Biography
Ajith Kumar Parlikad is a University Senior Lecturer at Cambridge University Engineering Department. He is based at the Institute for Manufacturing, where he is the Head of the Asset Management research group. He is the MET IIB course director and a Fellow and Tutor at Hughes Hall.
Ajith leads research activities on engineering asset management and maintenance. His particular focus is examining how asset information can be used to improve asset performance through effective decision-making. He actively engages with industry through research and consulting projects. He is also a member of the steering committee of the IFAC Working Group on "Advanced Maintenance Engineering, Services and Technology".
Ajith joined Cambridge University to read for his PhD degree, which he successfully completed in August 2006. For his PhD, he developed a methodology for quantifying the benefits of improving product information availability and quality on the effectiveness of product recovery processes.
Research
Publications
Zomer, T., Neely, A., & Parlikad, A. Institutional pressures and decoupling in construction projects: an analysis of Building Information Modelling implementation. Proceedings of the 36th Annual ARCOM Conference, 325-334.
Zomer T., Neely A., Sacks R., Parlikad A. (2021) A Practice-Based Conceptual Model on Building Information Modelling (BIM) Benefits Realisation. In: Toledo Santos E., Scheer S. (eds) Proceedings of the 18th International Conference on Computing in Civil and Building Engineering. ICCCBE 2020. Lecture Notes in Civil Engineering, vol 98. Springer, Cham. https://doi.org/10.1007/978-3-030-51295-8_29
Moving from building information models to digital twins for operation and maintenance (Lu, Q., Xie, X., Parlikad, A.K., Schooling, J.M. and Konstantinou, E., 2020.)
Qiuchen Lu; Ajith Kumar Parlikad; Philip Woodall; Gishan Don Ranasinghe; Xiang Xie; Zhenglin Liang; Eirini Konstantinou; James Heaton; and Jennifer Schooling; 'Developing a Digital Twin at Building and City Levels: Case Study of West Cambridge Campus', Journal of Management in Engineering, Volume 36 Issue 3 - May 2020
Xie, X., Parlikad, A.K. and Puri, R.S., 2019, October. A Neural Ordinary Differential Equations Based Approach for Demand Forecasting within Power Grid Digital Twins. In 2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) (pp. 1-6). IEEE. https://doi.org/10.1109/SmartGridComm.2019.8909789
Final Report - Exploiting traffic data to improve asset management and citizen quality of life
Lu, Q., Xie, X., Parlikad, A.K. and Schooling, J.M., 2020. Digital twin-enabled anomaly detection for built asset monitoring in operation and maintenance. Automation in Construction, 118, p.103277. https://doi.org/10.1016/j.autcon.2020.103277
Xie, X., Lu, Q., Rodenas-Herraiz, D., Parlikad, A., & Schooling, J. (2020). Visualised inspection system for monitoring environmental anomalies during daily operation and maintenance. Engineering, Construction and Architectural Management https://doi.org/10.1108/ECAM-11-2019-0640
