Digital Twin

The malfunction of machines and systems always poses a significant cost burden for companies. Costs of 120,000 euros or more per hour are not seldom for such downtimes.1  Profitability relies heavily on smooth operations and production. Unplanned downtimes exacerbate the situation, making it challenging to predict timing, duration, and associated costs.  To mitigate these risks, implementing optimized maintenance planning is advisable. Predicting specific error patterns is a crucial step toward condition-based maintenance, enhancing predictive maintenance strategies. The team at Dunkermotoren's digital brand, nexofox, specializes in preparing the manufacturer's drive systems for such maintenance approaches.  Adhering to the philosophy of "More than Motors," nexofox progressively expands the software product portfolio of Dunkermotoren, an AMETEK brand. A key component is the "Predictive Maintenance" software, offering customers a new option for automatic, condition-based monitoring of their entire drive systems. This software not only alerts customers to impending failures but also provides continuous updates on the system's current status. One distinct advantage of nexofox's "Predictive Maintenance" is its reliance solely on existing motor sensors, eliminating the need for additional electronic components. This approach not only saves space but also offers significant cost savings.  Predictive Maintenance in Detail In the initial stage of condition-based drive monitoring, the focus is intentionally placed on assessing the wear of the mechanics linked to the motor. This approach aims to optimize mechanical service life by detecting typical, gradual wear effects, such as those on an attached gearbox. Moreover, customers receive immediate alerts regarding abrupt changes that could potentially result in an unplanned downtime if not addressed promptly. Accurate detection of specific fault patterns necessitates collaboration with the customer, as they have the most detailed knowledge about their application's structure and can appropriately classify fault patterns. The initial version of nexofox's predictive maintenance solution offers customers a standardized basis as a tool for anomaly detection and unplanned downtime reduction, with room for individual adaptations. Like all nexofox software products, Predictive Maintenance is provided to customers as a Docker container, ensuring seamless integration into any existing industrial IoT solution without requiring a permanent internet connection. Predictive Maintenance operates locally on the EDGE gateway utilized by the customer. An internet connection is only necessary if the customer opts to share metadata with the nexofox team. However, consent is not obligatory for the software's full functionality. Nonetheless, the parameters processed by the software contribute to the ongoing optimization of the software´s algorithm. Subsequently, customers will have access to the latest algorithm version through regular updates. Downloads: Predictive Maintenance à la nexofox (PDF)