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

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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.