Optimization of plastic injection process parameters using the Taguchi method, machine learning and genetic algorithm

Abstract

Plastics are shaped by many different shaping methods according to their types and intended purpose. One of these methods is injection molding. Plastic injection is a production method that involves the injection of molten polymer into a mold cavity where the polymer later cools and is removed. Dimensional and visual errors (sink marks, flow marks, warpage, short shot, burn marks, weld line, air bubbles, jetting, etc.) occur in parts produced by the plastic injection method due to various reasons. In this thesis, a study was conducted on the warpage problem, which is one of the critical quality problems of injection molded parts and results in both structural and visual defects. Warpage can be defined as deviations and dimensional distortions compared to those in the original part design. The main cause of warpage is the development of uneven internal stresses during the filling, compression and cooling phases of the injection process. However, direct measurement or accurate modeling of these stresses is rather difficult. For this reason, the present study employed an indirect approach to determine the optimum values for the input parameters of the plastic injection process that minimize warpage. Firstly, using the Taguchi method, the most influential process parameters were determined (from the most influential onward): packing pressure, cavity steel temperature, cooling time, packing time and back pressure, respectively. Next, using the Taguchi experiment design, a full factorial experiment design set containing a more comprehensive dataset was created with parameters whose number and range of values were limited. According to this set of experiments, a second trial was made and the warpage values of the piece were measured. A machine learning (ML) model was then created using all the data. This model served as the simulation of the process and was employed by the genetic algorithm (GA) in the search for optimum process parameters that yield minimum warpage. As a result of the studies, it has been determined that the most influential parameters on warpage are packing pressure, cooling time, packing time, back pressure and cavity steel temperature. On the other hand, it was observed that parameters such as melt temperature and injection pressure had little effect on the process. An interesting observation was that, in contrast with literature, an increase in applied pressure had a negative effect on the warpage of the part.