Global Companies Team Up to Produce New IoT Solution

Engineering Ingegneria Informatica and Comau have signed a global cooperation agreement to develop solutions for predictive maintenance and analysis of field data using the Internet of Things (IoT) and Big Data Analytics.

The companies joint-developed solutions will be marketed toward the manufacturing industry, including companies operating in the automotive, industrial manufacturing, food and beverage, pharmaceuticals and white goods sectors, per the Industry 4.0 paradigm.

The two partner companies seek to predict malfunctions or a full stop of machines and to intercept negative trends in production process quality. Maintenance and production processes can then accelerate, benefiting the competitiveness of companies operating in global markets.

In recent years there has been a steady increase of technologies (IoT, collaborative robots, data analytics) and paradigms (Industry 4.0) able to reach and sustain the increasingly higher levels of efficiency, quality, productivity and time-to-market required of the manufacturing industry by the market. To address these challenges and respond to the profound transformation taking place in production processes, Comau and Engineering are providing innovative companies with their expertise and experience to the Industrial Automation and Information and Communication Technology sectors respectively.

“The agreement signed with Engineering is an important element in our strategy to make industrial automation increasingly ‘open’ and easy-to-use,” said Mauro Fenzi, CEO of Comau. “This collaboration and especially the synergy that comes from uniting the know-how of our two companies allows us to guide manufacturing companies toward changing production processes, with particular reference to the context of the so-called fourth industrial revolution.”

Paolo Pandozy, CEO of Engineering, commented, “Thanks to the complementary nature of our combined expertise and solutions, we can provide the market with the unique ability to improve the quality and cost effectiveness of automated production processes using the most modern field data collection and analysis technologies.”