Jul 2026· Proceedings of the international conference of contemporary affairs in architecture and urbanism-ICCAUA· Vol 9, pp. 2610203· 0 citations
TL;DR
Convergence of Building Information Modeling (BIM) and Procedural Modeling (PM) within contemporary architecture is analyzed and contributions of integrating PM and BIM to efficiency and automation in Digital Twin production are investigated.
Abstract
Increasing architectural complexity necessitates the adoption of integrated methods. Convergence of Building Information Modeling (BIM) and Procedural Modeling (PM), within contemporary architecture is analyzed in this study. The limitations and potentials encountered during this convergence are discussed within an integrated framework. Digital Twin concept, as a data-driven cyber–physical simulation and optimization system, is examined as key point of the integration between BIM’s rich semantic data environment and the rule-based, dynamic operational logic of PM. Therefore, contributions of integrating PM and BIM to efficiency and automation in Digital Twin production are investigated. The requirements for aligning architectural design and construction workflows with contemporary demands and for integrating them with Industry 4.0 concepts and tools are discussed through conceptual analysis, cases, and relevant literature. Open data environments, user-friendly interfaces, standardization, training and legal frameworks are proposed to facilitate the integration and widespread adoption of BIM and PM in contemporary architecture.
A framework with three core components has been developed, which contains a BIM model component, which contains the geometric, semantic, and orientation data of building elements and provides a set of functions to support collaborative design review.
Subin Thomas, SeyedReza RazaviAlavi, A. Suliman et al.· 2026: Transforming Construct...· 0 citations
Lean Construction and digital tools such as Building Information Modeling (BIM), common data environments (CDEs), and mobile applications are widely adopted in construction projects but are often implemented through parallel and disconnected workflows. Consequently, Lean production control continues to rely heavily on manual observations, meetings, and spreadsheets, while increasing volumes of digital project data remain underutilized for operational decision-making. This disconnect limits project teams’ ability to detect waste early, stabilize production flow, and learn systematically from recurring issues. This study develops a conceptual Digital Lean Construction (DLC) framework using a design-oriented methodology comprising three stages: synthesis of gaps in existing BIM–Lean integration research, examination of previously validated digital workflows for BIM Quality Control (QC), Quantity Takeoff (QTO), and digital twin monitoring, and integration of these components into a unified closed-loop architecture. The resulting framework organizes project information through four conceptual layers and six implementation components that connect BIM/Industry Foundation Classes (IFC4 × 3) models, schedules, issue and quality records, quantity data, field inputs, sensor information, and GIS-based spatial context. The framework assumes IFC4 × 3 because it provides enhanced support for infrastructure assets and linear referencing required for transportation and civil infrastructure projects. Rule-based analytical logic is formalized for seven Lean key performance indicators (KPIs): Percent Plan Complete (PPC), takt deviations, constraint age, rework cycles, waste event counts, QC status, and delay risk. The framework demonstrates how validated and location-aware project information can be transformed into actionable Lean performance intelligence and incorporated into weekly planning, daily huddles, problem-solving, and standardization routines. Several underlying data-generation components have been validated in previous studies; however, the integrated DLC framework itself remains conceptual and requires project-level empirical evaluation. As a conceptual framework grounded in prior literature and previously validated digital workflows, this study does not include empirical field validation. Instead, it proposes an operational architecture intended to guide future implementation and evaluation in real construction projects. The study contributes an implementable architectural foundation for moving from fragmented, retrospective reporting toward proactive, data-supported, and continuously improving production control.
In the digital transformation of the architecture, engineering, and construction industry, Building Information Modeling (BIM) is increasingly understood as an information management framework rather than a geometric modeling tool. For reinforced concrete (RC) structures, major discontinuities persist between design, construction, as-built delivery, operation, and retrofit stages, limiting the long-term value of BIM implementations. This paper adopts a practice-informed framework development approach, combining direct field experience in structural assessment with analysis of ISO 19650, IFC 4.3.x (ISO 16739-1), IDS 1.0, and relevant literature. Field evidence from structural inspection practice in Vietnam demonstrates that three categories of information—concrete quality records, load history, and as-built information—are systematically unavailable at the time of assessment, forcing engineers to rely on costly destructive investigation. On that basis, a five-layer BIM-IFC information framework is proposed, whose main contribution is an Extended Technical Data Layer (ETDL) for structural reassessment, retrofit planning, durability management, structural health monitoring, and forensic investigation. The paper further clarifies how ETDL attributes can be represented within IFC-compatible workflows through extended properties, derived indicators, and linked lifecycle records. A prototype implementation using Autodesk Revit, IFC-based information exchange, and lifecycle information workflows is presented to demonstrate technical feasibility. The proposed framework offers a practical maturity pathway for Vietnamese RC practice and supports the transition from project-centric BIM models toward asset-oriented information management for sustainable lifecycle decision-making.
Nguyen-The Duong· 2026 11th International Conf...· 0 citations
Integrating Building Information Modeling (BIM) and Geographic Information Systems (GIS) remain challenging due to differences in data schemas, coordinate systems and semantic representation. This paper proposes and validates a VN-tailored BIM–GIS workflow for as-built infrastructure modeling that (i) standardizes data exchange using IFC and CityGML, (ii) harmonizes spatial data to the VN-2000 coordinate system, and (iii) automates semantic mapping via FME middleware. The workflow fuses multi-sensor acquisitions (UAV–LiDAR, terrestrial laser scanning — TLS, handheld SLAM, GNSS-RTK and GPR) to produce a high-fidelity digital twin of the University of Transport and Communications (UTC) campus (Hanoi). Geometric validation comprised two stages: point-cloud vs CAD (64.3% of points within ±0.10 m; 86.5% within ±0.30 m) and BIM vs point-cloud (91.4% of points within ±0.05 m), confirming centimeter-level alignment for most elements. The integrated model, deployed in ArcGIS Pro, enables asset tracking, space-use queries and risk analyses (e.g., flood susceptibility), demonstrating operational utility for facility and infrastructure management. The study contributes a practical, policy-relevant pipeline that preserves semantic and geometric fidelity for national-scale applications and outlines directions for automation, semantic interoperability and IoT-enabled digital twins.
This study explores the synergistic integration of Building Information Modeling (BIM) and Digital Twins (DT) as a transformative paradigm to enhance project efficiency throughout the lifecycle of sustainable construction projects. Employing a qualitative research design rooted in a systematic literature review and library research, this paper critically examines recent scholarly contributions, technical frameworks, and industry reports across primary academic databases. The findings demonstrate that while static BIM serves as a robust digital repository for design and structural data, dynamic Digital Twins extend these capabilities by integrating real-time IoT sensor data, enabling predictive maintenance, continuous performance monitoring, and adaptive energy management. The integration bridges critical information gaps between pre-construction planning and post-occupancy facility management, thereby significantly reducing resource waste, carbon footprint, and life-cycle operational costs. Furthermore, this research identifies key technological, organizational, and interoperability challenges hindering widespread implementation and proposes an integrative strategic framework to mitigate these barriers. Ultimately, this paper underscores that combining static structural modeling with dynamic cyber-physical data streams is essential for achieving truly sustainable, smart, and resilient built environments, offering actionable insights for AEC practitioners and policymakers aiming to advance sustainable digital transformation.
S. Suharwanto· Formosa Journal of Multidisc...· 0 citations
This study aims to address the strategic gap in Building Information Modeling (BIM) implementation by developing and empirically validating a novel, process-based framework (BEP-V) that embeds Value Engineering (VE) directly into the BIM Execution Plan.
The framework was empirically validated through a real-world case study of a mixed-use building in Taiz, Yemen. A dual-phase VE integration was applied: first, a Quality Model was structurally embedded during the early architectural programming phase to guide conceptual design. Second, BIM (Autodesk Revit) was used for automated data extraction, while the analytic hierarchy process (AHP) was applied for multi-criteria evaluation of the generated alternatives.
The empirical application validates that shifting VE to a mandated BEP workflow significantly enhances design performance. Early intervention via the Quality Model prevented low-value designs from the outset, while the subsequent AHP evaluation facilitated a data-driven facade optimization. This synergistic approach achieved a substantial 73.0% reduction in execution costs while maintaining acceptable thermal performance (U-value: 2.37 W/m²K) and high architectural quality.
The framework provides AEC practitioners with a reproducible, value-driven digital roadmap. It proactively mitigates design errors, eliminates unnecessary costs and enhances multidisciplinary coordination from project inception through detailed design.
This study transcends traditional tool-based BIM-VE integration by conceptualizing a strategic, process-based merger. It offers a paradigm shift in construction management, establishing the foundational digital governance required for future AI-driven and automated value optimization environments.
Unknown authors· Journal of Engineering, Desi...· 0 citations
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