Hitachi Case Studies Predictive maintenance of medical devices based on years of experience and advan

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	Predictive maintenance of medical devices based on years of experience and advan Hitachi

Predictive maintenance of medical devices based on years of experience and advan

Hitachi

Technology Category	Analytics & Modeling - Machine Learning Analytics & Modeling - Predictive Analytics
Applicable Industries	Healthcare & Hospitals
Applicable Functions	Maintenance
Use Cases	Predictive Maintenance
Challenge	Failure prediction by human operators requires advanced skills, and the limited number of experts cannot monitor all MRI systems around the world. "Corrective maintenance" for repairs after breakdowns has also become inevitable. Read More
About Customer	Kashiwa Health Check Clinic in Chiba, Japan Read More
Customer Name	Kashiwa Health Check Clinic Read More
Solution	Hitachi analyzed three years’ worth of sensor data from 100 MRI systems and created a mechanism to investigate the cause patterns that lead to device failures. Then machine learning was used to define a normal operational state to achieve successful early detection of abnormalities and changes in status that lead to failures. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Machine Learning

Analytics & Modeling - Predictive Analytics

Applicable Industries

Healthcare & Hospitals

Applicable Functions

Maintenance

Use Cases

Predictive Maintenance

Challenge

Failure prediction by human operators requires advanced skills, and the limited number of experts cannot monitor all MRI systems around the world. "Corrective maintenance" for repairs after breakdowns has also become inevitable.

About Customer

Kashiwa Health Check Clinic in Chiba, Japan

Customer Name

Kashiwa Health Check Clinic

Solution

Hitachi analyzed three years’ worth of sensor data from 100 MRI systems and created a mechanism to investigate the cause patterns that lead to device failures. Then machine learning was used to define a normal operational state to achieve successful early detection of abnormalities and changes in status that lead to failures.

Impact #1	[Efficiency Improvement - OEE] Schedule maintenance before systems break down has been made possible
Impact #2	[Cost Reduction - Maintenance] Improve medical services and reduce costs for hospitals

Impact #1

[Efficiency Improvement - OEE]

Schedule maintenance before systems break down has been made possible

Impact #2

[Cost Reduction - Maintenance]

Improve medical services and reduce costs for hospitals

Benefit #1	Equipment downtime has been reduced by 16.3% compared to before its introduction

Benefit #1

Equipment downtime has been reduced by 16.3% compared to before its introduction

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Overview

Predictive maintenance of medical devices based on years of experience and advan

Operational Impact

Quantitative Benefit