Analysis of the main factors affecting mass production in the plastic molding process by using the finite element method

Plastic injection molding is widely used in many industrial applications. Plastic products are mostly used as disposable parts or as portable parts for fast replacements in many devices and machines. However, mass production is always adopted as an ideal method to cover the huge demands and customers’ needs. The problems of warpage due to thermal stresses, non-uniform pressure distribution around cavities, shrinkage, sticking and overall products quality are some of the important challenges. The main objective of this work is to analyze the stress distribution around the cavities during the molding and demolding to avoid their effects on the product quality. Moreover, diagnosing the critical pressure points around and overall the cavity projection area, which is subjected to high pressure will help to determine the optimum pressure distribution and ensure filling all cavities at the same time, which is another significant objective. Computer-aided design (CAD) and CATIA V5R20 are adopted for design and modeling procedures. The computer-aided engineering (CAE) commercial software ABAQUS 6141 has been dedicated as finite element simulation packages for the analysis of this process. Simulation results show that stress distribution over the cavities depends on both pressure and temperature gradient over the contact surfaces and can be considered as the main affecting factor. The acceptable ranges of the cavity stresses were determined according to the following values: the cavity and core region temperature of 55–65 °C, filling time of 10–20 s, ejection pressure 0.85 % of injection pressure, and holding time of 10–15 s. Also, theoretical results reveal that the uniform pressure and temperature distribution can be controlled by adjusting the cavities layout, runner, and gate size. Moreover, the simulation process shows that it is possible to facilitate and identify many difficulties during the process and modify the prototype to evaluate the overall manufacturability before further investing in tooling. Furthermore, it is also concluded that tooling iterations will be minimized according to the design of the selected proces