Maptek/KRJA Systems Ltd.

Environmental management and planning requires the integration of large volumes of disparate information from many sources and the analysis of this information with efficient tools for assessment and evaluation. Effective methods of communication that allow interactive participation in the planning, assessment and decision-making processes are also very important. The VULCAN software package from Maptek (Pty) Ltd comprises a large number of 3D graphical tools within an interactive 3D interface called ENVISAGE. These tools are designed and developed to help engineers and scientists to identify and solve environmental problems. The combination of VULCAN 3D Software and the I-SiTE 3D Laser Imaging system leads to powerful solutions for environmental management. This paper presents the capabilities of this integrated system and its applications for environmental management. 1

1.1 Mine Planning Software – A Historical

ABSTRACT: Modern mine planning software plays a crucial role in the operation of many of the world’s mining operations and projects. Mine planning software provides the mining industry with a fast, accurate, cost effective and efficient tool in order to manage their business interests worldwide. Every aspect of the mining industry is today using some form of mine planning software. From exploration to rehabilitation, the use of software is becoming more and more widespread. Mine planning software companies are constantly under pressure to evolve products to meet new challenges and solve new problems. Development of software is a result of both programming foresight and reaction to industry demands. Without mining industry feedback, many of the products now available would probably not have been developed. Mining software is an extremely competitive market which constantly drives the levels of development to new heights. This paper discusses some of the most important new tools and technologies incorporated in modern mine planning software and presents potential areas of improvement and further development

Mine Planning and Equipment Selection 2002 GRADE INTERPOLATION USING RADIAL BASIS FUNCTION NETWORKS

ABSTRACT: This paper analyses the application of Radial Basis Function (RBF) networks in grade interpolation. These networks are a very unique member of the family of Artificial Neural Networks. RBF networks have such theoretical properties that establish them as a potential alternative to existing grade interpolation techniques. Their suitability to the problem of grade interpolation will be demonstrated in this paper both theoretically and through a number of case studies from real and simulated mineral deposits.

Mine Planning and Equipment Selection 2002 ARTIFICIAL NEURAL NETWORK TECHNOLOGY IN MINING AND ENVIRONMENTAL APPLICATIONS

ABSTRACT: A number of mining and environmental related problems have been approached using ANN technology. These problems commonly relate to pattern classification, prediction and optimisation. ANNs have been successfully applied to these areas and are therefore suitable for similar mining and environmental problems. The general trend in the mining industry for automation to the greatest degree calls for technologies such as the ANNs that can utilise large amounts of data for the development of models which otherwise are very difficult or sometimes even impossible to identify. The examples presented in this paper support the choice of ANNs as the basis for developing solutions to mining and environmental problems were conventional techniques fail in one way or another.

Ore Grade Estimation with Modular Neural Network Systems – A Case Study

ABSTRACT: This paper introduces a neural network approach to the problem of ore grade estimation. The system under consideration consists of three neural network modules each responsible for a different area of the deposit, depending on the sampling density. Octant and quadrant search is used as a way of presenting input patterns to the modules. Both radial basis function networks and multi-layered perceptrons are used as the building blocks of these modules. An iron ore deposit provides the training and testing data for both the neural network system and kriging, and the results from the two approaches are compared

Visual Impact Assessment of Seaside Quarrying Operations and Planned Restoration

Digital photography combined with three dimensional models of topography, mining operations and restoration plans can lead to extremely realistic images and animations of the current and future states of a mine or quarry. The amount of work and the time required for the successful modelling of a mine and its restoration plan are surprisingly low nowadays. All these mean that the visual impact of mining and quarrying operations can be easily assessed using common computer hardware and some dedicated software packages. LAVA Mining and Quarrying SA is a company committed to strive continuously for the highest possible environment protection at the company’s quarries. The pozzolanic rock quarry located at Xylokeratia is one of the company’s quarries on the island of Milos and the subject of the study presented in this paper. A thorough restoration plan of the Xylokeratia quarry is being completed by the company. For its purposes, a complete visual impact assessment study was performed at the Department of Geotechnology and Environmental Engineering of th

GEMNET II -- A Neural Ore Grade Estimation System

This paper describes a neural ore grade estimation system developed at the AIMS Research Unit of the University of Nottingham. GEMNET II is a modular neural network system designed to receive drillhole information from an orebody and perform ore grade estimation on a block model basis. The aims of the system are to provide a valid alternative to conventional grade estimation techniques while reducing considerably the time and knowledge required for development and application. GEMNET II is fully integrated inside VULCAN, one of the leading software packages for resource modelling, allowing for advanced visual validation of the grade estimation process. The system uses parts of the SNNS v4.1 neural network simulator for the development and training of the neural network modules. A number of case studies have been carried out using GEMNET II. The results obtained and the overall functionality of the system prove that neural networks can offer a fast and robust grade estimation technique and a valid alternative to well established methodologies in this area

An Agent-Based System Framework for Mine Scheduling and Simulation

In today’s mining environment, improving production, performance, productivity and profitability is crucial. Production, ancillary, plant and shipping equipment need to be monitored and controlled by online systems delivering production statistics and real-time information to everyone involved, including equipment operators. Traditional systems currently in use today, operate in an iterative mode constantly switching between scheduling and execution. However, the real world tends to change in ways that invalidate such advance schedules. Agent based computing has been hailed as the most significant breakthrough in software development and the new revolution in software. Agent systems are being used in an increasingly wide variety of applications, including complex mission critical systems such as Air Traffic Control. This paper presents the possible ways that multi-agent systems can be applied to mine production and rehabilitation scheduling problems with focus on real time fleet management, plant and equipment performance monitoring, downtime and delay reporting, stockpile management, personnel and equipment tracking and product distribution and transportation. 1