Predictive maintenance in the metal industry

Thanks to artificial intelligence, automatic learning (Machine Learning), Big Data and the Internet of Things (IoT) we’re able to carry out plant maintenance in a more intelligent way, using the available resources more efficiently, as well as anticipating possible failures using predictive techniques (predictive maintenance) with the consequent savings in time and costs. Predictive maintenance is a developing field that makes it possible to analyze machine and/or process parameters, detecting abnormal behavior in advance that, if not repaired, could go on to cause an unexpected failure, allowing us to resolve problems before they even occur.

Opportunities of the digital transformation of industrial machinery

When facing the current environment of Volatility, Uncertainty, Complexity and Ambiguity (VUCA) which is also highly competitive, the digitization of industrial material is an essential differential value in order to quickly adapt to market requirements. It’s a must in order to optimize plant production and respond to new consumption habits that require agile, personalized manufacturing in record times.

Cyber security or how to manage vulnerabilities in industrial environments

Incorporating intelligence into factories is necessary in order for any industrial plant to compete in the 4.0 ecosystem, increase productivity and offer a personalized product and/or service, but this implies dealing with new vulnerabilities and, consequently, new security threats because machines, processes and information systems have to be in open networks, connected to the Internet, which increases exposure to cyberattacks.