Enhancing The Engineering Supervision Actions Quality: Quantitative Approach for The Evaluation of Implementation Based on Dual-code Activity Network

Abstract Intelligent supervision of construction progress and quality is crucial for the timely identification of engineering vulnerabilities and ensuring timely completion with quality assurance. To maintain real-time monitoring and control over project execution, we propose the idea of quantitative approach for evaluating the implementation from multiple dimensions to enhancing the engineering supervision actions quality. Based on the regulatory mechanism, we constructs a dual-code activity network by identifying the types and specific tasks of regulatory actions. Meanwhile, the paper establishes the evaluation system of action completion index from three dimensions. This mainly involves the time dimension, space dimension and efficiency dimension. We presents three methods of completion calculation according to the different types of action. Then we incorporate punitive variable weight to determine the contribution degree of different actions, and propose a quantitative approach of comprehensive evaluation for actions completion degree using associative path synthesis mechanism. We focus on a case study in railway flood season regulatory actions, verified the effectiveness and operability of the proposed method, which can avoid the problem of poor action execution effectiveness caused by existing progress management methods' lack of effective control over action process information. This quantitative approach can demonstrate significant advantages in improving action quality.