Smart injection molding based on material adaptive control

• Main Authors: Hartono, Moh, Adiwidodo, Satworo, Rarindo, Hari, Wicaksono, Hangga
• Format: Conference Proceeding
• Language: English
• Subjects: Adaptive control; Artificial intelligence; Artificial neural networks; Control boards; Injection molding; Manufacturing; Neural networks; Process parameters
• ISSN: 0094-243X; 1551-7616
• DOI: 10.1063/5.0126052

The study aims to explain the concept of a smart Plastic Injection Moulding (PIM) machine based on material adaptive control. In the current industrial era 4.0, information technology and artificial intelligence systems are very influential on the manufacturing industry. Therefore, the need for the manufacturing industry to use smart machines, including PIM machines, is absolutely to realize. In this study, the concept of a smart PIM machine uses an artificial intelligence approach with an artificial neural network. With an artificial neural network, the system will practice continuously so that the system can make adjustments and get used to the input material. In the hopper section of the PIM machine, there is an image sensor that can record any changes to the material that is entered, then a signal is sent to the control panel. In the control panel section, there is an adaptive control process based on artificial intelligence artificial neural networks to automatically make adjustments in parameter settings in the PIM process. Parameters set include injection temperature, injection pressure, injection speed, holding time, injection time, and clamping force. These parameter settings are automatically regulated by a smart system that adapts to the characteristics of the material being processed. The result of the research is a video simulation of the concept of a smart PIM machine based on material adaptive control. This article hopes that this concept can be realized into a small-scale prototype of a smart PIM machine and can gradually be realized in a smart PIM machine on a real scale.