Date of Award

6-1999

Degree Name

Master of Science

Department

Civil and Construction Engineering

First Advisor

Dr. Anil Sawhney

Second Advisor

Dr. Mohammed Haque

Third Advisor

Richard Arlington

Access Setting

Masters Thesis-Open Access

Abstract

Due to the central role of cranes in construction operations, specialists in the construction industries have cooperated in the development of structured methods and software for crane selection. Most of these software tools are for crane model selection and query the user for the type of crane to be used. Although research produced some fuzzy logic and expert system-based methods for crane type selection, no integrated systems that handle both crane selection phases are available.

IntelliCranes, a prototype integrated crane selection tool, assists in both crane type and crane model selection based on a set of inputs describing the construction operation under consideration. Artificial Neural Networks (ANN) process the subjective data needed for crane type selection while an expert system module performs the crane model selection.

By using historical data and advanced artificial intelligence computing tools such as ANNs, IntelliCranes automates crane type selection. Crane type and crane model selection are seamlessly integrated in a comprehensive crane selection tool, and consistency in the selection of cranes for similar situations is increased. The overall economic adequacy of the crane selected is improved.

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