In-line parameters optimization of plastic injection molding process in the context of disrupted supply chains

Abstract

Recent social, healthcare, and geopolitical events have caused major disruptions to global supply chains, leading to significant negative consequences on the availability and cost of raw materials for various industries. The injection molding sector has been significantly impacted, with supply chain disruptions resulting in reduced availability of plastic granules and overall increases in raw material costs. To overcome these challenges, plastic component manufacturers need to optimize their material validation process to make the most efficient use of available materials. This article proposes a fully automatic solution for optimizing plastic component production in the context of disrupted supply chains, leveraging a Cyber-Physical Production Systems (CPPS) composed by a Cobot, an automatic guided vehicle, an injection molding machine, and a test bench for plastic components. The paper details the system architecture, implementation, and experimental results, demonstrating the effectiveness of the proposed approach. The results show that the CPS-enabled manufacturing system can successfully adapt to changes in material availability, increase production efficiency, and reduce waste. The proposed approach offers a promising solution for the challenges posed by disrupted supply chains in various manufacturing contexts and with different granulates and products.