The content on this page is intended to healthcare professionals and equivalents.
Improving the uptime through failure sign diagnosis
Achieving higher uninterrupted system availability and optimizing maintenance costs remain challenges for conventional remote support services for medical devices. We have accumulated and analyzed Big Data to develop a new system that utilizes its "Failure Sign Diagnosis Service" to launch "Sentinel Analytics," a failure sign diagnostic service for superconductive MRI systems.
With the failure sign diagnosis based on IoT*2 the inspection and parts replacement cycles can be optimized and the system's up time can be improved.
The Sentinel server monitors the system status 24 hours a day.
When the Sentinel server detects either a malfunction or a lowered performance of the system, an alert is automatically reported to our service site. This helps to prevent the occurrence of a malfunction. Furthermore, a corrective measure is quickly taken in case of malfunction.
This feature provides service via direct connection of the service site and your system.To track down the causes of a malfunction, we check artifacts and abnormal images, check image data before reconstruction (raw data) and run test programs on the system.
Such features as encryption of communication data and communication based on mutual authentication are available to protect patient information. Furthermore, the specification does not allow recognition of personal information included in Patient Lists and images (such as an patient's name, sex, weight, age, and date of birth) on the Sentinel server and the Service Site.