Optimizing PCR-PET bottle production with machine learning and digital twin technology
A novel approach integrating simulations, machine learning, and digital twin technology to optimize PCR-PET bottle production by improving cycle time and quality through real-time monitoring and adaptive process improvements.
Overview
This innovative solution leverages cutting-edge technologies such as machine learning, sensorisation, and digital twin technology to enhance the production of PCR-PET bottles. By integrating Moldflow simulations with design of experiments (DoE) and advanced regression methods, including artificial neural networks (ANN), Gaussian processes, and support vector regression (SVR), the solution creates accurate predictive models for optimizing production processes. The inclusion of non-invasive thermocouples for real-time sensorisation enables inline optimization, thereby improving efficiency and maintaining high-quality standards.
Technical specifications
- Predictive Modeling: Utilizes machine learning models like ANN, Gaussian process, and SVR for developing predictive models based on simulation and experimental data.
- Sensorisation: Non-invasive thermocouples are used within mold inserts for real-time data collection.
- Digital Twin Technology: Employs finite element method (FEM) data and Kalman filtering to create a real-time, physics-based digital twin for process monitoring and quality assurance.
- Multi-objective Optimization: Implements adaptive Bayesian DoE and genetic algorithms for simultaneous optimization of cycle time and product quality.
- Real-time Monitoring: Continuous monitoring facilitated by sensor data and dynamic mode decomposition.
Technology readiness level
This solution is currently at Technology Readiness Level 6, indicating that it has been demonstrated in a relevant environment and is moving towards system/process validation under real conditions.
About Institute of Technology Sligo
Institute of Technology Sligo was a public institute of technology in Ireland; on April 1, 2022 it was dissolved and became the Sligo campus of Atlantic Technological University, retaining an applied, industry‑focused character. The campus connects with companies through applied research facilities co‑located with teaching, structured work placements, and an on‑site incubation hub supporting spin‑outs and collaborative development. As part of ATU’s multi‑campus system across the West and North‑West, partners access shared innovation hubs and a coordinated engagement function that routes opportunities to the right expertise. Research activity is backed by competitive funding from Enterprise Ireland and European programmes, including EU‑co‑funded Technology Gateway activity at Sligo. Technology transfer and industry liaison are managed centrally within ATU, providing IP guidance, licensing, and collaboration agreements for work originating in Sligo.
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