- Start: 01/02/2016
- End: 30/11/2018
In this project, a new solution for massive data analysis of GKN Driveline Vigo machines and equipment will be developed, using technologies and scalable Big Data architectures and machine learning techniques. It will be designed as a complete and easily integrated solution with the global plant management system.
The main objective of the project is to develop a tool for the production management of an intensive plant in manufacturing, by monitoring the quality of processes and the predictive control of equipment and manufacturing devices.
BITs 4.0 project aims to generate useful information for, on the one hand, monitoring the quality of manufacturing processes and, on the other hand, predict failures or anomalies in the machines and equipment, getting ahead of the appearance of unplanned stops, ensuring the quality of produced parts and processes and ensuring at any time the factory flows.
Thanks to this tool, it will be possible to:
1. To predict the state of deterioration of the equipment and devices, detecting in an early state the appearance of breakdowns.
2. To check the quality of 100% of the production, through the comparative analysis of parameters that affect to the quality of the process.
3. To optimize the machines efficiency through the optimization of the process conditions and the variation in the volume of produced parts, depending on the state of deterioration of each machine.
AIMEN will collaborate in the specification of conditions and, in the design, integration and validation of the global sensoring and acquisition architecture, for the monitoring and data acquisition, packaging and transmission to the Big Data platform.
- Sectors: Automotive, Food Industry, Metal mechanical, Textile
- R&D&i: Integrated monitoring and control systems
- Contributors: GRADIANT
- Leader: GKN Driveline Vigo
- Partners: GRUPO MATRIGALSA, Ágata Technology
- Acronym: BITs 4.0
- Ambit: Regional
FEDER