Low-carbon building design requests an estimation of total embodied carbon as the environmental performance metric for comparison of different design options in early design stages. Due to a lack of consensus on the system boundaries in building life cycle assessment (LCA), the carbon estimation results obtained by the current methods are often disputable. In this regard, this paper proposes a method for estimating building embodied carbon based on digital twin technology and LCA. The proposed method is advantageous over others by providing (1) a cradle-to-cradle LCA and (2) an automated data communication between LCA and building information modelling (BIM) databases. Because data for the processes in the life cycle are collected via digital twin technology in a standard and consistent way, the obtained results will be considered credible. So far, a conceptual framework is developed based on a comprehensive literature review, which consists of three parts. In the first part, formulas for LCA are given. In the second part, a hybrid approach combining semantic web with a relational database for BIM and radio-frequency identification (RFID) integration is described. In the third part, how to design the LCA database and how to link LCA with BIM are described. The conceptual framework proposed is tested for its reasonableness by a small hypothetical case study.

Ports and cities are intrinsically linked. Port city, which serves as a link between the local and global economy, is an integration of both urban and port systems. Constrained by different regional structures, port cities have developed various formulations over time. Using a two-stage data envelopment analysis (DEA) approach, this paper proposes a new method for measuring the sustainable development of different port city systems. While the previous empirical studies often separate the port system and the urban system, this paper assesses the two systems in an integrated way. Moreover, this paper develops a systematic methodology for measurement of sustainability. Twenty world-leading container port cities are selected for this study using contemporary data. The DEA results display their relative differences in levels of sustainable development, which reveal the effectiveness of the prevailing policies in them. Eventually, recommendations are drawn for other port cities by referring to the best practices.

The construction industry is embracing the digital transformation to streamline the process from design to build. However, compared with design companies, precast concrete (PC) companies seem to be slow in the adoption of building information modeling (BIM). The paper thus intends to (1) understand the current BIM maturity levels in these companies via a survey among the PC companies; (2) develop a model for identifying critical success factors (CSFs) influencing BIM adoption from PC companies’ view; and (3) give recommendations to the PC companies as well as policymakers. From the survey responses of 53 respondents from the PC industry in various countries including Association of Southeast Asian Nations (ASEAN) countries, China, Korea, Taiwan, the Middle East, and Finland, the study successfully identified a total of eight CSFs, which are regarded as the main contributions this research makes to the body of knowledge. Based on these CSFs, recommendations are provided to assist PC companies to become industry innovators. Some additional contributions are (1) a new BIM adoption model, which is a mix of a BIM maturity model and a BIM adopters’ model and acted on by driving forces; (2) a new framework (called “PCBIM Hexagon” by the authors) consisting of driving forces from six areas: the government, ecosystem, company, team, process, and BIM software tool; and (3) a new approach for ranking the importance of the factors.

An automated guided vehicle-based flow production system is used for manufacturing prefabricated bathroom units. One unit can occupy a space of more than 10 m². Due to large time deviations in sequential processes, queues are formed and greater plant space is needed. Reducing work-in-progress helps to save plant space but renders manufacture less efficient. The research explores better workstation arrangements. An open queuing network (OQN) model was used to approximate the flow production system. Since the problem of workstation arrangement is a combinatorial optimisation problem, simulated annealing (SA) was applied to search for a good solution. The combination of an OQN model and SA provides a powerful tool to solve the facility layout problem for a stochastic flow production system. The experimental results show that the proposed approach has the potential to guide industrial layout design and practice.

In this article, scheduling problem of a space-constrained AGV-based prefabricated bathroom units (PBU) manufacturing system is addressed. Space becomes a key resource to this manufacturing system because a very large space is required to accommodate the settling units as well as the queues. Although line balancing helps to reduce the queues, the system is still prone to deadlock due to limited space. Hence, in order to prevent deadlock situations, the production start times of PBUs have to be controlled. A genetic algorithm is proposed with the objective to decide operation for each workstation and to choose a start time for each PBU. The project duration is minimised while satisfying precedence relations and resource availabilities. A rule-based simulation approach is used to estimate the fitness value of every GA chromosomes. At last, the experiment based on data from an industrial project shows that the proposed algorithm has the potential to guide the real practice.