Holistic customer-oriented service optimization for fleet availability

Project leader: Björn Eskofier, Johannes Roider
Start date: 1. June 2021
End date: 31. May 2024
Funding source: Siemens Healthineers AG, d-hip

Abstract

The main goal of this project is to improve customer service processes and customer satisfaction. We analyze event data from various sources like customer service activities and IoT data from high-end medical devices. The data is used in combination to implement solutions for real-time diagnosis of machine failures and to predict outcomes of customer service processes.

Methods designed and used include:
– Deep Learning
– Process Mining
– Predictive Business Process Monitoring
– Data Fusion