Cookie settings

We use several types of cookies on this website to provide you with an optimal online experience, to increase the user-friendliness of our portal and to constantly improve our communication with you. You can decide which categories you want to allow and which you do not want to allow (see "Custom settings" for more information).
Name Usage Duration
privacylayerStatus Agreement Cookie hint1 year
Name Usage Duration
_gaGoogle Analytics2 years
_gidGoogle Analytics1 day
_gatGoogle Analytics1 minute
_galiGoogle Analytics30 seconds

MULTIPLE LINEAR REGRESSION

An approach to process improvement

11 March 2013: Thomas Pfeilsticker

This essay explains how to create and evaluate a regression study based on process data. The aim is to find an empirical model y=f(x1, x2, x3…) for our process data explaining their impact on the response.

The injection molding process of a thermoplastic produced components causing problems during the assembly due to high shrinkage. In order to find out about any method to reduce the percentage shrinkage, data about the injection temperature, injection speed and holding pressure were collected. The general model equation leads to percentage shrinkage = f (injection temperature, injection speed, holding pressure).

Which one of the three influencing factors has the major impact on the percentage shrinkage of the injection molding process? And how do you have to adjust the influencing factors in order to minimize the percentage shrinkage of the injection molded parts as far as possible?


Similar articles