| Author: | Du, Qianru |
| Title: | Semi-automatic lifting and assembly platform (SLAP) for mic to mitigate safety risks |
| Advisors: | Shen, Qiping (BRE) Chi, Hung-lin (BRE) |
| Degree: | Ph.D. |
| Year: | 2026 |
| Department: | Department of Building and Real Estate |
| Pages: | xvii, 201 pages : color illustrations |
| Language: | English |
| Abstract: | With the increasing adoption of Modular Integrated Construction (MiC) in Hong Kong, the demand for safer, more efficient, and precise lifting operations becomes critical. Traditional crane-based lifting methods face significant safety risks, inefficiencies, and operational challenges, especially in the dense and complex urban environments of Hong Kong. These challenges highlight the urgent need for innovative solutions to improve the safety, efficiency, and accuracy of MiC lifting operations. In response, this study aims to develop a Semi-automatic Lifting and Assembly Platform (SLAP), a robotic system specifically designed to enhance module localization and positioning in MiC. The aim of this research is to improve operational efficiency, accuracy, and safety performance, addressing the limitations of existing lifting methods while advancing MiC practices. To achieve this aim, the study follows three primary objectives: (a) To identify and analyze the key safety risks in MiC lifting operations across different stages, and to determine specific, measurable gaps that can be addressed through technological solutions. (b) To design, develop, and validate an SLAP capable of mitigating the identified risks and improving the safety, efficiency, and accuracy of MiC lifting operations. (c) To assess the practical performance of the SLAP system using a systematic evaluation framework based on industry practices and measurable parameters for safety, efficiency, and productivity. The research begins by systematically identifying critical safety risks in MiC lifting using a mixed-method approach, including a detailed literature review, semi-structured interviews, and numerical analysis. This process uncovers the most pressing lifting safety risks and provides a clear understanding of the challenges present at various stages of the lifting process. These findings lay a strong foundation for the development of targeted technical solutions. Building on this analysis, the SLAP is proposed as an innovative solution to address these challenges. The platform integrates advanced control mechanisms for horizontal steering, levelling, and translation, supported by a robust sensing system that provides real-time feedback. These features enable the system to meet the safety, precision, and productivity requirements of MiC while ensuring compatibility with the operational demands of the construction industry. The SLAP's control logic and mechanisms incorporate detailed workflows and pose adjustment principles to optimize its functionality, which is detailed and illustrated in this study. A laboratory-scale prototype is developed to validate the feasibility of the proposed design and methodology. Experimental results demonstrate the SLAP's ability to execute complex lifting tasks with precision. These findings confirm the system's potential to address critical safety risks while significantly improving efficiency and accuracy in MiC lifting operations. Recognizing the absence of a standardized framework for evaluating MiC lifting platforms, this research develops a comprehensive performance evaluation framework. This framework is established through a rigorous review of academic literature, international standards, and local guidelines, identifying key performance parameters such as Quality, Safety, and Productivity. The SLAP prototype is tested using this framework, and the experimental results validate both the system's functionality and the applicability of the evaluation framework. While the SLAP system demonstrates robust performance, minor limitations, such as theoretical simplifications and human-induced errors during calibration, are identified. These limitations provide opportunities for future refinement and optimization of the system. The key findings of this study are summarized across four dimensions. First, the research systematically identified and addressed critical safety risks in MiC lifting operations. Nine major safety risks, such as poor communication and operator's nonproficiency, were identified and prioritized. Furthermore, three measurable gaps across six operational stages were identified, which could be effectively addressed through mechanical automation or semi-automation. Second, to bridge these gaps, the SLAP system was developed, integrating three core modules: the Horizontal Steering Control Module (HSCM), the Levelling Control Module (LCM), and the Translation Control Module (TCM). These modules automate key tasks such as module rotation, levelling, and precise positioning, significantly reducing reliance on manual operations. Third, a scaled prototype of the SLAP system was constructed and tested, demonstrating its ability to reduce platform tilt by over 80%, achieve millimeter-level positioning accuracy (errors < 3mm), and control roll and pitch angles within ±1°. Additionally, the SLAP system reduced module positioning time to 5 minutes per move (including damping and data recording), compared to the significantly longer durations required by manual methods. Fourth, a comprehensive evaluation framework was developed, confirming the SLAP system's performance in safety, accuracy, and efficiency, and showcasing its potential to address critical safety risks and transform MiC lifting practices. This research makes original contributions to improving the safety and performance of MiC lifting operations from both theoretical and practical perspectives. Theoretically, it systematically identifies and prioritizes critical safety risks associated with MiC lifting, providing a structured framework for understanding and addressing these challenges. It also introduces the SLAP system as a novel methodology, integrating advanced automation and precision control to tackle these risks and enhance operational efficiency. The research bridges the gap between theory and real-world application through a comprehensive validation framework, demonstrating the system's feasibility and offering actionable insights for refinement under on-site conditions. Additionally, it advances the MiC lifting knowledge system by developing new methodologies, performance metrics, and validation techniques, laying a foundation for future research and innovation in automated lifting technologies. From a practical perspective, the SLAP system represents an innovative solution that addresses critical safety risks by automating hazardous tasks, reducing workers' exposure to unsafe environments, and mitigating risks such as human error, fatigue, and poor visibility. The system also improves operational efficiency, while significantly reducing physical labor demands. These contributions collectively pave the way for safer, more efficient, and more reliable MiC lifting processes and establish a foundation for future advancements in full automation and robotics within the construction industry. |
| Rights: | All rights reserved |
| Access: | open access |
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