Estimating capital and operational costs of backhoe shovels

• Main Authors: Ahmad Reza Sayadi, Ali Lashgari, Mohammad Majid Fouladgar, Miroslaw J. Skibniewski
• Format: Article
• Language: English
• Published: Vilnius Gediminas Technical University 2012-06-01
• Series: Journal of Civil Engineering and Management
• Subjects: loading equipment; backhoe shovel; cost estimation; multi-variable linear regression; principal component analysis; mining and construction
• Online Access: http://journals.vgtu.lt/index.php/JCEM/article/view/4461

Material loading is one of the most critical operations in earthmoving projects. A number of different equipment is available for loading operations. Project managers should consider different technical and economic issues at the feasibility study stage and try to select the optimum type and size of equipment fleet, regarding the production needs and project specifications. The backhoe shovel is very popular for digging, loading and flattening tasks. Adequate cost estimation is one of the most critical tasks in feasibility studies of equipment fleet selection. This paper presents two different cost models for the preliminary and detailed feasibility study stages. These models estimate the capital and operating cost of backhoe shovels using uni-variable exponential regression (UVER) as well as multi-variable linear regression (MVLR), based on principal component analysis. The UVER cost model is suitable for quick cost estimation at the early stages of project evaluation, while the MVLR cost function, which is more detailed, can be useful for the feasibility study stage. Independent variables of MVLR include bucket size, digging depth, dump height, weight and power. Model evaluations show that these functions could be a credible tool for cost estimations in prefeasibility and feasibility studies of mining and construction projects.