Scheduling for prefabricated prefinished volumetric construction with resource eligibility constraints

• Main Author: Tang, Xiuke
• Other Authors: Wu Kan
• Format: Thesis-Master by Coursework
• Language: English
• Published: Nanyang Technological University 2020
• Subjects: Engineering::Systems engineering
• Online Access: https://hdl.handle.net/10356/142895
• Institution: Nanyang Technological University

Prefabricated Prefinished Volumetric Construction (PPVC) is a kind of emerging energy-saving and environmentally friendly construction method that has gained in-creasing popularity in recent years. With the ability of widely applied substantial economic benefits, it consequently promoted by Singapore national policies. Since the manufacturing technologies of PPVC are approaching maturity, the increasing automation and standardization of the production flow are introduced to PPVC factories, able to adopt the concept of manufacturing. Notably, the uncertainty in the working schedule could be reduced significantly in the production process. Currently, the construction industry relies heavily on manual operation. Even if PPVC involves more automation robotics, the management of the shop floor is inef-ficiently controlled by manual work. Thus, it is urgent to improve via modern infor-mation technologies, especially in scheduling. For the manufacturing procedures, some are operated in the fixed sequence, and others are non-fixed sequence. For fixed sequence processes, the scheduling can be regarded as the flow shop schedul-ing problem (FSSP), and non-fixed sequence processes are regarded as open shop scheduling problem (OSSP). Therefore, this dissertation proposes a mathematical model that combines the OSSP and FSSP scheduling problems and simulates the actual situation in PPVC factory. This dissertation utilized genetic algorithms (GA), particle swarm optimization algorithms (PSO) and proposed a PSO based on GA algorithm to solve shop floor scheduling problems in PPVC factories. The reliability of the model and algorithm is validated through applications and comparisons with manual scheduling. Furthermore, the scheduling model in this dissertation can work as the foundation for the establishment of smart factories and MES systems in the future and provide a valid reference.