Through the proliferation of sensors, smart machines, and instrumentation, industrial operations are generating ever increasing volumes of data of many different types and our customers are demanding solutions that provide business value over this collected data. In our interactions with customers across verticals, we have discovered that there is an urgent need for predictive maintenance solutions that meet customer demands. The reason for the appeal of predictive maintenance solutions is their ability to increase equipment availability, reduce the cost of unexpected failures and make operations more predictable. Hitachi offers a portfolio of data analytics technologies to address predictive maintenance use cases in a variety of verticals and in this paper we present an overview of our work in this area.
Big Data Lab, Global Center for Social Innovation North America, R&D Division, Hitachi America, Ltd. He is currently the Chief Data Scientist and Department Manager at the Big Data Lab.
Big Data Lab, Global Center for Social Innovation North America, R&D Division, Hitachi America, Ltd. He is currently engaged in the development of new technologies for predictive maintenance.
Big Data Lab, Global Center for Social Innovation North America, R&D Division, Hitachi America, Ltd. He is currently engaged in the development of new technologies for fleet analytics and predictive maintenance.
Big Data Lab, Global Center for Social Innovation North America, R&D Division, Hitachi America, Ltd. He is currently a Senior Fellow and manages the Silicon Valley Research Center, Global Center for Social Innovation North America.
