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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
One-sided alternative hypothesis      98
One-sided cusum      396 400
Operating characteristic curve      110 159 160 217 286 302 652 654 655 656 657 664 672 679 692
Operation process chart      185
Operator-controllable versus management-controllable process problems      273
Orthogonal design      577 583
Out-of-control action plan (OCAP)      154
Out-of-control process      149
Outer array design      623
Outgoing inspection      14
p chart      267 268 269
P value      100
Paired r-test      123
Parameter estimation framework of HPC      528
Parameters of a distribution      93
Pareto analysis      31
Pareto chart      148 171 179 188 293
Partial least squares      519
Pascal distribution      59
Passed defectives in gauge R & R studies      364
path of steepest ascent      614 615 616
Pattern recognition      165
Patterns on control charts      163 165 214
Perceived quality      3
Percentiles      43
Performance      2
Performance excellence criteria      23 24
Phase I control chart usage      168 199 269 272 428 496 501 520
Phase I operation of $\overline{x}$ and R charts      199
Phase II control chart usage      168 204 217 234 496 501 504 520
Phase II operation of $\overline{x}$ and R charts      204 217
Phase II operation of individuals control charts      234
Point estimate      94
Point estimation of parameters      93 94
Poisson distribution      58 78 92 289 302
Pooled estimator of variance      116
Pooled t-test      see “Two-sample t-test”
Population      51
Potential process capability      338 349
Power of a statistical test      97 109 111 123
Pre-experimental planning      557
Precision of a gauge      357
Precision-to-tolerance ratio      354
Precontrol      474
Predicting process level with the EWMA      415
prevention costs      28
Principal component scores      516
Principal components analysis (PCA)      437 514 516 518 520
Principal fraction      597
probability distribution      51 52 53 55 57 58 59 60 61 66 69 70 72 86 93
Probability limits on control charts      158 212
Probability limits on the 1 and R charts      212
Probability models for count data      297
Probability plot      74 76 329 331 333
Process capability      155 202 327
Process capability analysis      327 328 329 349 351
Process capability ratios      203 333 334 335 336 337 338 339 343 346
Process characterization      552 611
Process failure mechanism      458
Process flow chans      184 186 187
Process gain      528
Process mapping      184
Process optimization      553 611
Process potential indices      348
Process robusmess studies      611 621 624
Producer’s risk      97 364 658
Product characterization      328
Product liability      33
Productivity      27
Profile monitoring      520
Projection of $2^{k-1}$ designs      600
Projection of $2^{k}$ designs      584
Proportional integral (PI) control      541
Proportional integral derivative (PID) control      541
Quality      2 4 27 28
Quality and productivity      27
Quality assurance      15 22
Quality characteristics      6
Quality control and improvement      5 16
Quality costs      28 30 31
Quality engineering      6
Quality of conformance      4
Quality of design      4
Quality planning      15
Quality systems and standards      20
Quarriles      43
R chart      180 194 196 197 200
Random effects model      358
Random sample      87 649
Random variable      51 93
Randomization      129
RANGE      see “Sample range”
Range method for estimating the standard deviation      95—96 232 239—242 636
Rational subgroups      162 207 245 413
Rational subgroups and the cusum      402
Rectifying inspection      14 658
Reduced inspection      673 678
Reduction of variability      4 5 14 527
Reference value for the cusum      390
Regression adjustment      507 509
Regression control chart      215 472
Regression model      507 509 571 581 582
Rejectable quality level      see “Lot tolerance percent defective (LTPD)”
Relative range      95 198
Reliability      2 6 69 72
Renewal-reward process      460
Repeatability      357 361
Replication      129
Reproducibility      357 361
Residual analysis      137 566 571 606
Residual control charts      443 444 446 450 509
Residuals      137 443 509 566 600 606
Response model      624
Response surface designs      553 612
Response surface methods      547 611 612
Response surface plot      583
Revision of control limits      199 204
Robust parameter design (RPD)      623
Robustness of the EWMA to nonnormality      412
Rotatable design      620
Rounded adjustment chart      539
Run chart      44 189
Runs on control charts      163
s control chart      194 222
Sample      41 51 87
Sample autocorrelation function      440
Sample average or sample mean      47 88 94
Sample fraction defective (nonconforming)      58 266
Sample range      85 95—96 232 239—242
Sample size decisions      109 111 123
Sample sizes in MIL STD 105E      679
Sample standard deviation      48 49 88
Sample variance      48 88 94
Sampling costs      458
Sampling distribution      88 89 90 91
Sampling with replacement      87
Sampling without replacement      56 87
Scale cusum      401
Scatter diagram      148 175
Screening experiment      552
Second generation process capability ratios      343
Second-order autoregressive model      445
Second-order effects      589
Second-order response surface model      589 613 616
Semi-economic design of a control chart      460
Sensitivity of residuals control charts      450
Sensitizing rules for control charts      166 167
sequential experimentation      557 597 614
Sequential sampling      649 662 669 700
serviceability      3 6
Setpoint      529
Setting specifications      367 374
Setting specifications on linear functions      367
Setting specifications on nonlinear functions      371
Sftewhart control chart      153 180 266 385 386 398
Shapiro — Wilk test for normality      332
Shewhart process model      438 453
Short-run control charts      244
Short-run SPC      424 427
Signal-to-noise ratio      356 623
Single replicate of a $2^{k}$ design      585
Single-sampling plan      648 652 657 672 689
Six Sigma      25 26
Six sigma process      429
skewness      332
Skip-lot sampling plans      706
Sparsity of effects principle      585
Special cause of variation      see “Assignable cause of variation”
Specifications      7 206 367 371 374
Standard deviation of a distribution (or population)      53
Standard error of an effect in a $2^{k}$ design      584
Standard normal distribution      62
Standard values on $\overline{x}$ and R charts      212
Standardization      62
Standardized $\overline{x}$ and R charts      426 427
Standardized control charts      283 300 397
Standardized cusum      397
Stationary process      156
Statistic      88
Statistical inference      87
Statistical methods      6 8
Statistical process control (SPC)      11 148 550
Statistics      42
Steepest ascent      see “Method of steepest ascent”
Stem-and-leaf display      42 43 148
Stratification pattern on control charts      215
Switching rules in MIL STD I05E      673 674
t distribution      90
Tabular or algorithmic cusum      389 391
Tampering with the process      533
Taylor series      371 626
Test statistic      96
Testing for curvature      589 590
Third generation process capability ratios      343
Three sigma control limits      152 158
Tightened inspection      673 677
Time between events control chart      304
Time series model      443 445 453
Time series plot      44
Tolerance chart      181 203 205
Tolerance isterval control charts      476
Tolerance limits      374 375
Tolerance stack-up problems      367
Tool wear      472
Total quality management (TQM)      19
Trajectory plot      518
Transmission of error formula      371 626
Trend on control charts      215
Trial control limits      199 269
Two-sample t-test      118
Two-sided alternative hypothesis      96
Type A OC curve      655
Type B OC curve      655
Type I error      97 158
Type II error      97 109 111 123 158 286 302
u chart      295
Unbiased estimator      94
uncontrollable factors      see “Noise factors”
Uncorrelated process data      156
Uniform distribution      53
Unreplicated $2^{k}$ designs      585
Unweighted batch means control chart      452
Upper control limit      150
V-mask form of the cusum      389
Value Engineering      20
Variability      4 6 15 42 150
Variable sample size      227
Variable sample size on the p chart      277 280 282 283
Variable-width control limits      280
Variables control charts      156 194 231 232 312
Variables data      6 180 648 689
Variables-sampling plans      689 690 694 699
Variance components      359
Variance of a distribution (or population)      52 94
Voice of the Customer      15
Wanting limits on control charts      159
waste      5
Weibull distribution      72 304
Western Electric rules      166
What quality characteristics to monitor      312
Where to place control charts      312
Within-sample variability      207
x control chart      see “Individuals control chart”
Yield control charts      267
Zero defects      20
Zone rules on control charts      see “Western Electric rules”
“Magnificent seven”      148 169
“Quality is free”      20
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