Newspaper press maker manroland Goss has launched a major update of its AI-assisted Maintellisense maintenance platform.

Introduced in 2019, the data-driven application has been used to increase systems reliability and productivity. Now monitoring of press and production data has been individualised and automated, so that customers are automatically notified of relevant deviations.

A new look and feel also highlights ease of use with its clear design language, delivering “minimal maintenance, only when required” through a modern Industry 4.0 solution. Based on analysed press parameters, the digital maintenance platform provides information on necessary or sensible measures in print production.

“Maintellisense enables us to carry out maintenance in a more targeted and predictive manner,” says chief executive Franz Kriechbaum. “Thanks to intelligently-evaluated information, we know when and where we need to start maintenance – and which parts of the system to check. Maintellisense thus ideally complements our reliable and competent service.”

The web application compares individual production data with similar presses to identify potential issues, using a database is derived from worldwide installed press historical data and the technical knowledge and expertise of more than 375 employees involved in the development process.”

With data protection of particular importance, data is stored on German servers in accordance with German data protection laws.

Among global users is Druck Styria, where operations assistant Dirk Destaller says the Austrian company has already been able to avoid several major shutdowns. “In today’s world it is essential to be able to detect possible downtimes at an early stage.”

With the focus for 2023 and beyond on Big Data for more sustainable and efficient production, a specially-developed IoT-box will make it be possible to combine various measured values with production data to allow further relevant perspectives.

By connecting various sensors, users can decide for themselves which resources they want to monitor. This will make it possible to determine the consumption of resources for a single product or the effect of adjusting the production speed on the consumption of operating materials and more.