Hitachi Predictive Maintenance solution helps organizations assess assets, diagnose problems using monitoring tools like sensors and image analytics, design the appropriate solution leveraging advanced algorithms and machine learning principles and deploy sustainable and repeatable maintenance solutions and an optimized asset lifecycle maintenance plan.
Hitachi Consulting and Hitachi Rail are bringing together the best of Hitachi to realize our vision of a digital railway that will deliver an enhanced and total passenger experience. We are exploiting Big Data and advanced analytics used for asset monitoring and predictive maintenance for the rail industry.
Drive significant gains in operational efficiencies across production, maintenance, quality, scheduling and logistics using IoT, advanced analytics and machine learning. Enable timely decision-making and environmental sustainability through continuous monitoring of machines, people and processes.
Signs of impending failure are detected and maintenance is scheduled before a breakdown, resulting in reduction of downtime by 16.3%.
Hitachi Predictive Maintenance is most relevant for industries that rely heavily on any mechanical assets such as machinery, robotics or IoT to run operations.
Get a closer look at how Hitachi can help you improve overall asset availability, reliability and lifetime value, while lowering maintenance costs.
Rajesh Devnani leads the Global Solutions Management function. His focus is on creating differentiated world-class solutions leveraging Hitachi Group capabilities. He is a part of the organization’s intellectual think tank chartered with driving the solutions-led organizational transformation.
David McGraw is part of Hitachi’s Solution and Innovation team specializing in IoT and the application of advanced analytics as a solution architect for a breadth of different use cases including PdM, PdQ, Visual Analytics and dynamic scheduling specific to transportation and manufacturing.
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