Recent NSF Award for Intuitive Predictive Maintenance of Industrial and Agricultural Equipment

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The SRSL team recently received an award from the National Science Foundation (NSF) to investigate probabilistic and explainable deep learning for the intuitive predictive maintenance of industrial and agricultural equipment. The approach will not only predict the remaining useful life of a machine component, but it will also quantify the uncertainty of a prediction. As a result, maintenance decisions can be made from a risk-based perspective, eliminating unnecessary maintenance stemming from low-confidence predictions. This STTR Phase I project is in collaboration with a local-to-Iowa industry partner, Percēv (a subsidiary of Grace Technologies) and Grace, and is set to be completed in November 2021.

Rising Stars Spotlight: Venkat Nemani and Jinqiang Liu

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Congrats to Venkat and Jinqiang for being recognized as “Rising Stars” by The REMADE Institute. Both have made outstanding contributions to our REMADE project titled “Data-Driven Design Support for Re-X of High-Value Components in Industrial and Agricultural Equipment”. Read more about their work on this project through the links below:

Interview with Venkat Nemani

Interview with Jinqiang Liu

Venkat and Jinqiang – Well done and well deserved! Congratulations!

Todd and Rohan Joined Our Group!

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Todd Thompson and Rohan Rao joined SRSL for their Ph.D. studies. Todd is a Staff Engineer in the John Deere Power Systems group. He will work on his doctoral research at ISU while working at Deere. Prior to joining SRSL, Rohan obtained his Bachelor’s degree from IIT Bombay in India and spent two years working as an Engineer at TEX E.G. Co., Ltd. in Japan. Welcome, Todd and Rohan!

New Funding for Battery Early Life Prediction Research

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SRSL has received research funding from the Iowa Energy Center, administrated by the Economic Development Authority (IEDA), for a collaborative project with Alliant Energy, SunCrate Energy, and Iowa Lakes Community College. This project is titled “Predicting Battery Lifetime with Early-Life Data for Grid Applications.” This two-year project ($280K in total) will develop a new software tool that harnesses the power of machine learning to accelerate the evaluation of battery lifetime in grid applications. The ISU Co-PIs are Dr. Anne Kimber (ECpE), Dr. Zhaoyu Wang (ECpE), and Dr. Gül E. Kremer (IMSE).

Dr. Hu Gave Keynote Speech at UQOP 2020

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On November 16th, 2020, Dr. Hu gave a keynote speech at the International Conference on Uncertainty Quantification & Optimisation (UQOP 2020) held as a virtual event. The title of his talk is “Engineering Design under Uncertainty and Probabilistic Failure Prognostics – Methods, Progress, and Challenges.” This talk focused on addressing the uncertainty issues in the reliability-based design of an automotive component and the remaining useful life prediction of lithium-ion batteries.

New Funding for Design for Reman Research

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SRSL is part of two R&D projects, funded by the Department of Energy (DOE) through the REMADE Institute, to study and advance design for sustainability (REMADE  Announcement). One project is titled “Quantification of Financial and Environmental Benefits Tradeoffs in Multi-Generational Product Family Development Considering Re-X Performances,” led by the University of Illinois at Urbana-Champaign; the other project is titled “Design Iteration Tool to Sustain Remanufacturability,” led by Iowa State University. Both projects are two years in duration and represent efforts to support and facilitate university-industry collaboration.