 173 177 293 295
Censoreddata and control charts      476
Center line on a control chart      150
Central composite deign      617 620 621
Central limit theorem      65
Central tendency      52
Chain sampling plans      656 700
Chance cause of variation      148
Changepoint model      470
Changing sample size on the $\overline{x}$ and R charts      209
Check sheet      148 169 178 137 238
Chemometrics      519
Chi-square control chart      493 494
Chi-square distribution      89
Choosing the proper type of control chart      312
ChSP-1      701
Clearance number      703
Combined array design      624 626
Combined cusum-Shewhart control-charts      398
Common cause of variation      see “Chance cause of variation”
Completely randomized experiment      131 560
Compound Poisson distribution      298
Concurrent engineering      7
Confidence interval      97
Confidence interval on difference in two means      115 120 121
Confidence interval on means      98 104
Confidence interval on proportion(s)      108 128
Confidence interval on variance(s)      106 126
Confidence intervals in gauge R & R studies      362
Confidence intervals on process capability ratios      343
Conformance to standards      3
Confounding in the $2^{k}$ design      594
consumerism      33
Consumer’s risk      97 364 658
Continuous probability distribution      51 52 53 61 66 69 70 72
Continuous sampling      702 705
Contour Plot      583
contrast      569
Control chart for a sue sigma process      431
Control chart for fraction nonconforming      266 268 269 277
Control chart for nonconformities (defects)      288 289 290
Control charts and hypothesis testing      151
Control charts and process capability analysis      349
Control ellipse      492
Control limits and natural tolerance limits      206
Control limits and specification limits      206
Control limits based on average sample size      282
Control-noise factor interactions      623
Controlchart      8 12 148 150 156 180 222 231 265 267 288 289 290 349 431
controllable factors      550 622 623
Cost of quality      see “Quality costs”
Costs of investigating and correcting the process      459
Critical region      97
Critical-to-quality characteristics      6
Crossed array design      623
CSP-1      703
CSP-2, CSP-3      705
Cumulative frequency plot      46
Cumulative sum (cusum) control chart      386 389 390 392 394 395 398 401 403 457 469
Curtailment in double sampling      663
Cuscore and cusum control chans      469
Cuscore and EWMA control charts      469
Cuscore and moving average control charts      469
Cuscore and Shevvhart control charts      469
Cuscore canatrf charts      467
Cuscore statistic      467
CUSUM      428
Cusum status chart      392 403
Cyclic panern on control charts      165 214
data transformation      137 304 340
Decision interval for the cusum      390
Defect      7 265 288
Defect concentration diagram      148 174
Defective      7 165
Defective product      7
Defining relation      595 602
Definitions of quality      4
Degrees of freedom      89 90
Delta method      371
Demerit      93 300 301
Deming philosophy      16
Deming’s 14 points      17
Design generator      595 602 603 604
Design of $\overline{x}$ and R charts      208
Design of a control chart      156 158 159 160 208 277 395 411 457 460
Design of control charts      457 460
Design of the cusum      395
Design of the EWMA control chart      411
Design resolution      600
Designed experiment      8 11 12 182 351 358 547 550 552
Designing a double sampling plan for attributes      667
Designing a single sampling plan for attributes      657
Designing a single sampling plan for variables      692
Detector in the Cuscore      468
Difference control chart      474
Dimensions of quality      2
Discrete probability distribution      51 52 55 57 58 59 60 61
Discriminating power of a gauge      353
Discrimination ratio      356
DMAIC problem solving process      26
DNOM control charts      425
Dodge — Roraig sampling plans      681
Double-sampling plan      648 662
Drifting process      527
durability      2 6
Economic design of control charts      457 461 466
Effect of л and с on ОС curves      654
Engineering process control (EPC)      157 526 535 540
Estimating process capability from a control chart      202
Estimation of process level with the cusum      394
Evolutionary operation (EVOP)      611 631
EVOP phase      633
EWMA      386 446 449 453 469 477 528 532
Exponential distribution      69 304 458
Exponentially Weighted Moving Average (EWMA) control chart      386 405 407 411 414 415
External failures      31
F distribution      91
Factorial design      12 182 358 547 552 553 557 567
Failure costs      30 31
Failure rate      69
False alarm on a control chart      161
False defectives in gauge R & R studies      364
Fast initial response cusum      398
Fast initial response EWMA      413
Feedback control      527 528 540
Feedforward control      527
Feigenbaum philosophy      19
Fill control      474
First-order autoregressive model      444
First-order integrated moving average model      446
First-order mixed model      446
First-order moving average model      446
First-order response surface model      583 613
Fitness for use      4
Fixed effects model ANOVA      131
Fraction nonconforming      266
Fractional factorial design      182 547 595
Fractional sampling control charts      437
Functional data analysis      521
Gamma distribution      70
Gauge capability      352 354 356 357
Gauge R & R studies      357 358 362 364
Gauge variability      355
Generalized variance      511
Geometric distribution      61
Group control charts      434 435
Guidelines for designing experiments      555
Guidelines for using acceptance sampling      650 651
Headstart on a cusum      see “Fast initial response cusum”
histogram      44 148 329
Hoteiling $T^2$ control chart      491 496 501 520
HVOP cycle      632
Hypergeometric distribution      55 77 655
Hypothesis testing      96 97 346 527
Hypothesis testing on difference in two means      114 116 120 123
Hypothesis testing on means      97 101
Hypothesis testing on process capabilities ratios      346
Hypothesis testing on proportions      107 126
Hypothesis testing on variance(s)      105 225
In-control process      148 156
Incoming inspection      14 646
Individuals control chart      231 232 305
Inner array design      623
Inspection level      673 675
Integral control      528 530 535 540
Integrating SPC and EPC      527 541 543
Interaction      557 558 567 575 576
Internal failures      30
International Standards Organization (ISO)      20 672 673
Interpretation of control charts      214—216 279 499
Interpretation of multivariate control chart signals      499
Interquartile range      43
ISO 9000      20
Juran philosophy      18
Juran Trilogy      18
kurtosis      332
Latent structure methods      see “Principal components analysis (PCA)”
Limiting quality level      see “Lot tolerance percent defective (LTPD)”
Logaormal distribution      66
Logbooks and the control chart      276
Lot disposition      see “Acceptance sampling”
Lot formation      649
Lot screening      658
Lot sentencing      see “Acceptance sampling”
Lot tolerance percent defective (LTPD)      655 681 683
Lower control limit      150
Main effects      557 568 574
Malcolm Baidrige National Quality Award (MBNQA)      23 24
Management of quality      15 35
Manual adjustment chart      535
Master black belts      26
Matrix of scatter plots      526
Mean absolute deviation      449
Mean of a distribution (or population)      52 94
Mean squares      133 359
Mean Time To Failure      69
measurement systems      352 357 358
Median      43
Method of least squares      582 613
Method of steepest ascent      614 615 616
Military Standard sampling plans      672 694 706
Minimum variance estimator      94
Misapplication of x and R control charts      309
Mixture pattern on control charts      214
Modified control chart      215 429 431
Monitoring versus control      527 541
Moving average control chart      417 469
Moving center-line EWMA control chart      449
Moving range control chart      232 234
Multiple-sampling plan      649 662 668
Multiple-stream processes      434
Multivariate control charts      486 487 489 491 504 507 510
Multivariate cusum control chart      504
Multivariate data      487 490 495
Multivariate EWMA control chart      504
Multivariate normal distribution      489
Narrow limit gauging      475
Natural tolerance limits in a process      203 206 327
Negative binomial distribution      60 298
Noise factors      550 622 623
Non-value-added work      184
Nonconforming product      7
Nonconformity      7 165
Nonnormal distributions and control charts      216 237 412 477
Nonparajpctric control charts      477
Nonparametric tolerance limits      375
Normal distribution      61 62 65 78 88 216 237 339
Normal distribution and variables sampling      691
Normal inspection      673 676
Normal probability plot      73 331
Normal probability plot of factor effects      588 600
Normal probability plot of residuals      137 566
Normality and process capability ratios      339
np control chart      279
Null hypothesis      96
OC curve      see “Operating characteristic curve”
Off-iine quality control      13
On-line quality control      13
One-factor-at-a-time experiments      558
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