Zhenglin joined DIAL in 2011 as a doctoral student. Since February 2016 he has been working as a research associate.


Zhenglin completed a BEng degree with 1st class honors in electrical and electronic engineering at the Manchester University and a MEng degree in communication and signal processing at the Bristol University. After completing his PhD in January 2016, Zhenglin has been working as a research associate. Part of his research is to help companies, such as Hitachi, to improve performance of their predictive maintenance of their asset management systems.


Currently, he is working on the maintenance optimization for bridge portfolio as a part of the Centre for Smart Infrastructure and Construction (CSIC) project.



Research interests

  • Condition-based maintenance
  • Stochastic process 
  • Maintenance optimisation
  • Power transformer maintenance




Zhenglin Liang, and Ajith Kumar Parlikad. 2015. “A Condition-Based Maintenance Model for Assets with Accelerated Deterioration Due to Fault Propagation.” IEEE Transactions on Reliability, 64(3), pp.972-982


Zhenglin Liang, and Ajith Kumar Parlikad. 2014. “A Tiered Modelling Approach for Condition-Based Maintenance of Industrial Assets with Load Sharing Interaction and Fault Propagation.” IMA Journal of Management Mathematics, dpu013.


Ajith Kumar Parlikad, and Zhenglin Liang. 2012. “Condition Based Maintenance for Complex Engineering Assets: A Multi-Layered Modelling Approach.” In Advanced Maintenance Engineering, 2:73–78.


Zhenglin Liang*, Khashayar Mahani*, Ajith Kumar Parlikad and Mohsen A. Jafari. "Top-down Maintenance Strategy for Assets within Operational Dependent Multi-unit System" Submitted to IEEE PES Transcations on Sustainable Energy. (* these authors contributed equally to the completion of this work)


Zhenglin Liang, Ajith Kumar Parlikad, Rengarajan Srinivansan and Nipat Rasmekomen. "On Fault Propagation in Deterioration of Multi-component Systems" Submitted to European Journal of Operational Research.


Contact Details

T: +44 (0) 1223 766141
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