In order to avoid machine failures and downtimes, plan personnel deployment efficiently and reduce costs by optimizing the operating states of the systems, it is advisable for companies to implement a predictive maintenance system that is geared towards overall system effectiveness. By calculating a theoretical optimum, it is possible to ensure high system availability, display maintenance cycles and install automatic upgrades. In addition, retrofit recommendations can be generated to keep the machine running at peak performance, troubleshooting can be shortened in the event of a fault and the overall system can be controlled and monitored more easily.

Requirements for implementation
The objective of preventing downtime and proactively saving costs requires a forward-looking approach that is independent of the size of a company. The study "Successful automation in toolmaking" by the Fraunhofer Institute for Manufacturing Engineering and Automation and the WBA Aachener Werkzeugbau Akademie illustrates just how vital digitalization and automation are for companies. According to the study, toolmaking must evolve from its tradition as a mostly craft-oriented trade to industrial production in order to survive in international competition. A key element of this is a digitalization strategy that includes the thorough and reliable collection and evaluation of process data in the company.

Support on the machine
The aim of a predictive maintenance system is to keep the entire system in optimum operating condition and prevent downtime. The first step is therefore to enable the system to be monitored by implementing such a management system: New systems are already equipped with it, existing systems can be optionally retrofitted. The next step is to assign access rights: Evaluations, status queries and production figures are provided on a user-dependent basis. Operators receive optimum online support at the machine. This means that information on operating resources, sub-systems and system statuses is available at all times. Service, maintenance and spare parts management can be carried out proactively, saving time and money.

All data at a glance at the touch of a button
The Trapo Intelligent Management System, or Tim for short, from Trapo enables predictive maintenance by specifying needs-based maintenance work and servicing technical systems. The core objective is to keep the entire system in optimum operating condition and prevent downtime. This is because in an automated environment with virtual processes on the customer side, more effective and safe processes can be systematically established while reducing costs and conserving resources.

"The pandemic has shown that intelligent networking will determine the future of the globalized working world," explains Marcus Schulte, Head of IT at Trapo. "With Trapo-specific tools, we provide online support for commissioning, predictive maintenance and service issues. This applies to all processes - from design approval to FAT and predictive maintenance." as