Enhancing the Production Performance of Prefabricated Buildings through the Integrated Optimization of Precast Component Layout and Worker Allocation

The layout of precast components (PCs) made of concrete materials on movable mold tables not only affects the number of movable mold tables but also impacts worker allocation during production. However, previous studies, to our best knowledge, have not yet considered the optimal precast component (PC) layout when optimizing worker allocation, potentially leading to more time, costs, and carbon dioxide (CO2) emissions during production. As such, this study proposes a method for optimizing the PC layout on movable mold tables and worker allocation during production from the perspective of multiobjective trade-offs. This method has the following characteristics: (1) the Pareto optimality (PO) principle is adopted to address the trade-offs between multiple objectives, while discrete event simulation (DES) technology is used to simulate the production process of PCs; and (2) optimizing the PC layout serves as the basis for optimizing the worker allocation. A real production case is used for demonstrating and validating this method. The results show that: (1) the method searches for two Pareto-optimal PC layout schemes on movable mold tables and reduces the sum of processing-time variance in an assembly line by 44.15% without changing the number of movable mold tables or by 89.18% with adding six movable mold tables; and (2) based on these two PC layout schemes, this method further reduces costs and CO2 emissions by 6.97% and 14.56%, respectively, during production. Thus, the method represents a pioneering and effective achievement in the integrated multiobjective trade-off optimization of PC layout and worker allocation, thereby enriching the methodological system of industrial construction and lean construction. In addition, the method, findings, and recommendations in this study facilitate factory managers’ high-performance decision-making in addressing the trade-offs among time shortening, cost reduction, and CO2 emission mitigation during PC production.