Currently I am undertaking a project for my studies. It requires I take some machine condition data as well as the age of the component and try to make a prediction on the remaining life based on these things. (Sorry I can't give exact descriptions due to the nature of the project).

The condition is based off a ranking from 1 to 5, 5 meaning urgent attention is required but not a guaranteed failure and 1 being normal operating conditions but random failure is still possible, the age is in hours.

I have created a regression model with some known failure data, The continuous predictors are the condition score and the current age, the independent variable is time to failure.

Now! I have completed the regression in minitab and have been tweaking and trying to improve the model for over a week, the best I can get is r-sq scores around 15% as well as S score about 3000 hours (expected life is around 24000 hours). Basically at this stage I am ready to give up and move onto something such as Weibull or Cox regression.

Attached is a 3d plot I did in matlab, the surface is the regression equation and the points are the actual values (residuals).. as you can see the model isn't going to be very accurate.. should I give up on regression? Any help is very much appreciated =) Thanks guys.