Philips Aims for Zero Unplanned Equipment Downtime with Predictive Analytics

Medical imaging systems such as MRI and CT scanners must provide optimal clinical performance and predictable cost of ownership. While clinicians understand the need for maintenance, any system downtime can be costly for health service providers. To overcome this challenge, Philips Healthcare is moving from reactive to data-driven, proactive maintenance, utilizing new sources of sensor data along with machine learning models to enable scheduled, predictable and non-intrusive service actions that don’t interrupt regular clinical workflow. Join our latest Data Disruptors webcast to hear Mauro Barbieri, Senior Scientist with Philips Research, discuss how Philips is moving towards zero unplanned downtime of medical imaging systems using remote monitoring and predictive analytics, powered by Vertica. Philips collects and processes data from devices to identify potential problems, reduce the likelihood of costly downtime and minimize impact on patients. The webcast will cover: • Philips' Aiming for Zero program and evolution from reactive to proactive service • How to achieve continuous, data-driven innovation with integrated teams of SMEs, data scientists and business stakeholders • The company’s approach to data integration and predictive model creation • Key aspects of Philips’ predictive maintenance platform and data architecture components