Industrial Internet: Let’s Drive Deep into Wind – Cutting Costs for Energy Producers by 1 cent per kW hr.
How can I be certain of the return on investment of my wind turbines fleet and reduce cost per kw/h by 1c? Asset managers for wind turbine fleets are using new solutions to predict and extend gearbox life months to years in advance. Model-based prognostic technology enables this ability to predict failures and fail understand how operational or maintenance changes today will improve life and return on investment. With DigitalClone Live, these models are deployed on what GE calls the Industrial Internet. Sentient Science’s Wind Energy task force will discuss how the prognostic models are deployed and the overall benefits of turning over assets Industrial Internet.
Raja V. Pulikollu, PhD
Director, Implementations & Chief Materials Scientist
Dr. Pulikollu is responsible for the commercial implementation of DigitalClone solutions and for the research and development of DigitalClone Material. His expertise includes material science, mechanical metallurgy, prognostics and health management, fatigue and fracture mechanics, probabilistic life prediction methods, and micro-structural analysis. He holds a Ph.D. in Material Science from Wright State University.