Mr. Jimmy K.K. CHAN is currently a Senior Building Services Engineer in the Electrical and Mechanical Services Department of the HKSAR Government. He has over 25 years of experience in Lift and Escalator engineering field. He has been active in the application of machine learning on predictive maintenance for lift installations in the Department. Mr. CHAN is a Chartered Engineer with the Engineering Council (UK), a Member of the Institution of Mechanical Engineers and a Corporate Member of Hong Kong Institution of Engineers.
Mr. Calvin K.F. LEUNG is currently an experienced Building Services Engineer in the Electrical and Mechanical Services Department of the HKSAR Government. He has been active in various digital transformation projects in the Department, specifically on the safety enhancement and innovation technologies of lift and escalator installations. Mr. LEUNG is a Chartered Engineer with the Engineering Council (UK), a Member of the Chartered Institution of Building Services Engineers and a Corporate Member of Hong Kong Institution of Engineers.
Mr. Wayne T.H. WONG is currently a Project Officer in EMSD. He has over 25 years of experience in IT industry for Application and System Development. He has been actively participated in the promotion of IT application to business and supporting of innovative Startup companies. Mr. WONG is a Professional Member of the BCS.
Mr. Scotty C.H. KWOK is the founder and CTO of Sebit Company Limited, a technology startup based in Hong Kong. He has over 20 years of software development experience and is specialized in artificial intelligence, machine learning and computer vision. He and his team has been active in developing artificial intelligence and machine learning solutions for Lift and Escalator. Mr. KWOK holds a Master of Science degree in computer science and is a frequent speaker in tech conferences.
Mr. Henry W. Y. WONG is currently a software engineer at Sebit Company Limited. He has three years of research and software development experience at university. He has been active in various projects of artificial intelligence and machine learning solutions for Lift and Escalator, and time series data analysis in physical science. Mr. Wong holds a Bachelor of Science degree in Physics.
This paper presents a proof-of-concept trial of a health monitoring platform for Condition-based and Predictive Maintenance of lift installations based on big data analytics. Different types of non-intrusive sensors have been implemented for measuring temperature, strain, acceleration and displacement of lifts such as the traction motor brake arms and lift car vibration. A novel design of sensing and data analytic approach that capable of early identification of faults, such as brake malfunction, lift car shaking, door malfunction and traction motor malfunction have gone through proof of concept testing. A health monitoring platform is established to comprehensively keep tracking of real time operating conditions of lift installations. Predictive models are also developed to predict the remaining useful life (RUL) for the critical components.
The health monitoring platform has been deployed in five lifts during the initial trial. The processing units collect and transmit the measured data to a remote cloud-based server where algorithms for defective components identification and predictive data analytics can be implemented. Coupled with artificial intelligence, the platform can help improve preventive maintenance and relieve the burden of servicing personnel for lift installations. This paper will share the experience, effectiveness and challenges when developing predictive maintenance strategy for lift installations.
Condition-based and predictive maintenance strategy for lift installations using big data analytics.
Jimmy K.K. Chan, Calvin K.F. Leung, Wayne T.H. Wong, Scotty C.H. Kwok.
Electrical and Mechanical Services Department Government of the HKSAR of the People’s Republic of China, China.