Example of Nonparametric Growth Curve

A reliability engineer wants to compare the failure rate for two different types of a brake component that is used on subway trains. The engineer collects replacement time data and component type for 29 trains. Each time a unit failed, it was repaired and returned to service.

The engineer uses a nonparametric growth curve to evaluate the data without assuming a distribution model. For these data, no brake components were retired from service. Therefore, all the data are exact failure times.

  1. Open the sample data, BrakeReliability.MTW.
  2. Choose Stat > Reliability/Survival > Repairable System Analysis > Nonparametric Growth Curve.
  3. In Variables/Start variables, enter Days.
  4. Under System Information, select System ID, and then enter ID.
  5. Select By variable, and then enter Type.
  6. Click OK.

Interpret the results

Minitab displays nonparametric estimates of the mean cumulative function and its corresponding standard error and confidence limits separately for each group. For example, for the type 1 brake component, the mean cumulative function at 650 days is 1.71429. That is, the mean cumulative number of repairs at 650 days, averaged over all the systems, is approximately 1.7. The engineer can be 95% confident that the true mean cumulative function for the type 1 component at 650 days is contained within the interval 1.27912 and 2.29750.

The engineer uses the mean cumulative difference function to make comparisons across groups. For example, at 500 days, the type 2 brake component had, on average, 2.16420 more failures than the type 1 brake component. The engineer can be 95% confident that, at 500 days, true mean cumulative difference (type 1 – type 2) is contained within the interval −3.23488 and −1.09352.

The event plot shows when the failures occurred for each system. Each line extends to the final day of observation. The plot also shows trends within and across groups. In this plot, system failures generally occur at a constant rate. At 200 days, there are many more failures for the type 2 brake component than the type 1 brake component.

The mean cumulative function plot displays the mean cumulative function for each group. From this plot, the engineer concludes the following:
  • The function that represents the type 2 brake component is relatively linear, not curved, up until approximately 450 days. Therefore, the failure rate for the type 2 brake component is relatively constant until 450 days.
  • The function that represents the type 1 brake component is linear from approximately 200 days through 700 days, and then increases rapidly. Therefore, the failure rate for the type 1 brake component is fairly constant until 700 days, then increases rapidly.
  • The function that represents the type 1 brake component is to the right of the function that represents the type 2 brake component. Therefore, failures occur less often for the type 1 brake component than for the type 2 brake component.
Type 1
System:  ID
Nonparametric Estimates

Table of Mean Cumulative Function


Mean
Cumulative
Function





Standard
Error
95% Normal CI
TimeLowerUpperSystem
330.071430.0688300.010810.47218179
880.142860.0935220.039600.51540132
2500.214290.1096640.078590.58426128
2720.285710.1207360.124810.65408137
2870.357140.1280600.176860.72120181
3020.428570.1322600.234070.78471119
3170.500000.1336310.296130.84423182
3640.571430.1322600.363030.89945112
3670.642860.1280600.435060.94990167
3910.714290.1574210.463741.10019112
4020.785710.1490980.541681.13970175
4210.857140.1707470.580081.26653137
4310.928570.1585740.664441.29771155
4441.000000.1749640.709691.40906119
4621.071430.1585740.801651.43200101
4811.142860.1376610.902531.44718145
4981.214290.1490980.954561.54468182
5001.285710.1870440.966751.70992119
5001.357140.1918531.028721.79042128
5481.428570.2193281.057351.93013112
5521.500000.2422261.093042.05848137
6251.571430.2805661.107442.22982137
6351.642860.2596531.205222.23940169
6501.714290.2561201.279122.29750169
6571.785710.2706491.326792.40338182
6871.862640.2666551.406922.46596179
6871.939560.2608621.490122.52456181
7002.030470.2548261.587712.59671175
7082.130470.2745271.654982.74258169
7102.241580.2687551.772142.83537145
7102.352690.2575861.898332.91581155
7102.463800.2402672.035162.98273167
7192.630470.3472162.030843.40714137
7242.830470.4255942.108003.80055112
7243.030470.4439942.274054.03849128
7243.230470.4105592.518184.14424132
7303.730470.4713072.912214.77864101
7304.230470.4105593.497695.11677119
Type 2
System:  ID
Nonparametric Estimates

Table of Mean Cumulative Function


Mean
Cumulative
Function





Standard
Error
95% Normal CI
TimeLowerUpperSystem
190.066670.0644060.010040.44284228
220.133330.0877710.036700.48447212
390.200000.1032800.072690.55029192
540.266670.1141800.115210.61721214
610.333330.1217160.162950.68186219
910.400000.1577620.184650.86652192
930.466670.1596290.238690.91237243
1190.533330.2079890.248341.14538192
1480.600000.2633120.253861.41809192
1730.666670.2610520.309451.43622190
1850.733330.2743340.352271.52661228
1870.800000.2699790.412891.55006235
1920.866670.2644350.476581.57604205
1940.933330.2576240.543351.60321216
2031.000000.2494440.613301.63052183
2051.066670.2576240.664421.71243243
2111.133330.2644350.717381.79046183
2421.200000.2699790.772101.86504190
2501.266670.2576240.850231.88706204
2641.333330.2775550.886642.00507243
2771.400000.2951460.926152.11630183
2931.466670.2807401.007862.13434184
3061.533330.3247791.012382.32237192
3691.600000.3098391.094682.33859206
3731.666670.3355481.123252.47298183
3821.733330.3192581.208102.48693200
4151.800000.3425401.239622.61370243
4161.871430.3405121.310072.67333235
4191.948350.3380971.386622.73764219
4192.025270.3493101.444352.83985228
4322.116180.3474411.533912.91948216
4342.216180.3450341.633373.00696204
4412.327290.3418391.745123.10369214
4472.452290.3374301.872623.21141212
4482.595150.3310332.021093.33227205
4482.738010.3153982.184663.43152206
4602.938010.2980092.408323.58420200
4613.188010.4498342.417764.20364192
4643.521340.5114782.648934.68108190
5034.021340.5353603.097785.22025184
5115.021340.5353604.074436.18831183
Comparison: (Type = 1) - (Type = 2)

Table of Mean Cumulative Difference Function


Mean Cumulative
Difference
Function




Standard
Error
95% Normal CI
TimeLowerUpper
19-0.066670.064406-0.192900.05957
22-0.133330.087771-0.305360.03869
33-0.061900.111541-0.280520.15671
39-0.128570.124114-0.371830.11469
54-0.195240.133322-0.456540.06607
61-0.261900.139830-0.535970.01216
88-0.190480.153496-0.491320.11037
91-0.257140.183399-0.616600.10231
93-0.323810.185008-0.686420.03880
119-0.390480.228047-0.837440.05649
148-0.457140.279427-1.004810.09052
173-0.523810.277299-1.067300.01969
185-0.590480.289837-1.15855-0.02241
187-0.657140.285719-1.21714-0.09714
192-0.723810.280486-1.27355-0.17407
194-0.790480.274074-1.32765-0.25330
203-0.857140.266399-1.37928-0.33501
205-0.923810.274074-1.46099-0.38663
211-0.990480.280486-1.54022-0.44073
242-1.057140.285719-1.61714-0.49714
250-1.052380.279994-1.60116-0.50360
264-1.119050.298435-1.70397-0.53413
272-1.047620.302679-1.64086-0.45438
277-1.114290.318886-1.73929-0.48928
287-1.042860.321731-1.67344-0.41228
293-1.109520.308568-1.71431-0.50474
302-1.038100.310335-1.64634-0.42985
306-1.104760.350677-1.79208-0.41745
317-1.033330.351196-1.72166-0.34500
364-0.961900.350677-1.64922-0.27459
367-0.890480.349114-1.57473-0.20622
369-0.957140.335260-1.61424-0.30004
373-1.023810.359155-1.72774-0.31988
382-1.090480.343985-1.76467-0.41628
391-1.019050.355960-1.71672-0.32138
402-0.947620.352358-1.63823-0.25701
415-1.014290.373582-1.74649-0.28208
416-1.085710.371724-1.81428-0.35715
419-1.239560.379800-1.98395-0.49517
421-1.168130.388808-1.93018-0.40608
431-1.096700.383618-1.84858-0.34482
432-1.187610.381917-1.93616-0.43907
434-1.287610.379729-2.03187-0.54336
441-1.398720.376828-2.13729-0.66015
444-1.327290.384013-2.07995-0.57464
447-1.452290.380094-2.19726-0.70733
448-1.738010.360677-2.44492-1.03109
460-1.938010.345574-2.61532-1.26070
461-2.188010.482663-3.13401-1.24201
462-2.116580.476966-3.05142-1.18174
464-2.449910.535496-3.49947-1.40036
481-2.378490.529680-3.41664-1.34033
498-2.307060.532767-3.35126-1.26285
500-2.164200.546276-3.23488-1.09352
503-2.664200.568698-3.77883-1.54957
511-3.664200.568698-4.77883-2.54957
548-3.592770.578546-4.72670-2.45884
552-3.521340.587608-4.67303-2.36965
625-3.449910.604423-4.63456-2.26527
635-3.378490.595004-4.54467-2.21230
650-3.307060.593471-4.47024-2.14387
657-3.235630.599884-4.41138-2.05988
687-3.081780.595533-4.24900-1.91456
700-2.990870.592914-4.15296-1.82878
708-2.890870.601644-4.07007-1.71167
710-2.557540.586803-3.70765-1.40743
719-2.390870.638098-3.64152-1.14022
724-1.790870.674662-3.11319-0.46856
730-0.790870.674662-2.113190.53144