Context of the project:
In the last years, a constant demand of diversity and personalisation in the plastic sector industry has led to a change of the manufacturing paradigm. This has entailed a globalized production model in which a mould is used in different types of injection machines. Moreover, short productions demand a high degree of flexibility, leading towards a high number of mould changes in plastic moulding factories, causing downtimes and scraps. The scraps during the setup phase represent up to 40% of the total scraps. A reduction of the mould setup time for each machine and a reduction of the reject rates are highly demanded within this context.
The use of statistical process control systems based on data acquisition from both sensors located inside the cavity of the mould and process parameters have tried to reach the required productivity improvement. Nevertheless, the reality is that currently less than 3% of new moulds are equipped with sensors and a change of production machine implies starting a new setup process. Sensor manufacturers have pointed out that one of the main causes of the converters’ refusal to use sensors is due to the wiring, proprietary interfaces and external devices, increasing the cost of the solutions and hinders the daily operations. This entails to low acceptance rates.
Overall objectives of the project:
PREVIEW project aims at developing a Cyber Physical System (CPS) for plastic injection manufacturing processes monitoring, control and optimization by incorporating several innovative and cutting edge technological solutions: advanced Artificial Intelligence and Machine Learning techniques, robust Industrial wireless communication, Internet of Things (IoT) and wireless indoor localization. PREVIEW is a middleware solution that facilitates easy, ubiquitous, holistic and fast sharing of product and process information across the entire injection production process. In general, PREVIEW will boost the use of a process control systems by reducing the number of visible components, simplifying its installation and improving and optimizing the production process. PREVIEW overall objectives are:
- To reduce mould setup time by developing a holistic methodology for predicting the optimal machine parameters configuration
- To optimize production control by applying AI and Machine learning techniques to analyse real time production data
- To develop a compact wireless-capable data acquisition system for injection moulds and machines
- To improve operational flexibility by implementing robust industrial wireless communication
- To seamlessly provide process information by using an indoor real time location system able to deliver specific information to a determined profile operator
