Automated Identification & Analysis of Design and Construction Processes through BIM (Building Information Modeling)

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• 批准号: RGPIN-2017-06697
• 负责人: NIKBAKHT, MAZDAK
• 金额: $ 1.6万
• 依托单位: Concordia University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=712343
• 关键词: Automated; Identification; Analysis; Design; Construction

The identification, modeling, and evaluation of design Building Information Modeling (BIM) supports project teams through such processes and therefore can be effectively used as an Enterprise Resource Planning (ERP) tool for AECO industry. BIM can integrate distributed information and derive new information. However, providing actionable information requires identification and evaluation of the end-to-end processes, as they happen in practice (opposed to what has been planned). Process mining, a branch of data science, detects end-to-end business processes via pattern recognition in enterprise operation data. For this purpose, data from ERP systems is processed to form event-logs (inputs of process mining engines). In spite of substantial contributions to enhancing processes in a wide range of industries; process mining has not had any major applications, in design construction event-logs; (2) Identifying, evaluating and enhancing design (3) Providing decision support in form of practice-oriented KPIs and enhanced simulation models. Seven HQP will be trained with dual specialties (design and data science skills) who will contribute to achieving these objectives. This program will extend the existing open standards of event-logs to support events, attributes and relationships in design as well as the behavior of associated actors. Finally, the program will offer a set of practice-oriented KPIs and a method to enhance construction process simulation. This research program will be a major step forward in assessment of processes and actors in AECO. It will yield deliverables at three major levels: (1) data standard and data mining tools (2) methods and algorithms (3) models global and Canadian AECO industry; and public sector bodies.

建筑信息模型（BIM）通过这些过程支持项目团队，因此可以有效地用作AECO行业的企业资源规划（ERP）工具。BIM可以整合分布式信息并导出新信息。然而，提供可操作的信息需要识别和评估端到端流程，因为它们在实践中发生（与计划相反）。 流程挖掘是数据科学的一个分支，它通过模式识别的方法从企业运营数据中发现端到端的业务流程。为此，来自ERP系统的数据被处理以形成事件日志（流程挖掘引擎的输入）。尽管流程挖掘在许多行业中对流程的改进做出了重大贡献，但在设计施工事件日志方面还没有任何重大应用;（2）识别、评估和改进设计;（3）以面向实践的KPI和增强的模拟模型的形式提供决策支持。七名HQP将接受双专业（设计和数据科学技能）培训，他们将有助于实现这些目标。 该计划将扩展现有的事件日志开放标准，以支持设计中的事件、属性和关系以及相关参与者的行为。最后，该计划将提供一套面向实践的KPI和方法，以加强施工过程模拟。 这项研究计划将是在AECO的过程和演员的评估向前迈出的重要一步。它将在三个主要层面产生可交付成果：（1）数据标准和数据挖掘工具;（2）方法和算法;（3）全球和加拿大AECO行业模型;以及公共部门机构。