Whilst the benefits of applying an industrialized building system (IBS) have been well recognized globally in the construction industry, the application of IBS is particularly limited in developing countries such as China, and quality is considered one of the key issues affecting its application. This paper identifies a number of the key quality factors which present barriers to the promotion of IBS within the context of the Chinese construction industry. These include key factors such as "Inaccurate design of the connecting points between core components", "Lack of design norms and standards for IBS components", "Lack of quality criteria for IBS components", "Lack of production norms and standards for IBS components", "Lack of quality management system in production process", and "Lack of technical guidelines for the construction of IBS projects". The data used for analysis are derived from a comprehensive practical survey. The validity of the data is examined by using a statistical method. The findings from the study provide valuable references for formulating effective measures to mitigate the negative effects of these quality factors on IBS application in China, thereby ensuring that practice of the IBS system can be further developed within the country.
The precast concrete (PC) preform automatic production line basically has no supporting enterprise resource planning (ERP) system and can only communicate information in the traditional way, which reduces work efficiency. ERP is an application that automates the business process and provides insights on marketing strategy. Therefore, the information research of the intelligent PC preform automatic production line based on a genetic algorithm is proposed. First, the core architecture of intelligent PC preform automatic production is proposed, then the core business process of PC factory is described, and the preform ERP core module is designed from multiple perspectives. According to the characteristics of genetic algorithm, the quantitative factor and proportional factor of the intelligent PC preform automatic production line transportation speed are calculated, the time-division control model of intelligent PC preform automatic production line transportation speed is established, and the calculation process of the quantitative factor and proportional factor is substituted to control the transportation speed of production line by time division. The experimental results show that after testing the control effect of the conveying speed of the production line, the convergence speed of the motor speed waveform, and the stability of the model, the information conveying speed of the intelligent PC preform automatic production line can be controlled by time, according to the instructions, and it has faster corresponding speed, higher stability, and smaller error in the process of controlling the production line.
In order to obtain the best scheme of safety production and operation decision-making of a smart factory and improve the rapid response ability of product information of a smart factory, the safety production detection algorithm of a smart factory is designed by using programmable computer (PC) control technology. The main interface, login interface, function interface, and navigation interface are designed, respectively, to realize the front-end design of the smart factory safety production detection platform. Based on PC control technology, the hardware equipment of perception layer, network layer, and application layer are installed, and on this basis, the database of the smart factory safety production detection platform is established. Once the operation data information is collected and detected, it is stored to the equipment fault experience knowledge base, and the fault diagnosis method of the minimum cut set of the fault tree is used to implement the on-site equipment diagnosis of the underlying Internet of Things of the smart factory, and finally the information sharing function of safety production detection through the information transmission of the safety production links of each smart factory is realized. Experiments show that the throughput data of the designed algorithm run stably, improve the control accuracy of safety production, and effectively improve the work efficiency.
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