This research reviews recent advances in the domain of Automated Rule Checking (ARC) and argues that current systems are predominantly designed to validate models in post-design stages, useful for applications such as e-permitting. However, such a design-check-separated paradigm imposes a burden on designers as they need to iteratively fix the fail-to-pass issues. Accordingly, the study reviews the best-practices of IFC-based ARC systems and proposes a framework for ARC system development, aiming to achieve proactive bottom-up solutions building upon the requirements and resources of end-users. To present and evaluate its capabilities, the framework is implemented in a real-life case study. The case study presents all the necessary steps that should be taken for the development of an ARC solution from rule selection and analysis, to implementation and feedback. It is explained how a rule checking problem can be broken down into separate modules implemented in an iterative approach. Results show that the proposed framework is feasible for successful implementation of ARC systems and highlight that a stable data standard and modeling guideline is needed to achieve proactive ARC solutions. The study also discusses that there are some critical limitations in using IFC which need to be addressed in future studies.
PurposeThis study provides an integrated risk-based cost and time estimation approach for deep excavation projects. The purpose is to identify the best practices in recent advances of excavation risk analysis (RA) and integrate them with traditional cost and time estimation methods.Design/methodology/approachThe implemented best practices in this research are as follows: (1) fault-tree analysis (FTA) for risk identification (RI); (2) Bayesian belief networks (BBNs), fuzzy comprehensive analysis and Monte Carlo simulation (MCS) for risk analysis; and (3) sensitivity analysis and root-cause analysis (RCA) for risk response planning (RRP). The proposed approach is applied in an actual deep excavation project in Tehran, Iran.FindingsThe results show that the framework proposes a practical approach for integrating the risk management (RM) best practices in the domain of excavation projects with traditional cost and time estimation approaches. The proposed approach can consider the interrelationships between risk events and identify their root causes. Further, the approach engages different stakeholders in the process of RM, which is beneficial for determining risk owners and responsibilities.Originality/valueThis research contributes to the project management body of knowledge by integrating recent RM best practices in deep excavation projects for probabilistic estimation of project time and cost.
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