This paper provides a methodology for pre-selecting a limited number of activities for detailed investigation using existing robotic feasibility analysis techniques, such as that proposed by Kangari & Halpin [1]. The QCF Delphi method has been employed to survey a significant portion of a company's site management, in order to determine their views on the value of specific robotic or automated systems and to discover the reasons for these views. Using this method reinforcement cage fabrication, site stock control, concrete floor finishing and HVAC installation were found to be the preferred activities for robotic development. It was also shown that service installation and all forms of finishes are presently major sources of construction delay. The method also highlighted the importance of co-ordinating site activities and of controlling the design and management process in order to successfully exploit any automated or robotic system.
Construction schedules exist in many forms to serve many purposes. They are prepared by various means by different individuals either manually or aided by computer software. Work which is underway to automate the production of schedules is now being supplemented by the development of an evaluation package for general usage . Outlined in this paper are aspects of a research project which uses artificial intelligence techniques for the purpose of automating the evaluation of construction schedules. In particular the early stages of the project, which recognise and utilise the logic in schedules, are detailed. Different classes of logic are identified and a general activity logic model is introduced. Techniques for interpreting activity names and for building and using knowledge bases are explained and illustrated with simple examples. The application of the early work to the objective of automated schedule evaluation is discussed.
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