Predictive system to recommend Injection mold setup in wireless - PowerPoint PPT Presentation

Predictive system to recommend Injection mold setup in wireless sensor networks This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 636892 04/08/2015 1

PREDICTIVE SYSTEM TO RECOMMEND INJECTION MOLD SETUP IN WIRELESS SENSOR NETWORKS cavity pressure 500 machine pressure 400 800 300 Cloud-based 200 600 computing 100 400 Advanced 0 Industrial 200 0 500 1000 1500 2000 2500 3000 3500 4000 Predictive Wireless 0 0 500 1000 1500 2000 2500 3000 3500 4000 System Comms Data acquisition Mould DNA system cavity pressure Mould and Machine 500 400 parameters 300 200 100 0 0 500 1000 1500 2000 2500 3000 3500 4000 Location based Recommended content delivery setup parameters based on historical data Optimal cavity pressure 800 600 Optimal machine pressure 400 800 200 600 400 0 0 500 1000 1500 2000 2500 3000 3500 4000 200 0 0 500 1000 1500 2000 2500 3000 3500 4000 This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 636892 04/08/2015 2

GOALS The goals of the PREVIEW project are to: • Design and develop a Data Acquisition System responsible for the adaption, amplification and digitalisation of the cavity and machine signals. • Develop an Advanced Predictive System (APS) to optimise the injection moulding process by reducing mould set up time and providing a quality control system. • Develop a robust Industrial Wireless Network to transport sensor data to the APS server. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 636892 04/08/2015 3

EXPECTED BENEFITS • A reduction in mould setup times • A reduction in scrap and energy consumption • An increase in productivity and flexibility with fast response against changes or new customer demands This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 636892 04/08/2015 4

THE CONSORTIUM SME-NL E ND U SERS SME-IT SME-HU E XPLOITATION SME-ES VALIDATION LE-UK TECHNOLOGY (Coordination RTD-ES) LE-IL UNI-GE This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 636892 04/08/2015 5

GENERAL INFORMATION Number of partners FoF-1-2014 CPS-based process optimisation of manufacturing Duration 3 years Number of partners 8 Budget €3.2 million Website www.preview-project.eu Project Co-ordinator: Jesús Pablo González Eurecat email : jesuspablo.gonzalez@ eurecat.org This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 636892 04/08/2015 6