A Knowledge-Based Decision Support System for Scraper Selection and Cost Estimation

نویسندگان

  • Khalid A. Eldrandaly
  • Neil Eldin
چکیده

Scrapers are advantageous earthmoving construction equipments as they are independently capable of excavating, hauling, and placing soil. Determining the suitable and the most economical selection of the size, model, and number of scrapers and pushers is a complex process that depends on multiple factors such as the haul-road conditions, equipment performance, operation’s travel time, etc. Equipment selection is the first and the most important decision made by a contracting firm. The right choice of equipment determines competitiveness as well as profitability. Therefore, this paper presents a prototype knowledge-based decision support system for scraper selection and cost estimation. The system is developed through employing Visual Rule Studio® (an object oriented COM-compliant expert system development environment for windows) as an ActiveX Designer under Microsoft Visual Basic 6.0 environment since it combines the advantages of both production rules and object-oriented programming technology. Also, using Component Object Model (COM) technology in designing and integrating the different components of the prototype system will assure software interoperability between these components. The architecture, the development and the implementation of the prototype system are discussed in details. A typical example is also presented to demonstrate the application of the prototype system.

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عنوان ژورنال:
  • Int. Arab J. Inf. Technol.

دوره 3  شماره 

صفحات  -

تاریخ انتشار 2006