½²×ùÖ÷Ì⣺Smart work packaging system in industrialized construction

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There are challenges in dynamic work package generation, adaptive work package sizing, and decentralized work package execution for the fragmented, complex, and untrustworthy collaboration of industrialized construction. This research seminar will introduce the smart work packaging (SWP) methodology to enable more efficient and effective collaborative working. The theoretical novelty is the SWP model for task planning. In SWP, as the duration and content of each planned task vary when projects progress, a task can be represented by an adaptive graph consisting of semantics formed by entities and relations. SWP can generate semantics-enriched tasks using attention-based graph neural networks adapting to dynamic changes in task contents. Furthermore, SWP can compute the optimal work package size by grouping semantic-enriched tasks for minimum cost within a makespan, adapting to task duration uncertainty based on stochastic optimization theory. SWP enables adaptive task generation and stochastic-based work package sizing in a local planner system. Studying blockchain will extend the SWP model from a local planner system to distributed supervision for accountable collaboration. Blockchain can expand the SWP model to the robot and stakeholder network using decentralized applications, e.g., decentralized scheduling, personalized monitoring, and digital supervision. The smart work packaging system demonstrates the potential for next-generation agile project management in industrialized construction.

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LI Xiao is an Assistant Professor at the Department of Civil Engineering at the University of Hong Kong (HKU). Xiao¡¯s research mainly contributes to smart and industrialized construction, which includes assembly systems, production systems, and smart work packaging methodology for collaborative planning and control in construction. He has authored 50+ papers in peer-reviewed academic journals with more than 5300 citations. He is the Top 1% Scholars by Clarivate Analytics and World¡¯s Top 2% Scientists by Stanford University, a fellow of the SYLFF Association, a National Registered Construction Engineer (Class 1), a member of the American Society of Civil Engineers and CIB, and guest editors of several leading journals in construction engineering and management. He held several international academic awards, e.g., the 49TH Geneva Inventions Gold Medal, CIC Innovation Award, SYLFF Research Grant Award/Research Abroad Award, CIB Sebesty¨¦n Future Leaders Award, ASCE Best Paper Award, CRIOCM Best Paper Award, and CIOB (HK) Outstanding Paper Award. He also led various research projects in the following fields: Blockchain and distributed collaboration; Work package-based scheduling and optimization; Human-robot collaboration-based production robotics system; Intelligent carbon monitoring system; Assembly robot in modular construction.

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