Dynamic human systems risk prognosis and control of lifting operations during prefabricated building construction
Zhe Sun, Zhufu Zhu, Ruoxin Xiong, Pingbo Tang, Zhansheng Liu
Abstract
Prefabricated building construction (PBC) involves tedious lifting operations that require multiple cranes to work simultaneously in dynamic workspaces. Such operations involve frequent interactions among human, cyber, and physical environments, creating challenges for risk prognosis and control in dynamic contexts. Unfortunately, human errors pose challenges for achieving resilient lifting operation control. A dynamic human systems risk prognosis and control (DHS RP & C) approach is thus necessary for 1) capturing human errors and 2) controlling risks of human anomalies proactively. This study critically reviews opportunities and challenges for establishing the proposed approach. Challenges exist as 1) how to collect human/team behavior data during lifting operations, 2) how to analyze these data for comprehending the impacts of human factors, and 3) how to respond to operational contingencies with risk control measures. In the end, the authors established a research roadmap for guiding future research activities toward automated lifting operations in PBC.