Micah Nehring

Dynamic Short term production scheduling and machine allocation in underground mining using mathematical programming

Abstract Maximising value is the main objective when developing long term mine production schedules. These results provide input for the development of a short term schedule that aims to meet process plant feed requirements so as to produce a quality saleable product. This paper reviews previous work on optimised short- and long term production scheduling and real time fleet management systems. A new dynamic mathematical model using mixed integer programming is proposed to optimise short term production scheduling and machine allocation for application in sublevel stoping operations. The objective of the model is to minimise deviation from targeted metal production. The dynamic nature of the model not only optimises the shift based schedule but also allows rapid equipment reassignment to take place as underground operating conditions change. Optimal results are generated in less than 1 min when trialled on a conceptual sublevel stoping dataset.

A local branching heuristic for the open pit mine production scheduling problem

This paper considers the well-known open pit mine production scheduling problem (OPMPSP). Given a discretisation of an orebody as a block model, this problem seeks a block extraction sequence that maximises the net present value (NPV) over a horizon of several periods. In practical applications, the number of blocks can be large, and therefore, the problem can be difficult to solve. It is even more challenging when it incorporates minimum resources requirements that are represented as lower bounds on resource constraints. In this study, we propose to tackle OPMPSP by using a novel metaheuristic technique known as local branching. To accelerate the search process, we combine local branching with a new adaptive branching scheme, and also develop a heuristic to quickly generate a starting feasible solution. Despite consideration of minimum requirements being seldom taken into account in the literature, this method yields near-optimal solutions for a series of data sets we have conceptually generated. To judge the performance of our methodology, the results are compared to those of two techniques from the literature, as well as to those obtained by a mixed integer linear programming (MILP) solver.

Operating value optimization using simulation and mixed integer programming

Mining operations around the world will increasingly need to operate at greater depths. This significantly influences the complexity of ore extraction and ore transportation to the surface. The increase in mine depth leads to increases in haulage distance from mine areas to the mine surface. This results in an increase in energy costs to haul material further. Due to the increasing cost of future operations, the choice of the haulage method becomes an important factor in the optimisation of the mine plan. The haulage process is one of the most energy intensive activities in a mining operation, and thus, one of the main contributors to energy cost. This paper presents the comparison of the operating values of the mine plans at depth levels of 1000, 2000 and 3000 m for diesel and electric trucks, shaft and belt conveyor haulage systems for the current and a predicted future energy price scenario. The aim is to analyse the impact of energy requirements associated with each haulage method, as well as the use of alternative sequencing techniques as mine depth increases. This study is carried out using a combination of discrete event simulation and mixed integer programming (MIP) as a tool to improve decision-making in the process of generating and optimising the mine plans. Results show that energy cost increases across each haulage method at both current and future energy prices, with increasing depth. This study thus provides a broad and up to date analysis of the impact on operating values that may be experienced with the use of the main haulage systems available at present. Also, the study shows how the combination of discrete event simulation and MIP generates a good tool for decision support.

Schemes of exploitation in open pit mining

The exploitation of open pit deposits usually takes place through a series of mining phases, commonly known as pushbacks. In open pit metalliferous mining, each pushback considers the extraction of one or more benches simultaneously in a process where the core operational tasks include: drilling, blasting, loading and hauling. In large open pit mines, shovels and front end loaders may be used to carry out loading activities. The type and number of shovels are selected during the planning process and their productivity determines the mining rate of the benches, pushbacks and the mine. The space available for loading is part of the pushback design. This defines the shape and size of the benches where the equipment will be placed. A relevant stage in mine design is the definition of the location and sequence that loading equipment must follow to deplete the benches of each pushback. The deployment of loading equipment in the mine is commonly referred to the scheme of exploitation. This term is widely used in the mining industry but not frequently referenced in the literature. The objective of this paper is to explore the concept of the scheme of exploitation in open pit mining within the context of the strategic mine planning activity. In the first part, the concept is presented through examples where the pushback size is fixed and the number of shovel is changed. The second part includes a discussion of the motivations and constraints that the mine planner may consider in the design. Configurations with several shovels and benches in a same pushback represent a challenge for the scheme design mainly due to the limitation of space for loading. Mathematical and optimisation tools can be useful in these cases; however, the models have to be able to represent the real constraints that will affect the productivity of the shovels in the different levels. In general, aggressive and costly schemes are rarely used by mining companies that seek high performance levels and lower operating costs. However, the selection of an appropriate scheme of exploitation needs to be aligned with the principal objective of the mine planning activity, which is to: create value through the exploitation of a mineral resource.

Open-Pit Mine Production Planning and Scheduling: A Research Agenda

Mining is a complex, expensive, yet lucrative business. Today’s open-pit mines are huge projects in Australia. To keep the projects profitable, planners and schedulers are under constant pressure to make mine plans that are as accurate as possible and optimize production at all stages, from mine to market. In general, two different systems are available for extracting material in the mining industries: the traditional truck and shovel (T&S) and the modern in-pit crushing and conveying (IPCC) systems. While T&S has been extensively studied by operations research (OR) community, there are, however, almost no studies for optimizing the operations in IPCC systems. Despite great advantages of IPCC systems, mining companies are often reluctant to use it, due to the lack of an optimum strategic plan that makes it difficult, if not impossible, to estimate the costs of IPCC systems. In most cases, industry is still relying on the judgement or best estimate of experienced personnel in strategic decision making. This is without any guarantee of optimality and will be refined manually through multiple time-consuming iterations. This chapter introduces IPCC to the OR community and points out the need for OR research. Subsequently, we will develop a research agenda that provides an apt ground to study this system.

The equipment utilisation versus mining rate trade-off in open pit mining

ABSTRACT This paper investigates the potential value adding role that ‘schemes of exploitation’ may have as part of the open pit mine planning process. The deployment of loading equipment within the push-back of an open-pit mine ultimately determines the ‘mining rate’. Traditional mine planning processes seek to adopt schemes of exploitation that maximise the utilisation of the loading equipment as this will typically minimise mining cost. This paper argues that this does not always lead to the creation of value. A case-study demonstrates that alternative schemes of exploitation, with higher mining costs and lower shovel productivity can actually generate greater value. The results show an increase in Net Present Value from US

Development of dozer push optimisation software for commodore coal mine

920M to US

A new mathematical programming model for production schedule optimization in underground mining operations

966M when a less productive configuration of four shovels is set instead of a configuration of two shovels. A sensitivity analysis is presented to show the economic and technical conditions that can favour this new proposal.

Adjusted Real Option Valuation to Maximise Mining Project Value - A Case Study Using Century Mine

This paper details the development and evaluation of a recently created dozer push program, ‘Dump Designer’ that was used to maximise dozer push horizons at Commodore Coal Mine in the Surat Basin, QLD, Australia. The necessary data required for Dump Designer were collected from the geological model of Commodore. From this, Dump Designer was trialled and the dozer push horizons were maximised wherever possible. Operating costs were then applied to show the benefits of maximising waste allocated to dozers. After processing 556 mining blocks, it was concluded that the coal dip significantly affects the amount of waste the dozers are able to push. It was also found that there are some implementation constraints with regards to mine planning that may prevent the dozers from being able to work to maximum dozer push horizons.