Contact Dr Samir Khan
- Email: Samir.S.Khan@cranfield.ac.uk
Areas of expertise
- Sensor Technologies
- Throughlife Engineering Services
Dr. Samir Khan his BEng and PhD from Loughborough University. He was the leading researcher working on the No-Fault Found research project between 2011-2015, at the Through-life Engineering Services Centre within Cranfield University, collaborating with Rolls-Royce, Jaguar Land Rover, BAE Systems, and MoD. In particular, he has developed machine learning solutions for aeronautical systems. Other research work includes performing fault analysis and condition monitoring from track-side feedback sensors, development of IoT technologies, analytics platforms for maintenance decision making and intelligent monitoring of intermittent failures and false alarms in electronic systems. He is a chartered engineer and a member of IEEE and IET.
Articles In Journals
- Khan S, Farnsworth M, McWilliam R & Erkoyuncu J (2020) On the requirements of digital twin-driven autonomous maintenance, Annual Reviews in Control, 50 13-28.
- Erkoyuncu JA, Roy R, Shehab E, Durugbo C, Khan S & Datta P (2019) An effective uncertainty based framework for sustainable industrial product-service system transformation, Journal of Cleaner Production, 208 160-177. Dataset/s: 10.17862/cranfield.rd.7182446
- Khan S, Liew CF, Yairi T & McWilliam R (2019) Unsupervised anomaly detection in unmanned aerial vehicles, Applied Soft Computing, 83 (October) Article No. 105650.
- McWilliam R, Khan S, Farnsworth M & Bell C (2018) Zero-maintenance of electronic systems: Perspectives, challenges, and opportunities, Microelectronics Reliability, 85 (June) 122-139.
- Khan S & Yairi T (2018) A review on the application of deep learning in system health management, Mechanical Systems and Signal Processing, 107 (July) 241-265.
- Khan S, Gorringe C & Farnsworth M (2018) Evaluating diagnostic failures during system design, CIRP Journal of Manufacturing Science and Technology, 21 (May) 97-109.
- Khan S, Farnsworth M & Erkoyuncu J (2017) A novel approach for No Fault Found decision-making, CIRP Journal of Manufacturing Science and Technology, 17 (May) 18-31.
- Erkoyuncu JH, Khan S, Hussain SMF & Roy R (2016) A framework to estimate the cost of No-Fault Found events,, International Journal of Production Economics, 173 (March) 207-222. Dataset/s: 10.17862/cranfield.rd.5472904.v1
- Khan S, Goodall RM & Dixon R (2012) Non-uniform sampling strategies for digital control, International Journal of Systems Science, 44 (12) 2234-2254.
- Hockley C, Jennions IK, Khan S & Phillips P (2015) No fault found: the search for the root cause. SAE International.