Latest News:

February 2018

¨ Dr. Feng’s research is featured in an article published in the Cullen College of Engineering News: Cullen College Professor Combines Math and Engineering to Enhance Safety, Efficiency in Oil and Gas Industry.”


October 2017

¨ The talk titled “Assessment of Container Port Efficiency using Data Envelopment Analysisby Sonal Jain and Qianmei Feng has been accepted and scheduled for presentation at the INFORMS in Houston, TX, October 21-25, 2017.

¨ Zhizhong Zhao, an undergraduate student from the Department of Petroleum Engineering, presented his poster “Real-time Monitoring in Drilling: Current Practice and Data Analysis” at UH Undergraduate Research Day, based on the research activities sponsored by the SURF (Summer Undergraduate Research Fellowship) program.


July 2017

¨ Dr. Feng has received a new NSF grant ($348,077) for “Maintenance Planning for Complex Systems in Dynamic Environments” from NSF/CMMI/OE, which will be used to support her research in exploring stochastic degradation-based reliability models and unified maintenance decision-making for heterogeneous complex systems in dynamic environments.


May 2016

¨ Two presentations were delivered by our group at the ISERC 2016 in Anaheim, CA:

· Multi-dimensional Markov Modulated Levy Processes for Multi-dependent Degradation under Dynamic Environments” by Yin Shu, Qianmei Feng, Hao Liu

· Using Degradation with Jump Measures to Estimate Life Characteristics ,” by Yin Shu, Qianmei Feng, Hao Liu

¨ Yin Shu received NSF Student Travel Grant for attending the ISERC 2016. Congratulations!


March 2016

¨ The paper “Levy Driven Non-Gaussian Ornstein-Uhlenbeck Processes for Degradation-Based Reliability Analysis ” by Yin Shu, Qianmei Feng, Edward Kao, and Hao Liu has been accepted by IIE Transactions.


November 2015

¨ Dr. Feng presented a seminar in the Department of Industrial and Systems Engineering at Texas A&M University on November 20, 2015.

¨ Three presentations were delivered by our group at the INFORMS Annual Conference 2015 in Philadelphia, PA:

· “Non-Gaussian Ornstein-Uhlenbeck Processes in Degradation-based Reliability Analysis” by Yin Shu, Qianmei Feng, Edward Kao, Hao Liu

· “Markov Additive Processes For Degradation With Jumps Under Dynamic Environments,” by Yin Shu, Qianmei Feng, Edward Kao, David Coit, Hao Liu

· Physics-of-Failure based Statistical degradation Models for Li-Ion Battery Life Prediction,” by Shufeng Li, Qianmei Feng, Yin Shu

¨ The paper “Reliability Modeling for Dependent Competing Failure Processes with Changing Degradation Rate” by Koosha Rafiee, Qianmei Feng, and David Coit is one of the five most popular articles published in IIE Transactions (2014 and 2015).


October 2015

¨ The paper “Markov Additive Processes for Degradation with Jumps under Dynamic Environments” by Yin Shu, Qianmei Feng, Edward Kao, David Coit and Hao Liu has been selected as one of the three papers for the QSR refereed track best paper competition at the INFORMS Annual meeting in Philadelphia. The other two finalists are Youngjun Choe and Eunshin Byon (University of Michigan), and Kamran Paynabar, Hao Yan and Jianjun Shi (Georgia Institute of Technology).

¨ The talk, titled “Life Distribution Analysis Based on Lévy Subordinators for Degradation with Random Jumps” has been accepted and scheduled for presentation at the 2015 Fall Technical Conference on October 8-9, 2015 in Houston, TX at the Westin Oaks Houston at the Galleria.




Feng Research Group

Text Box: Department of Industrial Engineering

        Our research group conducts research on a variety of quality and reliability problems for complex systems.  Our focus is on integrated quality and reliability models and analysis tools that provide fundamental insights for the successful development and commercialization of evolving technologies, such as Micro-Electro-Mechanical Systems (MEMS), biomedical implant devices, and nanotechnologies.  Our research spans the domains of several fundamental research areas including quality and reliability engineering, probability and statistics, and optimization for advanced evolving technologies, homeland security, and healthcare systems. Our projects have been supported by National Science Foundation (NSF), Department of Homeland Security (DHS)Texas Higher Education Coordinating Board (THECB), Texas Department of Transportation (TXDOT), and UH Grant to Enhance and Advance Research (GEAR).