Quality and Reliability Methods - SAS

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Contents Introduction to Accelerated Test Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .239 Launching the Fit Life by X Platform Window . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .239 Platform Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 241 Navigating the Fit Life by X Report Window . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .242 Summary of Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .243 Scatterplot. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .243 Nonparametric Overlay. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .245 Wilcoxon Group Homogeneity Test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .245 Comparisons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 246 Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .250 Viewing Profilers and Surface Plots . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .257 Using the Custom Relationship for Fit Life by X. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 258
Chapter 14 Lifetime Distribution II 239 Introduction to Accelerated Test Models Introduction to Accelerated Test Models The Fit Life by X platform provides the tools needed for accelerated life-testing analysis. Accelerated tests are routinely used in industry to provide failure-time information about products or components in a relatively short-time frame. Common accelerating factors include temperature, voltage, pressure, and usage rate. Results are extrapolated to obtain time-to-failure estimates at lower, normal operating levels of the accelerating factors. These results are used to assess reliability, detect and correct failure modes, compare manufacturers, and certify components. The Fit Life by X platform includes many commonly used transformations to model physical and chemical relationships between the event and the factor of interest. Examples include transformation using Arrhenius relationship time-acceleration factors and Voltage-acceleration mechanisms. Linear, Log, Logit, Reciprocal, Square Root, Box-Cox, Location, Location and Scale, and Custom acceleration models are also included in this platform. You can use the DOE > Accelerated Life Test Design platform to design accelerated life test experiments. Meeker and Escobar (1998, p. 495) offer a strategy for analyzing accelerated lifetime data: 1. Examine the data graphically. One useful way to visualize the data is by examining a scatterplot of the time-to-failure variable versus the accelerating factor. 2. Fit distributions individually to the data at different levels of the accelerating factor. Repeat for different assumed distributions. 3. Fit an overall model with a plausible relationship between the time-to-failure variable and the accelerating factor. 4. Compare the model in Step 3 with the individual analyses in Step 2, assessing the lack of fit for the overall model. 5. Perform residual and various diagnostic analyses to verify model assumptions. 6. Assess the plausibility of the data to make inferences. Launching the Fit Life by X Platform Window This example uses Devalt.jmp, from Meeker and Escobar (1998), and can be found in the Reliability folder of the sample data. It contains time-to-failure data for a device at accelerated operating temperatures. No time-to-failure observation is recorded for the normal operating temperature of 10 degrees Celsius; all other observations are shown as time-to-failure or censored values at accelerated temperature levels of 40, 60, and 80 degrees Celsius. 1. Open the Devalt.jmp sample data table. 2. Select Analyze > Reliability and Survival > Fit Life by X. 3. Select Hours as Y, Time to Event. 4. Select Temp as X. 5. Select Censor as Censor.
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Version 10 Quality and Reliability
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INDIRECT OR CONSEQUENTIAL DAMAGES O
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6 Nelson Rules . . . . . . . . . .
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8 8 Assess Measurement Systems The
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10 Other Menu Options . . . . . . .
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12 Reliability Forecast Platform Op
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Chapter 1 Learn about JMP Documenta
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Chapter 1 Learn about JMP 17 Book C
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Chapter 1 Learn about JMP 19 Book C
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Chapter 1 Learn about JMP 21 Additi
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Chapter 1 Learn about JMP 23 Additi
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Chapter 2 Statistical Control Chart
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Chapter 3 Introduction to Control C
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Chapter 4 Interactive Control Chart
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Chapter 5 Shewhart Control Charts V
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Chapter 9 Capability Analyses The C
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Chapter 9 Capability Analyses 143 L
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Chapter 9 Capability Analyses 145 C
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Chapter 10 Variability Charts Varia
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Chapter 10 Variability Charts 153 V
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Chapter 10 Variability Charts 163 R
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Chapter 10 Variability Charts 169 D
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Chapter 10 Variability Charts 171 A
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Chapter 11 Pareto Plots The Pareto
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Chapter 11 Pareto Plots 181 Pareto
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Chapter 16 Degradation 291 Inverse
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Chapter 16 Degradation 293 Platform
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Chapter 18 Reliability Growth Using
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Chapter 18 Reliability Growth 343 A
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Chapter 18 Reliability Growth 345 A
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Chapter 18 Reliability Growth 347 S
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Chapter 19 Reliability and Survival
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References Abernethy, Robert B. (19
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References 407 Carroll, R.J., Ruppe
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References 409 Haaland, P.D. (1989)
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References 411 Lawless, J.F. (1982)
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References 413 Nelson, W.B. (2003),
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References 415 Snee, R.D. and Marqu
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Index JMP Quality and Reliability M
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Index 419 Fit SEV 242 Fit Weibull 2
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Index 421 Q Quantiles table 356 R R
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Index 423 Weibull Plot 360 Westgard
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Quality and Reliability Methods - SAS

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