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Failure prediction

Risk-based dynamic pricing leveraging failure prediction

Huijuan Shao R&D Division, Hitachi America, Ltd. Equipment-as-a-service Equipment-as-a-service (EaaS) is gaining popularity in industries as it provides the customers with high flexibility and scalability and allows a service provider to optimize operations so that both the service provider and t...
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hitachi-rd-en @ hitachi-rd-en
Industrial AI BlogAI & Data scienceFailure prediction

Generative adversarial networks for prognostics failure prediction

Shuai Zheng R&D Division, Hitachi America, Ltd. One of the main objectives of predictive maintenance is to predict and identify failures in equipment. This is typically done by monitoring the equipment and searching for any failure patterns. With the increased use of IoT devices, data-driven meth...
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hitachi-rd-en @ hitachi-rd-en
Industrial AI BlogAI & Data scienceDigital service platformsFailure prediction

Failure prediction for multiple connected devices

Huijuan Shao R&D Division, Hitachi America, Ltd. Failure prediction is an important problem in industry and has been studied over decades in various areas. Generally, majority of equipment and industrial components deteriorate after running for a period of time. The failures among multiple device...
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hitachi-rd-en @ hitachi-rd-en
Industrial AI BlogAI & Data scienceManufacturingFailure prediction

Equipment Health Indicator Learning using Deep Reinforcement Learning

By Chi Zhang R&D Division, Hitachi America, Ltd. One of the important objectives in industrial operations is to minimize unexpected equipment failure. Unexpected downtime due to equipment failure can be very expensive for example, an unexpected failure of a mining truck in the field can have a co...
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hitachi-rd-en @ hitachi-rd-en
Industrial AI BlogAI & Data scienceManufacturingFailure prediction

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