The forecasting techniques used are,

5 period moving average

10 period moving average

40 period moving average

Single exponential smoothing

Double exponential smoothing

Linear regression

Log transformed linear regression

I tried to compare all the models using Root Mean Squared Error (RMSE). The best model is one with low RMSE.

The problem is different methods have low RMSE and are good for different machines. For example, Linear regression is good for machine 1 and Double exponential smoothing is good for machine 2 etc. Also, the difference in RMSE between methods is very low. But the goal is to have one common reliable method for all machines. How do we do it statistically? Any recommendations?

P.S. tried ANOVA and t-test on SE (squared error) but the results was like there is no significant difference in mean.