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Dynamic and Proactive Risk-Based Methodology for Managing Excessive Geometric Variability Issues in Modular Construction Projects Using Bayesian Theory

机译:基于贝叶斯理论的动态和主动风险管理方法,用于管理模块化建筑项目中过多的几何变异性问题

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Managing excessive geometric variability risks (i.e., out-of-tolerance and out-of-alignment issues) represents a major challenge in modular construction projects, owing to lack of accurate data on modularization process capabilities for fabrication, transportation, and erection at the early design phase. Unrealistic and insufficient modularization process capability data typically convey a misleading risk profile and result in suboptimal mitigation solutions, which can in turn lead to cost overruns, schedule delays, quality issues, and owner dissatisfaction. Current modularization practices and previously developed risk management frameworks apply static risk assessment and management techniques, which do not enable updating of the generic information and initial assessment of the risk profile, when more realistic data become available. To address this persistent challenge in modular construction projects, this paper aims to introduce a systematic methodology that employs Bayesian inference theory for the dynamic assessment and proactive management of excessive geometric variability issues. The developed methodology includes a practical process for continual (1) updating of initial estimates of the performance of tolerance-based mitigation strategies based on real-time data, (2) reassessment of the risk profile, and (3) refinement of risk response decisions. The results of the case study described subsequently in this paper demonstrate how key project stakeholders and modular construction managers (e.g., designers, fabricators, and contractors) can use this methodology to efficiently reduce uncertainty in tolerance-related risk estimates and proactively manage impacts to improve modularization performance and maximize its benefits. (C) 2019 American Society of Civil Engineers.
机译:由于在早期阶段缺乏用于制造,运输和安装的模块化过程能力的准确数据,因此管理过多的几何可变性风险(即,公差和对齐问题)是模块化建筑项目中的主要挑战。设计阶段。不现实且模块化过程能力不足的数据通常会传达误导性的风险状况,并导致解决方案不理想,进而可能导致成本超支,进度延误,质量问题和所有者不满。当前的模块化实践和先前开发的风险管理框架采用静态风险评估和管理技术,当可获得更真实的数据时,这些技术无法更新一般信息和对风险概况进行初始评估。为了解决模块化建筑项目中的持续挑战,本文旨在介绍一种系统方法,该方法采用贝叶斯推理理论对过多的几何可变性问题进行动态评估和主动管理。所开发的方法包括一个连续不断的实践过程(1)基于实时数据更新基于公差的缓解策略的性能的初始估计值;(2)重新评估风险概况;以及(3)完善风险响应决策。本文随后描述的案例研究结果表明,关键项目利益相关者和模块化施工经理(例如,设计师,制造商和承包商)如何使用此方法有效地减少与公差相关的风险估计中的不确定性,并主动管理影响以改善模块化性能并最大程度地发挥其优势。 (C)2019美国土木工程师学会。

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