Truck Assignment Based in Performace: a Complement Tool to Fleet Management Software.
Introduction
Hauling represents 50% percent (Kennedy,1990) of the operating costs in a shovel - truck open pit mining operation, efforts to control or reduce hauling cost in order to reduce their impact over the mining cost has been done along the time.
The most common approach is to improve the efficiency of the hauling fleet, reducing idle and waiting times for the trucks by assign them to a loading equipment in real time, this can be done using ad hoc software as Dispatch® or Jigsaw® .
These software algorithms work with variables as route length, loading time, hauling time under certain parameters of ore quality and quantity. Based over this information they optimize the variables and assign more or less trucks to a certain face regardless of the truck (as independent unit) performance.
Truck Performance
We can define the truck performance as the capability of the truck to haul material between two or more points efficiently using all their own mechanical functions and characteristics. In order to understand this concept we should notice that two trucks, with the same characteristics and age, can have different production rates over the same route; that difference in their production rate should be address to some factors as their maintenance history (which affect their reliability), accidents and driver’s ability. Moreover, these differences could be bigger if we have a fleet composed by trucks from different models and makers.
Objectives
The objective of this research project is to improve the haul efficiency and reducing cost by develop a tool that can be a complement for the Dispatch® or Jigsaw® software . This tool will select the best trucks, base in their performance, among the fleet in order to be assigned to the active faces.
Methodology
Based in the huge amount of information registered by the Dispatch® or Jigsaw® software in the mine data warehouse is possible to use this information to find performance patterns, that help
Hauling represents 50% percent (Kennedy,1990) of the operating costs in a shovel - truck open pit mining operation, efforts to control or reduce hauling cost in order to reduce their impact over the mining cost has been done along the time.
The most common approach is to improve the efficiency of the hauling fleet, reducing idle and waiting times for the trucks by assign them to a loading equipment in real time, this can be done using ad hoc software as Dispatch® or Jigsaw® .
These software algorithms work with variables as route length, loading time, hauling time under certain parameters of ore quality and quantity. Based over this information they optimize the variables and assign more or less trucks to a certain face regardless of the truck (as independent unit) performance.
Truck Performance
We can define the truck performance as the capability of the truck to haul material between two or more points efficiently using all their own mechanical functions and characteristics. In order to understand this concept we should notice that two trucks, with the same characteristics and age, can have different production rates over the same route; that difference in their production rate should be address to some factors as their maintenance history (which affect their reliability), accidents and driver’s ability. Moreover, these differences could be bigger if we have a fleet composed by trucks from different models and makers.
Objectives
The objective of this research project is to improve the haul efficiency and reducing cost by develop a tool that can be a complement for the Dispatch® or Jigsaw® software . This tool will select the best trucks, base in their performance, among the fleet in order to be assigned to the active faces.
Methodology
Based in the huge amount of information registered by the Dispatch® or Jigsaw® software in the mine data warehouse is possible to use this information to find performance patterns, that help