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All Journal Civil Engineering Journal Management Science Research Journal
Saqr, Abdullah
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Civil Engineering, Building, Construction & Architecture Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Social Sciences

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BIM-Based Integrated Model for Project Cost Estimation: A Case Study for Concrete Elements Elsheikh, Asser; Saqr, Abdullah; Motawa, Ibrahim
Civil Engineering Journal Vol. 11 No. 11 (2025): November
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2025-011-11-021

Abstract

Construction projects often struggle to align design models, cost estimates, and scheduling processes. To address this challenge, this study presents an integrated 5D BIM model that automates cost and schedule estimation by linking 3D BIM components to a structured database of historical productivity and activity data. A unique coding system connects each BIM object to its corresponding construction tasks, enabling automatic generation of resource-loaded schedules with associated durations, costs, and crews based on the selected construction method. The workflow integrates Autodesk Revit, Navisworks, a relational (SQL) database, and Primavera P6 to achieve seamless interoperability across design, estimating, and scheduling tools. The model is validated through a case study of a six-story reinforced concrete building. Findings show that the approach significantly improves estimation, accuracy, and efficiency. Predicted costs closely match actual values, thereby reducing dispersion among estimates. The automated process minimizes manual data handling while keeping cost and schedule outputs synchronized. Novel contributions include the incorporation of detailed historical productivity data, construction method alternatives, and structured cost/activity records into a unified framework, representing a methodological advance in 5D BIM that bridges the design, estimating, and scheduling domains for more reliable and automated project planning.
The Impact of AI in BIM-to-Digital Twins on Facility Management Handover: Bridging the Gap between Construction and Operations through AI-Driven Integration. Saqr, Abdullah
Management Science Research Journal Vol. 5 No. 1 (2026): FEBRUARY 2026
Publisher : PT Larva Wijaya Penerbit

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56548/msr.v5i1.197

Abstract

The present paper will consider how Artificial Intelligence (AI) will help in the shift by Building Information Modeling (BIM) to Digital Twins (DTs), specifically in relation to facility management handover. It deals with the main industrial concerns in the fragmentation of data, lack of interoperability, and ineffective regulatory compliance process by using AI-based solutions to enhance data validation, predictive analytics, and real-time synchronization. The data collection was conducted with the help of a qualitative method based on an interpretivist worldview and grounded theory approach, which allowed collecting data through semi-structured interviews with BIM professionals. The findings prove that AI could be effective to increase the accuracy, effectiveness, and quality of BIM-DT handover procedures, which, in its turn, leads to more efficient operations, proactive maintenance of facilities, and sustainable facility management.
Co-Authors Elsheikh, Asser Motawa, Ibrahim