Artificial Intelligence and Predictive Analytics: A Novel Approach for Molded Product Quality Improvement
Keywords:
Artificial Intelligence, Predictive Analytics, Injection Molding, Quality Products, Molding Machine and Design, SensorsAbstract
In the manufacturing process, injection molding is one of the most widely used plastic materials manufacturing technology where Artificial Intelligence (AI) plays an important role, which is particularly popular in the automobile industry. This paper aims to establish consistency in mold, short size, and run-to-run. The molded part should meet all quality requirements, and its injection process should run efficiently. Hence, injection molding cannot be completed and imagined without the help of a sensor. There are many sensors available in the market, but some of them are the most important sensors; like first one is a temperature sensor, which senses the temperature of the material in the hopper, barrel, nozzle, and cavity.
The paper presented here gives a comprehensive overview of five elements that help accelerate successful injection molding to manufacture quality molded products. During the manufacturing process, obtained data with the help of sensors are sent to the PLC (Programmable logic control unit) to monitor and control with the help of Artificial Intelligence (AI) in the injection molding process. The second one is the pressure sensor, which senses pressure in the mold cavity. This paper also studies different processing parameter conditions like mold temperature, melt temperature, injection time, injection speed, injection pressure, screw rotation speed, shot size, holding time, cooling time, and so many parameters. Here discussed their effect on molded products and their ignorance of the risk or defects in the developed products.
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