A simple regression approach to the shortened stiffness tests for pallets

The purpose of the paper is to develop the model by using the predicted value of creep response based on the regression methodologies that can be effectively used to reduce the test time required to put the stiffness test for the plastic pallets. In order to develop the best model, we examine a wide variety of regression techniques including the OLS (ordinary least squares), the WLS (weighted least squares), the Newey-West robust estimator, and the SUR (seemingly unrelated regression). The new protocol is assessed to remarkably enhance the test productivity by decreasing the standard bending test time by 77% from 26 to 6 h. It is shown that the deflection process under load is best described as a linear model regressing deflections on the natural logarithm of test duration. The model is statistically validated against the various estimation techniques and sample. We demonstrate how the forecasted deflections at a specific time point are statistically tested for a certain performance standard limit. From a standpoint of the parsimony and practical significance, we claim the OLS estimation of a simple regression model is a reasonable choice for the shortened stiffness tests of pallets.