The Jeuns

“Utilizing Cumulocity IoT for Innovations in IoT and AI with SAP Asset Performance Management”

April 23, 2024 | by The Jeuns

SAP Asset Performance Management (APM) is a cutting-edge solution designed to assist S/4HANA and Enterprise Asset Management (EAM) customers in developing maintenance strategies and managing asset health through a closed-loop business process. By incorporating AI and sensor data, APM enables customers to minimize the risk of asset failure and make quicker, more accurate maintenance decisions.

Incorporating Internet of Things (IoT) technology into the APM solution is crucial, as it provides the foundational capabilities required to connect and manage devices, as well as ingest sensor data for remote equipment monitoring and analytics. Many asset-intensive industries worldwide are facing challenges in consolidating their operational technology systems and gathering sensor data from various sources to shift towards more condition-based and predictive maintenance approaches.

To facilitate this transition, SAP will integrate Cumulocity IoT, a leading Industrial IoT platform, into SAP Asset Performance Management. This integration aims to simplify connectivity scenarios, enable seamless management of IoT devices, and continuously monitor asset health in a closed loop using AI and rule-based technologies in real-time. The incorporation of Cumulocity IoT will enhance the capabilities of SAP Asset Performance Management by providing advanced device management and connectivity features.

Furthermore, the rise of artificial intelligence (AI) is driving increased adoption of IoT as AI can extract valuable insights from vast amounts of sensor data. SAP Asset Performance Management leverages SAP AI Core to detect anomalies in equipment behavior that could lead to potential failures based on IoT sensor data. This anomaly detection capability is user-friendly for reliability engineers, enabling them to quickly deploy it to monitor equipment sensor data and receive alerts for any detected anomalies.

Examples of anomaly detection in customer projects include monitoring filling valves on a beverage production line, air filters on transportation trucks, and electric motors on rotating equipment. This AI-based predictive maintenance capability is adaptable to various asset classes and equipment types, learning from customers’ equipment data over time.

A preview of the AI-based Anomaly Detection feature, set to be available in May, can be viewed in a provided video link. Additionally, SAP announced at the Hannover Messe event their plan to integrate Cumulocity IoT into SAP Asset Performance Management later in the summer. Stay tuned for updates on the official Roadmap Explorer link.

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