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

设计和施工过程的识别、建模和评估最近引起了建筑、工程、施工和业主（AECO）研究机构的关注。建筑信息模型（BIM）通过这些流程支持项目团队，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，派生出新的信息。然而，提供可操作的信息需要识别和评估端到端过程，因为它们在实践中发生（与已计划的相反）。流程挖掘是数据科学的一个分支，它通过企业运营数据中的模式识别来检测端到端的业务流程。为此，处理来自ERP系统的数据以形成事件日志（流程挖掘引擎的输入）。尽管在许多行业中为改进流程作出了重大贡献；过程挖掘在设计和施工过程中没有任何主要应用。这主要是由于AECO缺乏ERP系统，而且需要特定领域的解决方案来反映设计和施工项目的独特特征。******该计划的总体目标是自动识别和评估设计和施工过程以及相关的参与者网络。这一目标将通过三个主要目标来实现：(1)扩展现有的数据标准，以支持BIM生成设计和施工事件日志；(2)通过动态IFC文件的分析，识别、评价和改进设计和施工过程；(3)以面向实践的kpi和增强的仿真模型的形式提供决策支持。七名HQP将接受双重专业（设计和施工知识；和数据科学技能）的培训，他们将有助于实现这些目标。******该计划将扩展事件日志的现有开放标准，以支持设计和施工过程中的事件、属性和关系。然后，该标准将用于创建从IFC文件生成BIM事件日志的服务。在第二阶段，将创建各种算法来捕捉一些通用的设计和施工过程。使用这些算法，模型将被训练为这些过程的性能（例如，偏差，瓶颈等）；以及相关参与者的行为。最后，该计划将提供一套以实践为导向的kpi和增强施工过程模拟的方法。******该研究计划将是评估AECO过程和参与者的重要一步。它将产生三个主要层面的交付成果：(1)数据标准和数据挖掘工具；(2)方法和算法；(3)模型和kpi。这将特别有利于三个主要领域：学术界；全球及加拿大AECO产业；以及公共部门机构。

The identification, modeling, and evaluation of design & construction processes have recently attracted attention within the Architecture, Engineering, Construction & Owners (AECO) body of research. 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 processes. This is primarily due to the lack of ERP systems in AECO, and furthermore the need for domain-specific solutions to reflect unique characteristics of design & construction projects. ******The overarching goal of this program is to automate identification and evaluation of design & construction processes and the associated actor networks. This goal will be achieved through three main objectives: (1) Extending the existing data standards for supporting BIM to generate design & construction event-logs; (2) Identifying, evaluating and enhancing design & construction processes via analysis of dynamic IFC files; (3) Providing decision support in form of practice-oriented KPIs and enhanced simulation models. Seven HQP will be trained with dual specialties (design & construction knowledge; 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 & construction processes. The standard will then be used to create a service to generate BIM event-logs from IFC files. In the second phase, a variety of algorithms will be created to capture some of the generic design & construction processes. Using those algorithms, models will be trained for performance of those processes (e.g., deviations, bottlenecks, etc.); 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 & KPIs. These will particularly benefit three major domains: academia; global and Canadian AECO industry; and public sector bodies.