Professor Ray Zhong, Assistant Professor of Department of Industrial and Manufacturing Systems Engineering
For and beyond the manufacturing, construction, and textile and apparel industries, the use of big data is set to usher in revolutionary changes.
And Ray Zhong, an Assistant Professor in the Department of Industrial and Manufacturing Systems Engineering, has been at the forefront of accelerating that process.
A recent project for him and his 22-member research team – at Ash Street, Tai Kok Tsui, led by Chun Wo Construction and Engineering Company Limited (Chun Wo for short), is a private residential development project in Hong Kong using the innovative Modular Integrated Construction (MiC) building method. Through cutting-edge technologies, Professor Zhong’s team developed a smart platform to facilitate fitting out work for the construction supply chain management.
The Internet of Things-enabled BIM (Building Information Modelling) platform tracks building materials from procurement to last-mile deliveries via a web and mobile based system, analyses captured data for supporting decision-making, and coordinates with decision-makers to ensure efficient distribution of materials, including windows, fragile or metal components, pipes, etc., from storage to the site, floor, and room.
“We provided customised design using feature-based machine learning for BIM; an AI-based building material scheduling; Digital Twin-enabled logistics visualisation using Big Data Analytics,” Professor Zhong explained.
Work on Government projects
His team has already provided technological support for the Hong Kong Housing Authority’s public housing projects. It has also developed a smart system for watering grass at the Hong Kong Jockey Club’s headquarters in Happy Valley, apart from upgrading a wastewater treatment plant for the Drainage Services Department.
Input from his team is also needed for the Government’s Northern Metropolis project, to provide logistical support at a system level for infrastructural development, such as the construction of tunnels, wastewater pumps and so on.
One preoccupation of his team is always the protection of workers’ safety. As anyone would agree, even one fatal accident is still too many. Unfortunately, Hong Kong saw 17 construction-related deaths in 2022. Government statistics show that the construction sector is the most hazardous of all industries in terms of accident and fatality rates, due to its risky job nature and site environment. On average, there were 29.1 construction accidents per 1,000 workers in 2022, more than twice the economy-wide rate of 13.5.
His multicultural team will continue to focus on construction work, especially in light of the Government’s plan to build 410,000 public housing units in the coming decade. The ambitious construction goal can benefit from research input on ways to enhance safety protection, efficiency and quality. “Our team is focusing on using the Internet of Things (IoT), digital twin, and BIM to have real time checks of humans, cranes, trucks etc. to avoid unnecessary accidents,” said Professor Zhong. “We try to use the data to help supervisors make advanced decisions, or simulate possible risks at construction sites to help improve safety for frontline workers.”
Professor Zhong and his research team participated in BIM model development for Hong Kong Jockey Club Project
Widespread changes for the construction sector and beyond
Increasingly, a wide spectrum of robots has been deployed at construction sites in place of manual labour, doing work from spray painting, demolition, grouting to plastering. Professor Zhong believes in the coming decades, robots will take on even more prominent roles, eventually replacing human labour in the construction process, like in the automobile industry. “Even trucks transporting materials around a site could be replaced,” Professor Zhong said.
The COVID-19 pandemic highlighted the importance of remote system control, as all logistics, and supply chains were severely disrupted. Territorial borders were closed, dealing a blow to the transportations of goods. With the use of cutting-edge technologies, Professor Zhong’s research team helped companies navigate their product delivery efficiently and effectively amid various constraints.
“We helped with the scheduling of delivery by train, coordinated the loading and unloading of goods, maximised the amount of cargo carried, etc.,” he explained. Looking to the future, he added, as a result of frontier research, logistics will become an easy process where simply by the touch of a key, a trader can find out the optimal way to deliver goods to a destination, with no hassle.
Building Material Scheduling Service (BMSS) for scheduling agents to make decisions (e.g. plans and schedules) for fit-out constructions with the adoption of Deep Reinforcement Learning (DRL)
Compliance with ESG
Another area of his work is to help both public and private sectors comply with ESG (environment, social and governance) standards.
Based on real-time data, systems devised by his team could help companies measure their performance. Nowadays, listed companies are required by the Hong Kong Stock Exchange (HKEX) to report on their compliance with ESG standards.
“The government is always concerned about public housing’s ESG-related issues,” he said. “For example, each construction site is expected to submit a report about not just safety alone, but also what they have done in relation to ESG.”
He has held talks with the HKEX and the textile and apparel industry on the ESG standards to be measured, or creating an ESG index to help companies evaluate their overall performance. “The technology we have used for the construction industry like collecting real time data can be applied to other industries. We will try to create the first indexing system for the region.”
His team has already received HK$10 million funding support from the Innovation and Technology Fund for assisting the textile sector to generate ESG reports, by capturing key information such as water usage.
Handling a vast amount of data comes with challenges. For example, how to make good use of diverse materials of heterogeneous format and sources? There is also the issue of enhancing the user-friendliness of various systems.
The Future world of construction
In the hugely complex setting of a construction site, it takes much advanced research to transform the work process, or elevate it to the level of full automation. Artificial intelligence is indispensable for creating a smart environment. “We need new models, new algorithms to deal with new research issues, such as handling supply chain risks,” said Professor Zhong. “We have created a technology to check the facilities at construction sites, but for the checking of equipment, that is very challenging. For example, there are different types of trucks, forklifts and cranes. We will need to resort to computer vision and AI to help different facilities, equipment interact with each other.”
“A smart site needs to integrate different components, starting with capturing, integrating, visualising data, then using them for decision making and co-ordinating with different parties. Engineers may need to write new algorithms for more efficient data processing.”
Professor Zhong presented data-driven smart prefabrication construction in Hong Kong at a workshop
Research and studies on big data
A native of Jiangxi province, China, Professor Zhong learned about the Internet of Things when he was a master’s student in the mainland. In the 2010s, his focus on data mining during his doctoral studies exposed him to the rising trend of data analytics, paving the way for his later research.
By now, he has collaborated with most professors in relevant fields both at HKU and other universities. “They are all chair professors/full professors who are happy to support younger researchers like me,” he said with gratitude.
Similarly, he is grateful to his PhD supervisor at HKU who encouraged him to produce research articles for journal publications. Later, also upon the supervisor’s advice, he left for a teaching position at the University of Auckland in New Zealand to broaden his own experience.
Since returning to HKU in 2019, he has immersed himself in a productive, satisfying research journey. Currently he serves as associate or area editors for several well-known international journals, including Computers & Industrial Engineering: An International Journal; International Journal of Computer-Integrated Manufacturing, etc.
The rise of big data opened new doors for him, resulting in the creation of advanced models and systems for various purposes. “We can build different digital twin models or customised designs for different construction sites or industrial scenarios,” said Professor Zhong, whose paper entitled “Big Data Analytics for Physical Internet-based Intelligent Manufacturing Shop Floor” won the IJPR Best Paper in 2018. “We can also have customised designs using the Cyber-physical Systems, which are collections of closely integrated physical and computer components that can together operate a process safely and efficiently.”
Comprising PhD students, post-docs, full-time and part-time research assistants from countries including China, India, Russia, and Pakistan, his team members have made indispensable contributions to various projects. “They are very talented,” remarked Professor Zhong. “I was lucky and am also lucky to have so many wonderful students here.”
To join his research team, each potential member is required to have published at least two research papers before entering into HKU. “I set a very high bar for joining,” he said.
Having majored in mathematics and computer science at a teacher-training university in China, he enjoys both teaching and research. The fresh and young minds of undergraduates are a source of inspiration to him.
“They are more creative sometimes. Maybe their ideas are not reasonable or do not follow logic, but they are stimulating. I like interacting with them.”
Professor Zhong and his research team members