A WCA-Based Evaluation Approach for Matching Analysis of the Construction Process

• Published in: Buildings (Basel) Vol. 14; no. 8; p. 2457
• Main Authors: Ye, Hongyu, Zhang, Hong, Sun, Minjie, Lv, Yihan, Yang, Wensheng, Gong, Yinan, Huang, Baolin, Cong, Meng
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-08-2024
• Subjects: Case studies; co-simulation; Concrete; Concrete structures; Construction costs; Construction industry; Critical path; Decision making; deconstruction and reconstruction; Efficiency; Environmental impact; Environmental law; Feasibility studies; Geospatial data; Indicators; Laws, regulations and rules; lightweight steel building; Literature reviews; Matching; Methods; Optimization; process match degree; Productivity; Questionnaires; R&D; Research & development; Research methodology; Schedules; Steel construction; Surveys; weighted criteria approach
• ISSN: 2075-5309; 2075-5309
• DOI: 10.3390/buildings14082457

Assessing construction process optimization and efficiency is crucial for the industry, yet quantitative methods for comparison are lacking. We propose the process matching degree (PMD) to quantitatively assess construction processes, enhancing efficiency and sustainability. Five primary indicators—regulations, environment, equipment, components, and organization—were identified, each of which were initially weighted equally using the weighted criteria approach (WCA). To refine the assessment, we conducted a questionnaire survey to adjust these weights based on expert feedback. Three sub-indicators were introduced for each primary indicator to increase granularity. The PMD’s operability was verified through two cases study involving BIM-simulated and real construction processes. The light-steel-structure building’s PMD values were 68 and 58 points, and the concrete structure’s PMD was 88.25, respectively, and the reasons for these differences were analyzed. This paper introduces PMD, its evaluation indicators, and calculation method, and verifies its feasibility through cases studies and expert questionnaire surveys, providing a comprehensive PMD research methodology.