Department of Industrial Engineering and Decision Analytics
The field of Industrial Engineering (IE) originated with the Industrial Revolution due to the complexities of mass production. Industrial engineering originally dealt with the optimization of complex production systems with the aim of improving quality and productivity. The ultimate goal was to design factories capable of simultaneously offering product variety, high quality and low costs. Such factories first became a reality in the automobile industry before spreading more broadly.
With the digital revolution came the mass production of semiconductors and its derived technologies including computers, cell phones and the Internet. In the 1980s and 1990s, a great deal of effort in IE was directed to semiconductor manufacturing, to logistics and to supply chains. With the Internet came the information age, where data became abundant and computer power cheap. In the early part of this century, we saw IE direct its efforts to healthcare, call centers, and to the design and pricing of product and services including financial engineering, dynamic pricing and revenue optimization. We are now seeing the emergence of new technologies, such as blockchain and machine learning, and a host of new problems in the knowledge economy where growth is dependent on the creative use of information and technology rather than on physical means of production. It is in this new economy that our graduates will launch their careers, and it is our mission to train them so they can successfully do so.
Research in the Department falls along three themes: Logistics and Supply Chain Management, Product Design and Manufacturing, and Decision Analytics. Our work in Logistics and Supply Chain Management emphasizes on integrating the logistics and supply chain needs of Hong Kong with its vicinity for further enhancing the cooperation with the provinces and hence adding value to the economic development. In the area of Product Design and Manufacturing, the research focuses on bringing competitive advantages to industry by leveraging on the technological advances in the financial, communication and logistics sectors. Decision Analytics encompasses work in operations research, statistics, machine-learning with applications to domain specific areas that include financial engineering, fintech, dynamic pricing, revenue optimization, risk management, and health care analytics.
The Department has a host of state-of-the-art facilities to support its teaching and research. Government- and industry-funded projects are ongoing. Collaborations with renowned universities and professional institutions have been established. The Department has also built partnerships with major service industry sectors, in particular with the financial and logistics industries.
IT solutions are emphasized in teaching, research and industry collaborations, together with the impact of the globalization of the world’s economy.