Matthew obtained his MSc (Eng) degree from the University of Hong Kong, Master of Aviation from Massey University (New Zealand), Master of Business Administration from University of Macau and Bachelor of Business Administration (Business Computing) from the University of East Asia in Macau. Matthew is the Fellow of Institution of Railway Signal Engineers (FIRSE), Chartered Electrical Engineer with MIET, MHKIE and MCIE professional membership.
With over 34 years of professional railway engineering experiences in signalling design, rail systems design and system assurance experiences, Matthew has been involved in Nicaragua Canal Project as QSE Manager, Lead System Assurance Engineers for Taiwan High Speed Railway Project (Nangang Extension) and Senior Consultant in WSP consultancy firm.
Currently, he is the Operation Assurance Manager of the Express Railway Line (XRL) under signalling trackside equipment maintenance contract.
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SMART Railway maintenance is crucial for the operations of current MTR SMART railway systems, as these are subject to strict requirements in terms of efficiency, cost-effectiveness, quality of service and scalability. Existing solutions for railway maintenance are, traditionally, either reactive or periodical, which are far from optimal. Nowadays, China Railway Construction (HK) Limited (CRCC) tends to take advantage of emerging techological tools and techniques, such as robotic systems, cloud-based operation, and intelligent data processing and information extraction/inference for supporting MTR SMART Railway operations. In fact, predictive maintenance is the core paradigm of what is now called Smart Railway Maintenance. This presentation provides an insight into Smart Railway Maintenance technologies, by introducing existing approaches to railway maintenance systems, identifying their limitations with respect to current requirements, presenting technologies with potential for supporting future Smart Railway Maintenance systems.
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Date: 24 March 2023 (Fri)
Time: HKT 12:45 p.m. - 2:00 p.m. (Registration starts on 12:15 p.m.)
Venue: Online with ZOOM
CPD: 10 points
FREE admission
Medium: Cantonese
Quota: 500
Enrolment Deadline: 22 March 2023 (Wed)