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Overview

Dr Qing Wang

Associate Professor

BEng MSc PhD CEng SMIEEE, MIMechE MASME FHEA


Affiliations
AffiliationRoom numberTelephone
Associate Professor in the Department of EngineeringE379 (Higginson)+44 (0) 191 33 42381

Biography

Dr. Qing Wang is an Associate Professor within the Department of Engineering at Durham University. Her PhD programme was sponsored by BAE Systems and her doctoral research was carried out to identify and develop Artificial Neural Network techniques for use within the cost model development process. Her ANN techniques have since been successfully applied to the development of consultancy work to establish thermoforming cost models within the Composite Wing Programme at BAE Systems.

Dr Wang has over fifteen years’ experience in research, industrial and project management and has secured funding from the Nuffield Foundation, Knowledge Transfer Partnerships, BP, IMechE, Royal Academy of Engineering, Royal Society, EPSRC and EU for her research. Her research interests focus on product life cycle engineering including cost engineering, virtual manufacturing/remanufacturing systems involved in operations research, large scale metrology and enterprise supply networks design. Since 2010, she has extended her research into product service systems in relation to developing wind turbine condition monitoring techniques. Dr Wang has published two co-authored books and more than 80 papers in refereed journals and international conferences.

Dr Wang is the Associate Editor of IEEE Transactions of Instrumentation and Measurement. She is on the Editorial Board for the IEEE Transactions of Instrumentation amd Measurement, International Journal of Optimisation and Control: Theory and Applications and International Journal of Research in Computer Science. She is also a peer-reviewer for a number of international journals including IJPR, IJAMT, IJPE, IJCIM and IMechE Part B. She has served as an international scientific committee member for several international conferences including ICMR and ICMEEM. She was a Session Chair for the ASME 16th and 17th Design for Manufacturing and the Life Cycle Conferences (DFMLC) in 2011 and 2012, the Program Chair for the ASME DFMLC Conference in 2016 and is the Conference Chair for the ASME DFMLC Conference in 2017. She is a Chartered Engineer (CEng), a senior member of IEEE(SMIEEE), a member of IMechE(MIMechE), a member of ASME(MASME), a member of EC (UK Engineering Council), a Mid-Career Fellow of Durham Energy Institute and a Fellow of the Higher Education Academy.

Student recruitment

Dr. Wang is keen to work with talented students with an education background in maths, electronics, electrical engineering and mechanical engineering on MSc/PhD projects. These projects are likely related to structural health monitoring using nondestructive testing and evaluation; energy storage and transfer ( battery) developing wind turbine condition monitoring techniques; establishing remanufacturing systems for new materials; laser metrology for large scale component measurement; and supply chain optimisation and integration. If you are interested in any of these projects and would like to apply for a position at Durham, please email Dr. Wang with a full resume for further discussion. 

Research interests

  • Product life cycle engineering
  • Sustainable design and manufacturing
  • Supply chain management optimisation and integration
  • Structural health monitoring (No-destructive testing)
  • Electronic instrumentation and mesurement ( advanced measurment method)
  • Wind turbine condition monitoring

Research groups

Publications

Authored book

Chapter in book

  • Wang, Q. (2005). Virtual Manufacturing & Systems. In E-Manufacturing: Fundamentals and Applications. Southampton: WIT Press. 231-263.

Conference Paper

Journal Article

Patent

  • Huang, S. L., Zhao, W., Zhang, Y., Wang, Q. & Wang, S. (2020). Device and method for detecting defect in main shaft of wind turbine. US Patent: Patent No. US 10,605,790 B2. Application filed: 10 August 2017. Granted: 1 January 1970

Supervision students