Reliability Verification, Testing, and Analysis in Engineering DesignCRC Press, 2002. gada 27. nov. - 416 lappuses Striking a balance between the use of computer-aided engineering practices and classical life testing, this reference expounds on current theory and methods for designing reliability tests and analyzing resultant data through various examples using Microsoft® Excel, MINITAB, WinSMITH, and ReliaSoft software across multiple industries. The book disc |
No grāmatas satura
1.–5. rezultāts no 58.
v. lappuse
... identify mixtures and competing failure modes from the examination of prob- ability plots , and introduces the use ... identifying design deficiencies . In the former case , we show how to use MINITAB'sTM built - in accelerated life ...
... identify mixtures and competing failure modes from the examination of prob- ability plots , and introduces the use ... identifying design deficiencies . In the former case , we show how to use MINITAB'sTM built - in accelerated life ...
3. lappuse
... identified early in the design process to ensure that important customer requirements are designed into the product ... identify potential customer uses of a product up - front in the design processes . In some instances the hidden ...
... identified early in the design process to ensure that important customer requirements are designed into the product ... identify potential customer uses of a product up - front in the design processes . In some instances the hidden ...
6. lappuse
... identified prior to the product's release to the customer . In such cases design errors might result in the product's never performing to customer expectations , or it might do so for a while until performance degrades to an ...
... identified prior to the product's release to the customer . In such cases design errors might result in the product's never performing to customer expectations , or it might do so for a while until performance degrades to an ...
9. lappuse
... identification of potentially critical ( important ) failure modes up front in the design process . Each failure mode is rated by its criticality — the severity of the failure event multiplied by the likelihood of its occurrence or by ...
... identification of potentially critical ( important ) failure modes up front in the design process . Each failure mode is rated by its criticality — the severity of the failure event multiplied by the likelihood of its occurrence or by ...
12. lappuse
... identify the root causes of the failures . Designed experiments may be useful when many potential variables are under exploration . Corrective action must eventually be taken at the product design , process design , or production stage ...
... identify the root causes of the failures . Designed experiments may be useful when many potential variables are under exploration . Corrective action must eventually be taken at the product design , process design , or production stage ...
Saturs
LXXXVII | 204 |
LXXXVIII | 206 |
XC | 207 |
XCII | 208 |
XCIV | 210 |
XCVI | 211 |
XCVII | 213 |
XCVIII | 214 |
XI | 23 |
XII | 24 |
XIII | 25 |
XIV | 29 |
XV | 30 |
XVI | 32 |
XVIII | 35 |
XIX | 36 |
XX | 40 |
XXI | 63 |
XXII | 64 |
XXIV | 68 |
XXV | 71 |
XXVI | 74 |
XXVII | 75 |
XXVIII | 77 |
XXIX | 79 |
XXX | 81 |
XXXI | 83 |
XXXII | 84 |
XXXIII | 86 |
XXXIV | 88 |
XXXVI | 90 |
XXXVII | 92 |
XXXVIII | 95 |
XXXIX | 101 |
XLI | 104 |
XLIII | 105 |
XLIV | 110 |
XLV | 114 |
XLVI | 117 |
XLVIII | 118 |
L | 119 |
LI | 121 |
LII | 125 |
LIII | 126 |
LVI | 127 |
LVII | 129 |
LVIII | 131 |
LIX | 133 |
LX | 135 |
LXI | 137 |
LXIII | 142 |
LXIV | 147 |
LXV | 148 |
LXVI | 151 |
LXVII | 155 |
LXVIII | 157 |
LXIX | 159 |
LXX | 161 |
LXXI | 162 |
LXXII | 163 |
LXXIII | 164 |
LXXIV | 166 |
LXXV | 168 |
LXXVI | 173 |
LXXVII | 177 |
LXXVIII | 180 |
LXXIX | 186 |
LXXX | 189 |
LXXXI | 190 |
LXXXII | 195 |
LXXXIII | 196 |
LXXXIV | 199 |
LXXXV | 201 |
LXXXVI | 203 |
XCIX | 216 |
CI | 217 |
CII | 221 |
CIII | 222 |
CIV | 224 |
CVI | 225 |
CVIII | 226 |
CIX | 229 |
CX | 231 |
CXI | 233 |
CXII | 234 |
CXIII | 238 |
CXIV | 239 |
CXV | 240 |
CXVI | 241 |
CXVII | 246 |
CXVIII | 250 |
CXIX | 253 |
CXX | 254 |
CXXI | 255 |
CXXII | 257 |
CXXIII | 259 |
CXXIV | 260 |
CXXV | 265 |
CXXVII | 271 |
CXXVIII | 274 |
CXXX | 277 |
CXXXI | 280 |
CXXXII | 282 |
CXXXIV | 284 |
CXXXV | 287 |
CXXXVI | 289 |
CXXXVII | 290 |
CXXXVIII | 291 |
CXXXIX | 292 |
CXLI | 300 |
CXLIII | 305 |
CXLV | 307 |
CXLVI | 309 |
CXLVIII | 311 |
CXLIX | 312 |
CL | 314 |
CLI | 316 |
CLII | 319 |
CLIII | 320 |
CLIV | 322 |
CLVI | 325 |
CLVII | 329 |
CLVIII | 351 |
CLIX | 352 |
CLXI | 356 |
CLXIII | 359 |
CLXV | 360 |
CLXVI | 362 |
CLXVII | 367 |
CLXVIII | 368 |
CLXIX | 369 |
CLXX | 371 |
CLXXII | 372 |
CLXXIII | 373 |
CLXXIV | 376 |
CLXXVI | 377 |
CLXXVII | 379 |
CLXXVIII | 387 |
Citi izdevumi - Skatīt visu
Reliability Verification, Testing, and Analysis in Engineering Design Gary Wasserman Ierobežota priekšskatīšana - 2002 |
Reliability Verification, Testing, and Analysis in Engineering Design Gary Wasserman Priekšskatījums nav pieejams - 2002 |
Bieži izmantoti vārdi un frāzes
accelerated analysis Appendix approximation asymptotic beta distribution binomial distribution bogey testing Chapter component computer-aided engineering confidence intervals confidence limit cumulative cycles density function design verification electronics Equation evaluated exponential distribution expression F-distribution failure distribution failure mode Figure FMEA Goal Seek hazard identify illustrated inverse likelihood contours likelihood estimation linear location-scale distribution lognormal distribution lower confidence limit LR limits maximum likelihood median rank Microsoft Excel Minitab ML estimates Monte Carlo MTTF normal distribution occur parameter estimates percentile phenomena potential failure modes probability plots procedure properties Q-Q plots random variable rank estimator rank regression recorded failures relationship reliability metrics right-censored sample sizes shape parameter simulation standard normal stress subsystem success-failure test t₁ Table temperature usage values variance wearout Weibayes Weibull data Weibull distribution Weibull parameters Weibull plot Worked-out Example