Evaluation method for engineering supervisory action quality based on dual-code activity network

Intelligent supervision of construction progress and quality is crucial for the timely identification of engineering vulnerabilities and ensuring timely completion with quality assurance. To enable real-time monitoring and control throughout project execution, we introduce a multi-dimensional quantitative approach for evaluating implementation outcomes, thereby enhancing the quality of engineering supervision activities. Based on the regulatory mechanism, we construct a dual-code activity network by identifying the types and specific tasks of regulatory actions. Meanwhile, the paper establishes an evaluation system for the action completion index from three dimensions. This mainly involves the time dimension, space dimension and efficiency dimension. We propose three completion calculation methods according to the different types of action. Then we incorporate punitive variable weights 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 conduct a case study on regulatory actions during the flood season of railway engineering, verifying 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.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2026-03-12
DOI
https://doi.org/10.1038/s41598-026-42529-5
Primary Topic
Manufacturing Process and Optimization
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Evaluation method for engineering supervisory action quality based on dual-code activity network

Hua Kai Wei, Deyi Xue, Jiangtao Xi, Xiaoxia Wang
Scientific Reports
Manufacturing Process and Optimization
article

Evaluation method for engineering supervisory action quality based on dual-code activity network

Hua Kai Wei, Deyi Xue, Jiangtao Xi, Xiaoxia Wang
article en

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 enable real-time monitoring and control throughout project execution, we introduce a multi-dimensional quantitative approach for evaluating implementation outcomes, thereby enhancing the quality of engineering supervision activities. Based on the regulatory mechanism, we construct a dual-code activity network by identifying the types and specific tasks of regulatory actions. Meanwhile, the paper establishes an evaluation system for the action completion index from three dimensions. This mainly involves the time dimension, space dimension and efficiency dimension. We propose three completion calculation methods according to the different types of action. Then we incorporate punitive variable weights 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 conduct a case study on regulatory actions during the flood season of railway engineering, verifying 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.

Scientific Reports
North University of China (CN), Shanxi University (CN), University of Wollongong (AU)
National Natural Science Foundation of China
Openalex Percentile: Top 27%
Manufacturing Process and Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.