State-of-the-Art Review on the Applicability of AI Methods to Automated Construction Manufacturing

Abstract

Productivity in the U.S. construction industry has stagnated over the past 50 years, whereas manufacturing industries have about doubled productivity levels. Adoption of smart manufacturing with construction has challenges to achieving efficiency in a factory environment. Construction projects are one-off designs with little replication in the configuration of components. The ability to reconfigure factory production and network optimization performance help smart manufacturing systems. Artificial intelligence (AI) is well suited to this problem. This paper provides an in-depth review of AI methods and how the technology may be applied to automated construction manufacturing systems. This starts with a state-of-the-practice review of AI applications within construction manufacturing. This is followed by an identification of the AI needs of construction manufacturing systems. Lastly, the paper reviews the state-of-the-art of artificial neural networks (ANNs) (e.g. deep learning and transfer learning) from the domains of manufacturing and industrial engineering, and discusses the potential for application to construction manufacturing. The objective of the paper is to help identify the direction for future research and development in this field.