Use Case 2: Machine diagnostics for plastic injection sector to improve quality and reduce waste (IAL)

The use AI for early identification and automatic or semi-automatic correction of the manufacturing process parameters by implementing Machine Learning (ML) techniques aims to avoid quality defects in the plastic parts during the thermoplastic injection process. AI and ML will be used for real-time alarm generation system with prescriptive maintenance indications according to the analysis of quality defects. Implementing a Machine Learning (ML) and Human in the Loop (HITL) techniques will allow the interaction of the operators in charge of the production lines with the ML Predictive models.

The scope of the demonstrator is to create an intelligent system, which will be able to communicate with the injection machine’s control unit and with the operator’s inputs through Human in the Loop (HITL) Dashboards, to automatically adapt the TEAMING.AI Engine to self-adjust the quality control model parameters when a deviation from nominal is detected in the case of sufficient trust assurance evidence and otherwise to request human assistance based on preliminary process diagnostics. The goal is to increase the Overall Equipment Effectiveness (OEE).