Semester

Spring

Date of Graduation

2013

Document Type

Thesis

Degree Type

MS

College

Statler College of Engineering and Mineral Resources

Department

Mining Engineering

Committee Chair

Vladislav Kecojevic

Committee Co-Chair

Christopher J. Bise

Committee Member

Brijes Mishra

Abstract

Rope shovels are used to dig and load material in surface mines. One of the main factors that influence the productivity and energy consumption of rope shovels is the performance of the operator. Existing methods of evaluating operator performance do not consider the relationship between production rate and energy consumption. This thesis presents a method for evaluating rope shovel operators using the Multi-Attribute Decision-Making (MADM) model. Data used in this research were collected from an operating surface coal mine in the southern United States. The MADM model used in this research consists of attributes, their weights of importance, and alternatives. Shovel operators are considered the alternatives in the MADM model. The energy consumption model was developed with multiple regression analysis, and its variables are included in the MADM model as attributes. Formulation of the production rate model is already known, and thus determining the attributes that have a significant influence is straightforward. Preferences with respect to min/max of the defined attributes were obtained with multi-objective optimization. Multi-objective optimization was performed with the overall goal of minimizing energy consumption and maximizing production rate. Weights of importance of the attributes were determined by using the Analytical Hierarchy Process (AHP). The overall evaluation of operators was performed by using one of the MADM models, PROMETHEE II. The research presented here may be used by mining professionals to help evaluate the performance of rope shovel operators in surface mining.

Download

Share

COinS