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By H Hoogvliet

The Goondicum Crater industrial minerals deposit is located about 30 km east of Monto, Central Queensland, Australia. Early exploration programs in the 1990s found alluvial ilmenite along the banks of the Burnett River. This mineralisation was traced upstream to the Goondicum Crater. The Goondicum Crater is a topographic feature centred on a roughly circular 6 km diameter layered gabbro complex. Significant ilmenite, apatite, titano-magnetite and feldspar mineralisation are present in a weathered horizon up to 25 m thick. After several drilling campaigns in the Crater and subsequent feasibility studies, the project was developed by Monto Minerals Ltd, an ASX listed company, in 2007. However, the project never achieved production performance expectations and ran out of commissioning funds. The company subsequently went into voluntary administration in August 2008.In 2009, the RMM Capital group, of Brisbane, took control of Monto Resources Pty Ltd, and renamed the company Belridge Enterprises Pty Ltd (Belridge). Belridge commissioned a redevelopment study aimed at recommencing mining and processing operations. As part of the redevelopment study the authors planned a drilling campaign, managed a quality control program and developed a block model. This paper describes the drilling program, analytical procedures, quality control procedures and the preparation of the block model.The block model for the resource estimate was created using 1 m high blocks, wireframes defining the main material types, and 2.5 m thick horizontal search ellipsoids with a radial pattern. The deposit was ‘flattened’ prior to modelling. To assist with the economic evaluation of the project, each block in the model was assigned a net dollar value based on economic parameters provided by Belridge, including anticipated revenues and costs. This modelling technique allowed for efficient investigation of various scenarios and was used extensively in the development and optimisation of the project’s financial model. At a zero net value per block, comparable to a break-even cut-off grade of four per cent ilmenite equivalent, the Indicated plus Measured resource is estimated at 51 Mt, averaging 4.1 per cent ilmenite, 1.9 per cent apatite and 2.5 per cent titano-magnetite.

Oct 5, 2011

Block caving is the lowest cost underground mining method but it has relatively high risks and a high up-front capital and development cost. It has application to large, often lower-grade orebodies where high production rates can provide good returns on the investment. However, it has a range of technical risks that are peculiar to block caving and the usual financial, political and environmental risks that may be exacerbated by the long lead-in times associated with the development of a block cave operation. With initial development costs that may be $100 M to $1000 M when the building of a treatment plant is also required, it is obviously important to minimise and manage the risks. In a greenfield project, commitment to a substantial proportion of the capital expenditure may be required to gain access to the deposit, and the decision to proceed at this stage would be based very largely on interpretations of drill hole data. In established mines the data may be supplemented by geological mapping and past experience, etc. The quality of this data is critical and yet it is frequently degraded through poor techniques and avoidable omissions. The final decision to proceed would be assessed on projected commodity prices, mining capital and operating costs, dilution and run of mine ore grades. The latter will vary over the life of the project and these can be estimated with drawdown or draw control modelling techniques. In this modelling, there are further risks in the assumed modelling parameters or that the modelling technique may not be applicable or appropriate. The paper addresses the most critical technical and operational risk areas and provides some practical precautions that can be taken to reduce these and improve the reliability of the geological and geotechnical models.

Jan 1, 2000

By J Westh, S Rashleigh, L Gallagher

Mining companies are moving towards automated haul trucks and other equipment. One reason for this is that if automated trucks can operate in a standard pattern over and over again without variation, then human error is reduced, if not eliminated.The challenge for mining production leaders/managers is to ensure operators follow standard operating procedures for load and dump operations, with each operator doing the same thing, every time. However, operators are only human and inconsistent performance is rife at every mine site. The finger may be pointed at the operators for not doing as instructed. The clarity and variability of trainer instructions may be considered causal to the problem. Herein lies the problem. Almost all operators believe they are following the procedure very closely; moreover, they all demonstrate a strong desire to conform to instruction.Using video analysis and feedback, each operator can be shown where and by how much they differ from the benchmark set by their company. Operators, often for the first time, can see definitively what they are doing, compared to industry best practice.The technology utilised by real-time video (RTV) crews measures time, distance and angles. It can overlay the video of the operator at the load site, with video of the perfect pass. Operators are amazed when they see how near to, or how far they are from best practice.The footage and data gathered by RTV assists operators in understanding exactly what adjustments are required to increase proficiency. It also assists load and dump superintendents to identify where in the process they are losing time. When translated to overburden removal or mineral/resource extraction, the result is large production economies without the need for large capital investment in new automated technology.CITATION:Westh, J, Gallagher, L and Rashleigh, S, 2012. Improving safety and mine productivity using real-time video technology, in Proceedings International Mine Management 2012, pp 173-188 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 20, 2012

By P Dowd, R Jeuken, C Xu

In Australian coalmines there are a number of coal quality parameters that are measured by analysing samples from boreholes. The data points are used to generate spatial models of these parameters, typically using inverse distance as an interpolation method. Numerous additional boreholes are drilled which have geophysical logs measured downhole but from which no coal quality samples are taken. Full suites of coal quality analyses are expensive and time consuming to drill and sample. If geophysical proxies for coal quality could be used, this would greatly improve the accuracy of the resource estimation without additional cost.This paper examines two of the most important coal quality parameters – ash and volatile matter – and assesses the results of a number of geostatistical interpolation methods. The aim is to improve the accuracy of the interpolated models. Auxiliary variables from geophysical logs are also trialled to improve the estimation.A multivariate analysis of ash, volatile matter and several auxiliary variables of a selected coal seam was undertaken in a spatial context, using variography. This was used to construct a model of co-regionalisation that relates all of the variables as manifestations of an underlying geological theme.The traditional inverse distance interpolation approach was compared to ordinary kriging, universal kriging, co-kriging, regression kriging and kriging with external drift approaches. The relative merits of the six interpolation methods were compared by removing all points, one at a time and estimating at the thus known location. The mean error and the root mean square error were evaluated as a measure of bias and precision.This paper demonstrates that there is significant opportunity to improve the estimations of coal quality when using kriging with external drift. For example, the results show that when using the depth of a sample as an external drift variable there is a significant improvement in the accuracy of estimation for volatile matter. Furthermore, when using borehole wireline density logs as an auxiliary variable for ash content, there is improvement in the estimation of the in situ ash. The underpinning reasons for this are discussed in the context of the underlying geology and the physical properties of the coal. These findings hold promise for utilising cheaper proxies for coal quality parameters to dramatically improve data density and the quality of estimations.CITATION:Jeuken, R, Xu, C and Dowd, P, 2017. Improving coal quality estimations using geostatistics and auxiliary variables, in Proceedings Tenth International Mining Geology Conference 2017, pp 157–168 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 20, 2017

By J P. Sykes, A Trench

"The common-held view of the future of copper mining is one of declining quality of mineral resources and increasingly limited long-term development options. This decline, in turn, is viewed as inevitably leading to increasing economic, socio-political and environmental costs. As a result, new technologies and innovations will be required to mitigate cost escalation. The future is therefore typically summarised as a battle of a ‘below-ground’ declining quality asset base pushing costs upward versus ‘above-ground’ technology and innovation driving costs downward. The role that high quality new mineral discoveries could play in mitigating industry cost pressures is typically understated, if considered at all. New high quality discoveries can be mined at lower cost than existing assets and potentially if discovered in the right locations within a more amenable contemporary environmental and socio-political setting. Such deposits, once discovered, would improve the overall quality of the industry asset base, as well as benefitting their owners substantially through higher margins. However, to target new high quality deposits explorers need some understanding of the nature of high quality copper mines in the long-term future. Conventional scientific and economic techniques for analysing the future of copper supply, generally by studying the project pipeline, ignore as yet undiscovered resources and also struggle to fully incorporate the multiple internal and external factors that could impact upon copper mining practices in the future.Scenario analysis is specifically designed to consider multiple factors interacting in the future, and is thus more creative than simply looking at the visible project pipeline. The use of scenarios is therefore potentially capable of providing insight into aspects of the future of copper mining about which little is currently known or that remains considerably uncertain. In this study, the Oxford University Scenarios methodology was employed to analyse different plausible futures for copper mining and the consequent implications for exploration targeting strategies. The scenario analysis highlights two key dimensions or axes that serve to map out potential industry futures: firstly the technical and economic optimisation of the existing industry; and secondly the generation of new prospects or ‘search space’ for the copper industry. These two axes in turn frame four different scenarios for the future of the copper mining industry. These copper mining scenarios are then compared to the 20 largest existing copper mines and projects, and their owners, to determine if any represent an appropriately robust exploration targeting proxy: none do. The paper therefore concludes that efforts by industry are required to generate mine concepts that would be viable across all scenarios, and thus act also as exploration targeting proxies. In the interim, companies will have to seek to build portfolios that create an overall robust asset base, out of individually less robust assets. Failure to do this implies that consequential, irreversible strategic decisions lie ahead for the copper mining industry, which may be a threat to both incumbents and the very industry itself. This situation makes strategic exploration targeting in the copper industry very difficult.CITATION:Sykes, J P and Trench, A, 2016. Using scenarios to investigate the long-term future of copper mining and guide exploration targeting strategies, in Proceedings International Mine Management Conference, pp 265-290 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Jun 22, 2016

By D Kent, J Bullock, M Wilkinson

Over the last few years at Glencore’s Mount Isa Copper Operations (MICO) mining conditions have become increasingly challenging through lower head grades and higher work indices. MICO has had great success improving operating efficiencies and increasing productivity through focusing on technology, innovation and operational discipline. The recent implementation of the Mine Site Technologies (MST) ImPact System has supported the continued transformation of the MICO operations through improved personnel safety and direct measurement of productivity. The ImPact System has implemented new safety systems such as the heavy vehicle proximity detection system, underground personnel tracking system and emergency evacuation dashboards improving the overall safety of the workforce. The ImPact System has facilitated productivity improvements via real-time equipment and personnel monitoring, and the implementation of exception reporting (personnel productivity), KPI reports and production dashboards, and transparent reports highlighting developing maintenance issues.This paper discusses the components of the ImPact System, the current installation at MICO, and critically analyses the implementation processes and right sizing of the system to meet the needs of the business today and into the future.CITATION:Bullock, J, Kent, D and Wilkinson, M, 2017. Productivity and safety improvements supported by MST’s ImPact System at Glencore’s Mount Isa Copper Operations, in Proceedings 13th AusIMM Underground Operators’ Conference 2017, pp 279–286 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Oct 16, 2017

By C Hoffmann

Given that each year, 30–40 per cent of mining industry deaths are attributable to failures of vehicle interaction controls (EMESRT, 2023), the mining industry is now armed with a growing body of knowledge from EMESRT (Earth Moving Equipment Safety Round Table) and ICMM (International Council on Mining and Metals) global vehicle interaction initiatives over the past years, that enables mining companies, OEM’s and technology providers to work together to develop and implement more effective controls and drive the adoption of capable solutions. Leveraging 20 years of experience as a global technology provider of Proximity Detection System (PDS) and Collision Avoidance System (CAS) solutions for surface mining operations, Wabtec Digital Mine Technology shares key insights for ensuring the effective selection, implementation and integration of these technologies into existing mine site controls and mining operations for effectively reducing vehicle interaction risk enabling mines to drive towards ‘zero-harm’ objectives. Topics covered include: alignment with industry best practice for controlling vehicle interaction risk by EMESRT and ICMM, importance of the maturity of EMESRT levels 1–7 vehicle interaction (VI) control framework, managing expectations that PDS/CAS is a ‘silver bullet’, alignment with industry functional – performance – technical requirements, proximity detection versus collision avoidance, sensor performance and fusion and limitations, rules engine intelligence critical to mitigating nuisance alarms during normal operations, system health monitoring and reporting, human factors engineering and operator acceptance, implementation strategy, installation standards and quality control, change management program, training programs, reporting and data analytics with actionable insights and maintenance strategies. Insights will also be provided on the challenges moving from EMESRT levels 7 (operator awareness) and 8 (advisory controls) to level 9 (intervention controls) as it’s a journey not an out-of-box solution, the growing demand for coexistence of CAS and Autonomous Haulage Solutions (AHS), functional safety approach, value added systems integration and the applicability of new emerging technologies.

Apr 16, 2024

By P Thwaites

The mining industry uses many types of mineral and metallurgical plants to produce saleable product from ore mined. Plant design history has left current operations with a mixture of manual operation and various forms of automated process controls. Consequently, we typically see high-variability in the continuous operations together with a shortfall in the attainment of full capacity or higher utilisation of consumables.At a level of best practice, ‘operational performance excellence’ focuses on process control, using automation and control systems to deliver process optimisation. This more sophisticated delivery is a great deal more difficult than the first stage of equipment selection/installation. It includes the appropriate selection of the right instrumentation and control system, key process knowledge, individuals with a solid control engineering background/experience and the essential backing/support of the operations management team together leading to higher-value delivery. Robust solutions can be realised, considerably minimising process variation, thus leading to process optimisation. This approach results in an easier, efficient and safer process while providing considerable returns for the plant owners.How variable are your processes, and do you maintain optimised process performance with dedicated resources, modern instrumentation, ‘best practice’ control systems and performance monitoring tools? In this paper, these questions and their possible answers are discussed.I say we can do much more and be ‘more efficient’ in our efforts to remain competitive. This area remains a major opportunity for improved efficiency, minimising tailings losses and other milling costs.CITATION:Thwaites, P, 2014. Manual control, process automation or operational performance excellence – what is the difference?, in Proceedings 12th AusIMM Mill Operators’ Conference 2014 , pp 13–40 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 1, 2014

By Low Russell

Mark Westfield, writing in The Australian on 16 May 1994 stated: The role of the independent expert is crucial to Australia's investment system. When it falls down, there can be very dramatic consequences. The scope of these consequences was dramatically illustrated in the decision of Rogers J. at first instance in Cambridge Credit Corporation v. Hutcheson (1983) 8 ACLR 123 when the auditors of the failed company were found liable for breach of contract and faced a damages award of $145 million, well in excess of their insurance cover. No comfort should be sought in the fact that this decision was overturned on appeal, for the result of the appeal rested on whether there had been a causal connection between the breach of contract which had occurred and the loss suffered, rather than on the fundamental principle of auditors' liability. Thus: Those who prepare experts' reports in company cases carry a heavy moral responsibility, whatever their legal duties may be... Unless high standards are observed by those who prepare these reports, there is a danger that systems established for the protection of the investing public will, in fact, operate to their detriment through reliance placed on those reports and on the reputations of those who furnish them. In lending his name, the expert will often, as in this case, be lending a name to conjure With.

Jan 1, 1995

By V Liebezeit

Data management is a significant, but perhaps unrecognised, consideration for any organisation embarking on a geometallurgy program. While resource geologists are accustomed to dealing with thousands or millions of samples and their associated assays, metallurgists and mineralogists have traditionally carried out only a few expensive and complicated tests and consequently tend to manage the resultant data in spreadsheets. The emerging discipline of geometallurgy arrives with significant challenges as a result of the sheer volume of data generated. As an example, the Olympic Dam geometallurgy program has generated more than:60 000 physical subsamples analysed for up to 30 analytes; 25 000 spreadsheet-based laboratory test results; 30 000 sized fractions analysed via QXRD, MLA and/or QEMSCAN;multiple external providers of data, and more than seven terabytes of data. Considerations for any geometallurgy data management system include storage space, data integrity, accessibility, traceability (sample provenance), maintenance and ease of use, integration with data providers and the ability to modify the system to adapt to changing requirements. Further, aspects of a geometallurgy program, such as conducting a range of tests on one sample, producing subsamples such as concentrates and tailings, compositing and routine QA/QC may not be well handled by existing software and providers geared to standard geochemistry, mineralogy or metallurgical test programs. The development of a geometallurgy database using existing software (AcQuire), and the associated file management system will be described for a large geometallurgy program at Olympic Dam. As with many aspects of geometallurgy there is no approach that meets the needs of every site or program. Recognition of data management as an issue, a structured approach in the program planning phase and commitment to executing the strategy will increase the chances of successfully mining the geometallurgical data.

Sep 5, 2011

The mineral processing industry is in boom times. The focus on mill availability and therefore profitability has never been greater, as grinding mill maintenance often dictates the entire plant shut down duration. Advances in mill systemsÆ quality and reliability and the faster, safer relining afforded by RMEÆs Mill Relining Systems have significantly enhanced grinding plant availability and utilisation. Yet relining performance is still affected by the design and planning by a team of stakeholders long before the maintenance team set foot in the mill. For a greenfield grinding plant project, these team players include: 1. project owner, 2. project manager, 3. mill supplier, 4. liner supplier, 5. plant operating personnel, 6. plant maintenance personnel, 7. mill relining crew, and  8. mill reline system supplier (RME). The complex and sometimes competing design demands of mill construction and operation together with the pressure of tight timelines can result in even simple maintenance requirements being overlooked let alone optimising plant design and planning for maintenance. This paper identifies all the involved stakeholders in an effective mill relining 'team' and gives principles and considerations for each to more effectively achieve the goals within their vital roles. This paper is aimed to be a practical guide for grinding mill designers and planners to more fully exploit the advances in Mill Relining Systems and improve their mill profitability.

Jan 1, 2008

By N Anderson

With traditional grade control processes, geological models are created by geologists at the completion of the data collection stage and wireframe construction is closed off at a set date to allow for time to complete the estimation process. Any issues identified at earlier stages or the addition of new data requires the estimation process to be started again. Alternative interpretations are explored only if time allows and often in a limited fashion. An alternative workflow has been developed at the Waihi Underground Gold Mine utilising Leapfrog Edge and Seequent Central. Geological and grade control models are created, dynamically linked, and saved as separate branches. A project geologist is able to work on the grade control model and a mine geologist on the geological model simultaneously. This allows for a non-linear modelling workflow with continual review and feedback. The introduction of new data can occur right up to the model due date, with data collection, validation, alternate interpretation, and review happening incrementally. Models are categorised and stored in Seequent Central according to project status. An approved version of the geological model and grade control estimate are uploaded at the time of release and transparently capture all data used at a point in time, as well as the review process. Dynamically updating models for grade control has reduced turnaround time while increasing accuracy and quality. Estimates of individual domains are vastly improved from being able to rapidly evaluate the effects of model parameter changes in real time and 3D. Development and stope design directly benefit from these streamlined processes, with higher quality, timely production occurring as a result.

Mar 22, 2022

By B P. Micke

Central Norseman Gold Corporation was established in 1935 and has been mining on the Norseman field in Western Australia since then. It is Australia’s longest continuously operating gold mining operation at nearly 80 years, although it has had its periodic challenges in the intervening years.Over the last 40 years, a series of open pit mines around the Dundas Goldfield have supplied lower cost mill feed to the Phoenix Mill at Norseman from time to time but this has largely come to an end for the foreseeable future. Now that underground ore sources are once again the principal mill feed, there are several challenges to be met for an ongoing profitable operation.During the last 20 years, there have been three different owners and this has affected the manner in which the operations were managed quite significantly. These differing approaches are contrasted and examined in some detail from both the operational and financial aspects.Planning of a downsized operation to ensure sustainable profitability in the future in a mining environment where there has rarely been more than two to four years of reserves ahead of the mill for planning purposes has been a significant challenge. Several of the options examined are described, including alternatives for future mine development.CITATION:Micke, B P, 2014. Managing the margin at Norseman, Western Australia – a case study, in Proceedings 12th AusIMM Underground Operators’ Conference 2014 , pp 119–128 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Mar 24, 2014

By G Malherbe, J Gonzalez, D C. Franklin, J Bassan, C T. Farrelly

To respond to ever-increasing challenges, mining companies have been experimenting with new business models and technologies in order to speed mine development, production, processing and transport. The various experiments involve mobile access to data, intelligent sensors, advanced analytics, virtual collaboration, virtual reality, automated equipment, remote operations centres and strategic partnerships. A synthesis of all these components creates a ænetwork effectÆ that can dramatically improve the overall effectiveness the entire operation. The concept of the Network Centric Mine borrows from a variety of industries, including defence, aerospace, aviation, petroleum, utilities and manufacturing. Central to the concept are improvements to the way we connect people, process, information and technology, resulting in a more highly collaborative business model, with roles and processes designed to take advantage of new technology. The components of the mining operation act as a connected network aimed at a common goal, regardless of the boundaries of organisation and location.The design of this new organisational ecosystem needs to take into account the recent advances that enable the æplug and playÆ integrated collaborative environment, including cloud computing, mobile devices and social networking, as well as advances in augmented reality, robotics, geo-location, digital labelling, simulation and analytics. However, the most consistent lesson from other industries is the need to properly enable the behaviour and process changes necessary for success.Benefits from adopting a network centric approach include the more effective use of scarce expertise, improved data and information analysis, reduced process variance, and more informed and faster decision-making. The future of mining will see more technology savvy workers who will drive the adoption of new processes. The operations will shift from a relatively static and disparate set of functions, to a digitally aware, dynamic, automated, integrated and interactive environment, with increased agility, lower operating costs, higher productivity and improved safety.CITATION:Farrelly, C T, Malherbe, G, Gonzalez, J, Bassan, J and Franklin, D C, 2012. The network centric mine, in Proceedings International Mine Management 2012, pp 143-160 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 20, 2012

With the theme of û æUnderground Ore Handling SystemÆ, Kopanang Mine completed an extensive project on a specific system with technologies for the handling of ore from a dedicated drawpoint to the shaft system. The intended rail haulage tramming system had to be capable of handling the shaft design and Life of Mine (LOM) requirements. Kopanang is an AngloGold Ashanti gold mine situated in the province of the Free State in South Africa. In the Sotho language the name æKopanangÆ means to come together as a team. ItÆs an appropriate name given that 25 companies worked on this project. The future focus at Kopanang is to establish four mining levels between 3 to 4 km south-west of the shaft and two mining levels to the west. The mine has an expected life of almost 20 years and capital was approved in order to access this reserve to establish the infrastructure to handle the ore, hence this exclusive rail haulage tramming system of close to R40 million (SA rands), which took three years to construct. Apart from the fact that this system had to be capable of handling 6500 t per shift at a depth of over 2 km over a length of 3.2 km, some of the major considering factors were: safety, economic factors with improved labour productivity, efficiency and reliability, risk termination, and ergonomics. The system comprises two 20 t locomotives operating in a double header configuration from a dedicated draw point to a dedicated tip area for the reef and waste ore. With the objective of handling high speed and high capacity, this 200 t payload train is capable of running at 35 km/h powered from a 500 volt ac overhead line. Each loco consists of two 90 kW dc motors with ac/dc power conversion on the locomotive. For the system to operate at this speed, the rail system is constructed with Class 1 rails over the entire hauling distance. The tipping mechanism is unique and the span of 11 hoppers each with a load of close to 20 t is capable of tipping the pay load of 200 t in about 20 seconds hands free.

Jan 1, 2005

By C Parihar, R Garg, A Bhandari, S Bhandari

Blasting can impact the efficiency of entire downstream mining operation. Individual technology solutions for blasting have been available in the industry for many years but all of them only cater for certain aspects of blasting. Many of them are based on individual research and/or experiences. Some of the available software solutions are not suitable to be used in the field as that they need advanced skills or tools. Also, most do not take technology advancements like mobility, advanced data analytics, web solutions and integration into consideration. Hence, no technology platform is currently present in the industry that addresses all potential needs a blaster may need in an integrated manner.This paper presents an integrated solution that takes care of all aspects of blasting – design blasts according to mine plan; collect data after drilling has been carried out (as there is often difference in designed and actual drilled hole locations in the field); predict blast results in terms of fragmentation, flyrock, ground and air vibrations, wave front reinforcement and flyrock distance; and after assessment, allows changes in charging, delay timing and sequence. The technology solution is a secure, cloud-hosted, web-based software-as-a-service solution that can be accessed from anywhere. Also it has a mobile app, which is available for both Android and iPhone/iPad. The mobile app is also integrated with the web-based solution using application programming interface calls to the central data repository.Case studies for two limestone mines are presented where this solution is being used in its initial format. This software platform enabled analysis of the outcome from a previous blast pattern and then subsequently allowed optimisation of blasting operations based on historical data. Uses of this platform have resulted in improved key performance indicators in these two limestone mines. The mobile app as part of this platform enables extensive field blast data capture and analysis and also various predictions before a blast. Data collected include blast parameters, individual hole charging, initiation pattern, videos, photographs and vibration records for analysis/reporting. The key features of the solution are a blast designer, a detailed blast data collection/analysis and a series of environmental predictors. These predictors give blast results in terms of fragmentation, flyrock, ground and air vibrations and wave front reinforcement and take remedial steps before blasting to optimise and control adverse environmental impact. Many features, such as fragmentation predictor and mobility solution, are completely unique features that are not available elsewhere in such a field personnel-friendly manner.CITATION:Bhandari, S, Parihar, C, Garg, R and Bhandari, A, 2015. An integrated technology solution for optimised and environmentally-controlled blasts, in Proceedings 11th International Symposium on Rock Fragmentation by Blasting, pp 393–400 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 24, 2015

By J Balzary, A Mohais

Dynamic market and operating conditions, coupled with an environment in which multiple objectives and trade-offs are common, pose major challenges for planners and schedulers working in any mining entity. Many mining companies recognise the need to shift from a siloed mining-focused push model to an integrated value chain, demand-driven approach, but there are still fundamental barriers in business process and the supporting technology preventing a consideration of end-to-end optimality.This paper presents some elements of experiences working with companies to adopt such advanced approaches. In addition to algorithmic elements, an approach to phased and gradual deployment of progressively more sophisticated optimisation models is described. From a practical software adoption perspective, it is believed that this last concern is also of primary importance. Next generation approaches to the optimisation of complex bulk commodity demand chains, namely iron ore and coal are presented, with case studies in the world’s largest integrated operations in Western Australia and Queensland from the raw material mined through to market. Utilising accurate simulation models supported by metaheuristic optimisation techniques, a range of ways to engineer a dynamic decision support framework that can adapt and change with the inevitable changes in commodity markets is explored. Objectives such as total revenue, margin, cost, NPV, throughput, asset utilisation, contractual penalties and bonuses, and energy consumption can be managed simultaneously across the mine, plant, logistics network, port operation, shipping and sales domains.CITATION:Balzary, J and Mohais, A, 2014. Consideration for multiobjective metaheuristic optimisation of large iron ore and coal supply chains, from resource to market, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014, pp 213–222 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014

By M I. Roberts

As Australia’s mining industry painfully retrenches, mining executives and managers strive to remain viable by seeking significant productivity increases directly through process improvement and indirectly by improving leadership and workplace culture, the most powerful determinant of productivity. Culture is the combination of people’s attitudes and behaviour, together with leadership values and focus.Comprehensive new and automated data collection and management systems promise much for improving productivity, yet despite rapid advances in measurement and sharing of data, the use of data can reduce productivity unless behavioural aspects are considered and designed as part of implementation. This is because systems drive behaviour that in turn shapes attitudes to determine culture.Experience from many mine sites and other industries in three countries confirm that the most powerful drivers of people’s behaviour are the Measurement-Analysis-Reporting system and business leadership.This paper discusses fundamentals of practical, statistically valid process measurement, analysis and reporting systems before discussing associated leadership considerations for sustained improvement in safety, productivity, employee retention, leadership, accountability and commercial returns.The key to productivity improvement is improving core processes and important support processes. In turn, the key to process improvement is identifying the major process components and their interaction by measuring and then analysing their variation and level of performance. Understanding variation is often neglected yet is usually highly significant. It is essential that the fundamentals of statistically valid yet practical process and data analysis are understood and incorporated into system design to ensure productive, informed behaviour.The design and use of Measurement-Analysis-Reporting systems influences behaviour most profoundly and determines people’s effectiveness. Behavioural aspects are detailed by focusing on six primary drivers of human behaviour and five basic systems for managing businesses. These are integrated in a seven-step process and productivity improvement methodology that combines statistical, analytical, systems and behavioural factors.The paper includes development, implementation and tracking of a project plan for improving management and leadership systems to drive aligned behaviours. This key leadership responsibility is essential for improving performance to get the most from capital while providing people with the opportunity to develop greater autonomy, which is essential for self-discipline, responsibility, initiative and accountability.CITATION:Roberts, M I, 2015. Integrating measurement, systems and leadership to build safe, productive cultures, in Proceedings Third International Future Mining Conference, pp 73–82 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 4, 2015

There are many compelling reasons why correct sampling schemes should be standard practice in the mining industry, yet there are numerous examples where poor sampling practices are known to exist in the business yet permitted to continue. It is not just technical issues that can be ascribed to the reasons for the continued use of incorrect methods. This paper proposes non-technical reasons why incorrect sampling practices continue, and identifies potential ways to overcome them.

Mar 1, 2010

By D Brown, Z Tabor

Projects must be flexible to account for the rapid development of new technologies and changing stakeholder expectations. Coupled with calls for bleeding-edge solutions, customers, shareholders, and regulators demand robust, safe products and systems-of-systems. Developing and integrating these solutions is becoming increasingly complex and maintaining the flexibility required to ‘pivot’ to effective solutions can be a serious challenge. The necessary flexibility is fundamental to the Agile ethos, and this family of methodologies therefore offers a potential solution to this challenge (Beedle et al, 2001). These have traditionally been delivered with systems engineering applied through a Waterfall methodology. Agile Systems Engineering combines both approaches and presents a means to achieve these goals without compromising flexibility, quality or safety. A robust methodology for the application of Agile Systems Engineering is required to enhance practical outcomes and reduce risk for real-world mining projects.

Sep 1, 2024