Selection of opencast mining equipment by a multi-criteria decision-making process

Abstract

Sophisticated, capital-intensive, high-capacity earthmoving machinery is now being used in opencast coal mines to meet demand in the face of increasing pressure from competitors. The selection of equipment for coal extraction and overburden removal is a determining factor in the viability and profitability of an opencast operation, seeing that extraction and haulage account for 50–70% of the total costs.1 Mines can achieve the targeted production at the minimum unit cost and gain a competitive edge through selection of the most appropriate equipment. The selection of equipment for mining applications is not a well-defined process and because it involves the interaction of several subjective factors or criteria, decisions are often complicated and may even embody contradictions. Traditionally, procurement costs become elevated through a system of public tendering to appear as the primary criterion and the major costs of looking after the equipment during its useful life are not taken into account.2,3 The cheapest procurement, however, is not always the best and the most economic approach. Life-cycle cost (LCC) analysis helps mine management to justify equipment selection on the basis of the total costs over its useful life rather than the initial purchase price. Rao and co-workers4 and Sharma5 have presented accounts of the methodology for mining equipment selection through LCC analysis. LCC analysis again considers only the cost parameters of similar equipment and other parameters are either predetermined or not considered. Various types of cost model have been proposed for applicaton to the selection of mining equipment.6–9 Hrebar6 and Sevim and Sharma7 used net present-value analysis for selection of a dragline and surface transportation system. Use of a linear breakeven model has been proposed.8 Models for equipment selection and evaluation described by Celebi9 were aimed at selection of the equipment fleet on the basis of minimizing the unit stripping cost and maximizing production. Linear programming10 and decision-making tools11 may be applied. General guidelines and a survey related to the selection of surface mining equipment were discussed by Martin et al.12 and Srajer et al.13 and Chanda14 reviewed the fundamental concepts of equipment selection. Erdem and coworkers presented an extended bench model by means of which the optimal dragline selection may be made.15 Hall et al.16 illustrated how reliability analysis can provide mine management with quantitative information of value for decision-making about surface mining equipment. Some researchers1,17,18 have advocated the use of knowledge-based expert systems. The application of modelling in the selection of a suitable equipment fleet was discussed by Sturgul and Jacobson19 and simulation in the context of selecting an ore haulage system was reported by Lebedev and Staples.20 Most of these decision-making tools either rely on objective input data, with little or no subjective judgement, or focus on a single parameter. Multi-criteria decision-making (MCDM) techniques, such as the Analytical Hierarchy Process (AHP), can, however, be very useful in encompassing several subjective criteria with conflicting objectives to arrive at an eclectic decision. Whereas AHP is well-established as an operations research technique for decision-making in engineering applications,21–24 there has been a dearth of development and application to mining problems. A method of selecting heavy earthmoving machinery for opencast mining use has now been developed on the basis of AHP and is presented here.