Optimal Drill Assignment for Multi-Boom Jumbos

Michael Champion (2010). Optimal Drill Assignment for Multi-Boom Jumbos PhD Thesis, School of Mechanical and Mining Engineering, The University of Queensland.

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Author Michael Champion
Thesis Title Optimal Drill Assignment for Multi-Boom Jumbos
School, Centre or Institute School of Mechanical and Mining Engineering
Institution The University of Queensland
Publication date 2010-04
Thesis type PhD Thesis
Total pages 189
Total colour pages 20
Total black and white pages 169
Subjects 09 Engineering
Abstract/Summary Development drilling is used in underground mining to create access tunnels. A common method involves using a drilling rig, known as a jumbo, to drill holes into the face of a tunnel. Jumbo drill rigs have two or more articulated arms with drills as end-effectors, that extend outwards from a vehicle. Once drilled, the holes are charged with explosives and fired to advance the tunnel. There is an ongoing imperative within the mining industry to reduce development times and reducing time spent drilling is seen as the best opportunity for achieving this. Notwithstanding that three-boom jumbos have been available for some years, the industry has maintained a preference for using jumbo rigs with two drilling booms. Three-boom machines have the potential to reduce drilling time by as much as one third, but they have proven difficult to operate and, in practice, this benefit has not been realized. The key difficulty lies in manoeuvering the booms within the tight confines of the tunnel and ensuring sequencing the drilling of holes so that each boom spends maximum time drilling. This thesis addresses the problem of optimally sequencing multi-boom jumbo drill rigs to minimize the overall time to drill a blast hole pattern, taking into account the various constraints on the problem including the geometric constraints restricting motion of the booms. The specific aims of the thesis are to: ² develop the algorithmic machinery needed to determine minimum- or near-minimum-time drill assignment for multi-boom jumbos which is suitable for "real-time" implementation; ² use this drill pattern assignment algorithm to quantify the benefits of optimal drill pattern assignment with three-boom jumbos; and ² investigate the management of unplanned events, such as boom breakdowns, and assess the potential of the algorithm to assist a human operator with the forward planning of drill-hole selection. Jumbo drill task assignment is a combinatorial optimization problem. A methodology based around receding horizon mixed integer programming is developed to solve the problem. At any time the set of drill-holes available to a boom is restricted by the location of the other booms as well as the tunnel perimeter. Importantly these constraints change as the problem evolves. The methodology builds these constraints into problem through use of a feasibility tensor that encodes the moves available to each boom given configurations of other booms. The feasibility tensor is constructed off-line using a rapidly exploring random tree algorithm. Simulations conducted using the sequencing algorithm predict, for a standard drill-hole pattern, a 10 - 22% reduction in drilling time with the three-boom rig relative to two-boom machines. The algorithms developed in this thesis have two intended applications. The first is for automated jumbo drill rigs where the capability to plan drilling sequences algorithmically is a prerequisite. Automated drill rigs are still some years from being a reality. The second, and more immediate application is in providing decision support for drill rig operators. It is envisaged that the algorithms described here might form the basis of a operator assist that provides guidance on which holes to drill next with each boom, adapting this plan as circumstances change.
Keyword Predictive control
mixed integer linear programming
Underground mining
mission planning
mining automation
Additional Notes Colour pages: 55, 56, 58, 59, 108, 121, 127, 133, 134, 136, 139, 140, 142, 143, 154, 156, 158, 160, 162, 188.

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Created: Fri, 10 Sep 2010, 10:53:31 EST by Mr Michael Champion on behalf of Library - Information Access Service