Planning and control technologies for construction

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The goal is to improve the effectiveness of current project & construction management (CM) processes for a project's procurement and construction phases through the development of richer representations of its dimensions and application of state-of-the-art information technologies to create computerized environments to improve decision making and enhance insights into reasons for project performance. In pursuing this goal, realities of the construction industry are considered - e.g. highly variable educational backgrounds of personnel, diversity & uniqueness of projects & their context, large sets of heterogeneous data, a need for generality as opposed to a very narrow focus, etc. Research objectives and guiding questions are: Objective 1: Interpretation of construction data using causal modeling and visual analytics - How can seasoned construction personnel express their judgement and experience about performance cause-effect relationships in terms of data collected for CM functions to search for supporting evidence? and, How can visual analytics be used to provide important insights into project performance, improve decision making and aid communication amongst project participants? Objective 2: Creating an environment for formulating and evaluating alternative construction strategies: How can CAD and linear scheduling be combined to allow for the formulation and exploration of alternative construction strategies to enhance project performance? Objective 3: Profiling project context for risk identification, impact and mitigation - How can the profiling of project context assist in developing an accurate risk profile for a project? Three intersecting building blocks underpin the three research objectives: (i) representation; (ii) knowledge management; and, (iii) visual analytics and CAD. Research methodology components include use of large scale data sets, testing of concepts developed on actual projects, building on research by others, and use of state-of-the-art technologies. The research program involves 3 PhD students, 2 MASc students, and 2 MEng students.