An expert system for hydraulic excavator and truck selection in surface mining

C. Kirmanli*, S. G. Ercelebi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

26 Citations (Scopus)

Abstract

The purpose of this paper is to develop an expert system for hydraulic excavator and truck selection in surface mining. Hydraulic excavators and trucks are finding increasing applications in mining operations. Hydraulic excavators are extensively used especially when bringing electricity to rural areas is difficult and for small-scale mining. This paper describes an expert system, which selects the optimum hydraulic excavator truck configuration such that unit production cost is minimized and technical constraints such as geological, geotechnical and mining constraints are satisfied. The system has four modules: user interface, rules and an methods, databases and output module. The expert system in this study is developed within KappaPC shell. It supports object-orientated technology for the MS Windows environment. The software provides a very useful tool to practitioners, saving time and cost. Equipment selection is a recurring and expensive problem of mine planning and often involves interdisciplinary experts from different fields. It is very difficult and expensive to bring together all these experts. The capabilities of the expert system developed are illustrated in the paper. The software overcomes the difficulties of selecting the proper equipment for surface mining operations, which is very important, and results in substantial savings. Equipment databases for hydraulic excavators with 15-59 yd3 capacities and trucks with 35-360 tons are constructed and these databases are used to select the proper configuration. A case study is carried out for Soma Surface Coal mines in Turkey.

Original languageEnglish
Pages (from-to)727-738
Number of pages12
JournalJournal of the Southern African Institute of Mining and Metallurgy
Volume109
Issue number12
Publication statusPublished - 2009

Keywords

  • Diggability
  • Equipment selection
  • Expert systems
  • Hydraulic excavators
  • Surface mining

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