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A key underlying challenge in today's model-driven approach to engineering is how progress and level of effort are being measured and reported. Recent definitions such as level of development enable project teams to track completeness of information in building information modeling (BIM)-driven processes; yet, there are no established processes or metrics to reliably measure progress or track productivity of a model-driven engineering process as a function of the maturity of the model and/or the data that supports the engineering process. To address this gap in knowledge, this paper presents a discrete set of model maturity index (MMI) definitions to measure progress in engineering work, per modeling discipline. Using these MMI definitions, a model maturity risk index (Model MRI) toolkit was created to track maturity of an engineering process at the granularity of work breakdown structure locations. The MMI toolkit also reports risk in achieving certain MMI levels per modeling discipline. To benchmark maturity of the modeling work per project milestone or model review session and to establish workflows for tracking progress, an addendum to the modeling execution plan (ModelXP) is presented. New productivity and project controls metrics for tracking modeling work are also introduced. The developed definitions, toolkit, and addendum to ModelXP were validated through exhaustive surveys and charrette tests with project stakeholders involved in capital projects. The role of the MMI definitions and Model MRI toolkit in providing project controls insight and proactive management opportunities in real-world projects is discussed in detail. [ABSTRACT FROM AUTHOR]

This paper focuses on applying that part of the design-process knowledge referred to as “design intent,” which is of essence to material selection and substitution. We have focused on the type of design intent that is related to architectural design. We express design intent in terms of function, user requirements, performance, and physical properties of a design description. This paper shows how design intent can guide the contractor's material selection and substitution when faced with a proprietary brand-name-or-equal specification. In such cases, the designer requires the contractor to use a specified material brand or any other material that is “equal.” However, the conditions of “equal” are usually not explicit. Five algorithms structured in pseudocode terms are provided for such equality interpretation. The paper concludes that a better understanding of design-process knowledge can strengthen the communication between design and construction. [ABSTRACT FROM AUTHOR]

Assistant Professor de la Garza and Research Assistant Panagiotis Mitropoulos in their CIB Montreal paper present the results of their study, first introducing the beta model and describing the methodology used to validate it and subsequently the technology transfer process is summarized. Although the model focuses on the transfer of expert system technology to the architecture, engineering and construction industry, the model provides a framework that can be used by all engineering disciplines for analysing the transfer of innovative technologies. [ABSTRACT FROM PUBLISHER]