GRINDING4.0

GRINDING 4.0

Smart 4.0 machine cell model for automotive cutting tool grinding services

The aim of the project is to create a smart grinding operation cell for the tooling industry, fully connected to the automotive industry end users. The research is part of the Industry 4.0 approach, which aims to connect production machines so that they can be monitored remotely.

Domaine: Manufacturing 

Asset: FADI 

Factsheet:

Description

Objectives

Grinding 4.0 intends to produce a new generation of grinding/cell machines and auxiliary equipments, which will be integrated into a new manufacturing environment concept, that initially will be focused to the automotive market, allowing these to integrate the subcontracted companies to give a fully 4.0 adapted services in their value chain.Retour ligne automatique The grinding cell manufacturer DOIMAK aims to maintain its leading position in the grinding machine tool market. CTMS needs to offer last generation intelligent services with zero defects and repetitive systems for non qualified operators. MicroMegaDynamics is willing to expand to the market of machine tool machining on-line supervision apart of its core vibration sensors activity. Finally, CETIC objective is to expand its knowledge on industry specific needs for IT tools for BigData.

Results

The project targets the development of connected grinding machines ready to be inegrated in Industry 4.0 plants. DOIMAK will exploit the results as a 4.0 concept kit offered in future machine to the market. CTMS will propose the first fully automated hob sharpening intelligent cell, that could be installed with no need of high qualified technical staff, and remotely manageable. MicroMegaDynamics will expand its business through a new product range including sensors, connectivity and web based customer users interfaces. CETIC target building of a generic data analysis and visualisation tool chain for industrial sector deployable on Cloud Computing environments.

Added value

Grinding cell management will evolve from a reaction mode to a predictive mode, with a strategy based on data acquisition, analysis and knowledge generation from integration and online monitoring.