manrolandGoss has launched a major update of its AI-assisted maintenance platform, automating and individualising monitoring of press and production data.
Launched in 2019, Maintellisense has become an integral part of the press maker’s service portfolio, its main aim being to increase reliability and productivity, and sustainably reduce costs.
Now if the web application detects a relevant deviation, the customer is notified automatically. A new look and feel also highlights ease of use and pioneering approach with clear design language.
manrolandGoss says the focus is on minimal maintenance, only when required. Using analysed press parameters, it provides information on “necessary or sensible” measures in print production, enabling maintenance to be undertaken in a more targeted and predictive manner – when and where we need to start maintenance – and which parts of the system to check.
The application compares individual production data with similar presses to identify potential issues. The 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 of the application to continuously enhance it.
For maximum security, data is stored on German servers in accordance with German data protection laws.
Among customers using Maintellisense, Druck Stryia operations assistant Dirk Destaller says the Austrian printing company has been able to avoid several major shutdowns in a year-and-a-half of use. “We decided to use the new software because we realized that in today's world it is essential to be able to detect possible downtimes at an early stage. The prospect of a smart solution also made the decision process easier for us, with the application continuously developing in line with Industry 4.0.”
A specially developed IoT-box will make it possible to combine various measured values with the production data to allow further relevant perspectives on the machine. By connecting various sensors, a user can decide which resources to monitor, making it possible, for example, to determine the consumption of resources for a single product or the effect of adjusting the production speed on the consumption of operating materials.