The printed circuit boards (PCBs) industry is one of the fastest-growing industries in recent decades. The PCB manufacturing process is highly complicated and severely affected by social factors, which makes it very important to conduct integrated inspection, assuring and improving the production quality. In this article, we propose an artificial systems, computational experiments, and parallel execution-based integrated inspection method in cyber–physical–social systems (CPSS) to realize smart manufacturing. In this inspection system, rather than simply performing modeling, analysis, and control, we perform descriptive intelligence to construct production processes with limited multimodal information, perform predictive intelligence to conduct defect detection and defect prediction, and perform prescriptive intelligence to achieve defect diagnosis and defect management. In this way, our inspection system could offer a learning and training platform for workers to master professional inspection skills, provide an experimentation and evaluation platform for product defect monitoring and early warnings, and supply guidance about defect management and control to improve manufacturing processes. For technical implementation, we leverage a Transformer-based foundation model to achieve knowledge reasoning and human–computer interaction. As a result, we provide an innovative solution to cope with the challenges of quality inspection in current smart manufacturing, and expect its further applications in the PCB industry.