Data analytics solution that includes data collection, characterization engineering and process modeling.
In an Industry 4.0 context, some of the problems affecting the manufacturing industry are:
- Increase of efficiency in the production and availability of productive resources (machines and people)
- Prevention of quality failures
- Predictive maintenance of machinery, anticipating problems.
One way to address these three challenges can be by sensing and using data analytics applied to solve them in the way Tecnalia has packetized Manufacturing Analytics. Manufacturing Analytics comprises a modular package including:
1. Data Collection: By adding of existing systems (PLCs, SCADA), sensors (vibration meters, thermocouples) or acquisition modules “black box” connected to the machines. In this sense, all machine parameters are acquired.
2. Engineering characterization (feature engineering). Over all the information collected, it is necessary to move from Big Data to “Selective Data” to choose the variables that really have a specific weight in the process.
3. Modelling of the process through data analytics. It attempts to correlate the key variables and look for patterns of cause and effect to solve the problems to be addressed. Facing challenges such as machine predictive maintenance is a value that the machine manufacturer can offer his customers. In turn, improved availability due to an eventual problem anticipation can prevent loss of millions of euros to the manufacturing company.
Technologies and key concepts:
- Big Data
- Predictive Maintenance
- LOIRE (GESTAMP)
Connected industry 4.0 axes:
3. Solutions applicable to business models, 3.1. Services platforms, 3.1.1. Cloud, 3.1.3. Analytical data, 3.4 Solutions for treatment and analysis of large volumes of information, 4. 2. Specific solutions for the automotive industry, 4. Specialized sector solutions, 4.0 Connected Industry, 4.14. Other sectors