The past century has witnessed significant developments in the field of Performance Measurement Systems (PMSs) in a wide range of disciplines, such as business management, engineering and computer science. Since 2007, PMSs have emerged in the Building Information Modelling (BIM) domain, with at least sixteen BIM Assessment Methods (BIM-AMs) developed to date, in both academia and industry. The need for BIM-AMs has been widely recognised, since they help businesses to track their progress of BIM Implementation and compare their capabilities against other companies. But despite these recent developments, BIM-AMs still face some fundamental challenges, in particular the way most assessments still rely on qualitative and subjective judgements, raising questions over accuracy, practicality and validation.This research presents a new approach to BIM-AMs and combines theory with practice. On the theoretical side, the thesis starts with a comparative overview of current Assessment Methods (AMs) to explore their various characteristic including what they evaluate (projects, organisations, teams or individuals), their range of measures and the way in which they communicate results. On the practical side, three AMs are applied to real case study projects in association with multiple Architecture, Engineering and Construction (AEC) companies. This combination of theory and practice expands and challenges what is currently known about BIM-AMs. It offers a solid foundation to build more in-depth research on BIM measurement.In order to optimise the current AMs, an automated plug-in is developed to measure the Level of Detail of model elements. The automation of BIM assessment is shown to have the potential to deliver less qualitative, more objective and practical approaches of assessment. It has the potential to turn subjective and qualitative measures into quantifiable and objective data and provides fast and user-friendly assessment for the AEC businesses.The positive impact of BIM-AMs has been recognised by academics, professionals and policy-makers. Existing AMs have contributed enormously to the field of BIM assessment, but they will only lead to sharper and more efficient businesses if coupled with automation in evaluation and innovation in choosing appropriate measures.
|Date of Award||29 Apr 2018|
|Supervisor||Alexander Copping (Supervisor) & Paul Shepherd (Supervisor)|