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Kroemer(1-3) and Kroemer et al.(4) define the isoinertial technique of strength assessment as one in which mass properties of an object are held constant, as in lifting a given weight over a predetermined distance. Several strength assessment procedures possess this characteristic. Most commonly associated with the term is a specific test developed to provide a relatively quick assessment of a subject's maximal lifting capacity using a modified weight-lifting device.(1,5) The classic psychophysical methodology of assessing maximum acceptable weights of lift is also considered an isoinertial technique under this definition.(6) While the definition provided by Kroemer(1) and Kroemer et al.(4) has been most widely accepted in the literature, some have applied the term "isoinertial" to techniques that differ somewhat from the preceding definition, such as in a description of the Isotechnologies B-200 strength testing device.(7) Rather than lifting a constant mass the B-200 applies a constant force against which the subject performs an exertion. The isoinertial tests described here apply to situations in which the mass to be moved by a musculoskeletal effort is set to a constant. Is Isoinertial Testing Psychophysical or Is Psychophysical Testing Isoinertial? As various types of strength tests have evolved over the past few decades, some unfortunate developments in terminology have arisen to describe and classify different strength assessment procedures. This is particularly evident in sorting out various tests that have been labeled "isoinertial." One example was cited earlier. Another problem that has evolved is that the term "isoinertial strength" has two connotations. The first is the conceptual definition: isoinertial strength tests include any strength test in which a constant mass is handled. In practice, however, the term is often used to denote a specific strength test in which subjects' maximal lifting capacity is determined using a machine and a constant mass is lifted.(1,5) Partially as a result of this dual connotation, the literature contains references to both "isoinertial strength test" as a psychophysical variant(8) and the psychophysical method as an "isoinertial strength test" (4,9) To lay the framework for the next two chapters, the authors will briefly discuss some operational definitions of tests of isoinertial and psychophysical strength. In stating that the isoinertial strength test is a variant of the psychophysical method, Ayoub and Mital(8) refer to the specific strength test developed by Kroemer(1) and McDaniel et al.(5) Clearly, this isoinertial protocol has many similarities to the psychophysical method: both are dynamic; weight is adjusted in both; and both measure the load a subject is willing to endure under specified circumstances. However, while both deal with lifting and adjusting loads, there are significant differences between the psychophysical (isoinertial) technique and the Kroemer-McDaniel (isoinertial) protocol in their procedures and the use of the data collected in these tests. For our purposes, we designate the

Jan 1, 1998

During the past 10 years, research work to improve the survey of stope limits after mining supplied useful information, particularly for large open and sub-level stopes, regarding waste dilution caused by differences between final production limits and planned stope limits. However, the efficiency of this information to improve the overall efficiency of the mining process is limited, given that the impacts of inaccurate ore limits leading to dilution (sensu stricto) and ore losses haw not been considered adequately. Geological/sampling information should be optimized in terms of quantity and/or quality for the deposit characteristics and the constraints of the mining method used. As industry practice regarding the definition and recording of dilution is flexible and as ore losses frequently am poorly doc-umented, the use of these terms is reviewed. Simulations were carried out on two typical narrow gold deposits, based on an earlier study at Inco's Thompson mine regarding the impacts of wide to narrow delineation grids using recorded variations of vein geometry. Vertical to sub-vertical deposits of 3 m and 6 m widths mined by long-hole open stopes were considered. Deposits delineated by 7.5 m (25 ft) grids were taken as a base case and the impacts of less accurate limits in conjunction with long hole mining based only on a 15 m (50 ft) delin¬eation grid. The impacts of overestimation (dilution) and underestimation (metal losses) were considered separately, using the average error of +/-0.62 m recorded in the Inco study. The impact of less accurate information was much stronger on the narrower deposit: both dilution and ore losses diminished the net present value of the 3 m wide deposit by 39.27% and 45.41%, respectively, and that of the 6 m wide deposit by 12.84% and 11.55%. As the impacts of ore loss and those of dilution on the net present value am almost identical in these simulations, we could, in practice, assume a 50/50 split between dilution and ore losses in such a case. These results do no take into account the effects of local optimization measures taken at the mine production level (blasthole sampling near stope limits, etc.) The potential impacts of geological and sampling uncertainties in terms of lower NPV justify and require more systematic efforts to ensure that deposit appraisal work and feasibility studies are adequate to optimize company revenue and competitive returns to investors from mine production activities.

Jan 1, 2005

By M. Vallée

"RÉSUMÉDurant les 10 dernières années, les améliorations dans le contrôle des limites des sautages et les arpentages après l’exploitation ont fourni des informations préalables et post facto sur les limites minières réalisées par rapport à la planification, plus particulièrement pour les grands chantiers exploités par les méthodes chambres vides et sous-niveaux. Cependant, peu de recherches ont été faites pour améliorer la délimitation du minerai, l’estimation des ressources et des réserves, les études de faisabilité et la récupération minière dans d’autres types de gisements. Il faudra d’abord expliciter les impacts des lacunes, en quantité et en qualité, de l’information géologique et de l’échantillonnage sur le rendement de l’extraction. Il faudra également remplacer la notion de « dilution générale » par celles de « dilution » et de « perte de minerai ». Les impacts des lacunes observées sur l’exploitation des gisements d’or filoniens sont démontrés par une simulation basée sur des résultats d’études antérieures à la mine Thompson d’Inco, des impacts financiers de densités d’information moindre et par des analyses des valeurs actualisées nettes (VAN) de deux cas types.Deux gisements similaires, de 3 m et 6 m de largeur et exploités par chambres vides sont étudiés, en prenant pour cas de base la délimitation sur maille de 7,5 m (25 pi.) et en étudiant les impacts des limites moins précises supportées par une maille de 15 m (50 pi.), en assumant que ces imprécisions moyennes de +/- 0,62 m se transforment soit en surestimation (dilution), soit en sous-estimation (pertes de minerai).Les impacts d’information moins précise ont été beaucoup plus forts sur le gisement plus étroit : autant la dilution que les pertes de métal ont diminué les VAN du gisement de 3 m de 39,27 % et 45,41 % respectivement, tandis que les VAN du gisement de 6 m ont été diminuées que de 12,84 % et 11,55 %.Ces impacts des valeurs actualisées nettes diminuées justifient et exigent des efforts plus systématiques pour s’assurer que les travaux de mise en valeur et les études de faisabilité soient réalisés de façon requise pour optimiser l’exploitation et offrir aux investisseurs des rendements compétitifs par rapport à ceux des autres secteurs industriels. ABSTRACTDuring the past 10 years, research work to improve the survey of stope limits after mining supplied useful information, particularly for large open and sub-level stopes, regarding waste dilution caused by differences between final production limits and planned stope limits.However, the efficiency of this information to improve the overall efficiency of the mining process is limited, given that the impacts of inaccurate ore limits leading to dilution (sensu stricto) and ore losses have not been considered adequately. Geological/sampling information should be optimized in terms of quantity and/or quality for the deposit characteristics and the constraints of the mining method used. As industry practice regarding the definition and recording of dilution is flexible and as ore losses frequently are poorly documented, the use of these terms is reviewed.Simulations were carried out on two typical narrow gold deposits, based on an earlier study at Inco’s Thompson mine regarding the impacts of wide to narrow delineation grids using recorded variations of vein geometry. Vertical to sub-vertical deposits of 3 m and 6 m widths mined by long-hole open stopes were considered. Deposits delineated by 7.5 m (25 ft) grids were taken as a base case and the impacts of less accurate limits in conjunction with long hole mining based only on a 15 m (50 ft) delineation grid. The impacts of overestimation (dilution) and underestimation (metal losses) were considered separately, using the average error of +/-0.62 m recorded in the Inco study.The impact of less accurate information was much stronger on the narrower deposit: both dilution and ore losses diminished the net present value of the 3 m wide deposit"

Jan 1, 2005

By S Oliver, D Willingham

"Although a resource model is central to the mineral resource value estimation process (Glacken and Snowden, 2001), creating it is a labour intensive task and in the end it is a limited representation of the actual orebody. Creating this resource model is a labour intensive task that requires inputs from geology, mining, metallurgical and commercial disciplines. It requires thousands of samples from hundreds of drill holes to be verified, grouped in geological domain, interpolated and then valued. Even after all this effort, a model is only an estimation; therefore further significant effort has gone into quantifying uncertainty in the model and subsequently risk around any value estimates derived from the model. Further risks to model quality are introduced through poorly conditioned data or incorrect assumptions.This paper proposes the application of machine learning to automate the resource model development. Machine learning is applied to the traditionally manual tasks of geological formation, domain identification and validation of the block model mineralogy. Through automation the resource estimation process can be accelerated, allowing more drill holes or a larger resource body to be processed in a given time frame, or allowing the process to be more agile to changes in input data and assumptions. A case study based on drill hole data from a Western Australian iron ore deposit (Government of Western Australia, Department of Mines and Petroleum, 2015) is used to demonstrate the application of machine learning in this process.CITATION:Oliver, S and Willingham, D, 2016. Maximise Orebody Value through the Automation of Resource Model Development Using Machine Learning, in Proceedings The Third AusIMM International Geometallurgy Conference (GeoMet) 2016, pp 295–302 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Jun 15, 2016

By F Phillips, E Deucker, J Kato

It is challenging to determine the optimal mining strategy to maximise value when a mine plan includes mineralised material which does not meet the full cost of mining but has value exceeding the variable cost of mining (‘marginal material’). Mining too much marginal material dilutes the operation’s head grade and undermines profitability. Conversely, leaving too much metal behind fails to achieve the full value of the endowment. Finding the balance between the two will maximise value delivered from the asset. This dilemma has traditionally been approached by calculating a suite of cut-off grades to define the grade of material that meets economic targets for an orebody (or zone within) and should therefore be included in the mine plan. A problem with this approach is that individual mining blocks within the zone have different costs, value and confidence levels, with each having economic co-dependencies between them. Blocks of identical grade but different mining contexts will have distinctly different economic outcomes. For example: • a block may be a low-grade increment or shell around a higher-grade stope; • a block may be available to be mined when there is spare mining capacity; or • a block may defer access to significantly higher cash flow material. Each of these circumstances would result in different value from the blocks if included as part of the mine plan. Cut-off grades calculated as averages over zones of material, or in isolation from schedule-based information, are missing the entire mining context that determines the ultimate economic outcome of making a mining decision. There are tools and techniques available to address this for open pit mining, however underground mining has different nuances. There are more intricate economic and physical dependencies between potential ore blocks, and importantly, the decision to leave material in situ can be made at any time. The case study in this paper explores a new methodology for underground mining, targeted towards strategic planning applications. It examines whether the economic logic usually applied via cut-off calculations can be implemented in the schedule so that optimal economic decisions can be made on a block-by-block basis, taking into account the mining context of the block, with the objective to maximise asset value. The results of the case study scenarios in Table 1 demonstrate the magnitude of the potential improvement in NPV that can be attained by a block by block valuation approach

Mar 15, 2021

By G. R. Morin, A. R. Leggett

"In 2010, closure of the Kidd metallurgical plants along with structural changes to the historical ratios of payable metals led to a review of the operating targets at the Kidd concentrator. Previous operating data indicated that there was potential for significant revenue improvements by lowering the copper concentrate grade. An extended plant trial was carried out in 2011 to quantify the revenue impact of lowering the copper concentrate grade from 27% to 25% Cu, as well as identifying the lower practical grade limit. Analysis of plant trial results indicated that the process change increased net concentrate revenue by $2 M to $3 M per year at current metal prices. Increased revenue was primarily associated with higher silver recovery to the copper concentrate while the marginally improved copper recovery was essentially offset by increased zinc losses and concentrate treatment and freight charges.Details of the plant test work results are discussed in this paper along with the financial analysis of the revenue improvements. Key areas covered are major revenue components of the concentrate contracts, validation of revenue improvements through plant testing and sensitivity of the improvements to market and plant variables.INTRODUCTIONThe Xstrata Copper Kidd concentrator commenced operations in 1966 treating ore from the nearby Kidd volcanogenic massive sulphide deposit in Timmins, Ontario (Thompson, Amsden, & Chapman, 1978). Over the years, up to four separate grinding-flotation divisions were in operation with throughput rates peaking at 4.5 million tonnes per year of ore in the mid 1980’s (Kelebek & Francis, 1998). As the mine production decreased and grinding throughput increased operations were gradually cut back and since 1998 two grinding-flotation divisions have been in operation treating Kidd mine ore. One of the idled divisions has been intermittently used for custom milling operations, most recently the Ni/Cu Montcalm deposit, which was milled from 2004 to 2009. Current budget throughput rates, limited by mine production, are 2.4 million tonnes per year of ore grading 1.7% Cu, 4.3% Zn and 55 g/mt Ag. Concentrate production rates are 150,000 tonnes per year of copper concentrate and 155,000 tonnes per year of zinc concentrate. The Kidd mine is the deepest base metal mine in the world with mining operations down to 9600 ft.In 2010 the copper and zinc plants at the Kidd metallurgical site, which previously treated the concentrate production from the Kidd concentrator, ceased operation due to a variety of economic and market factors. Following the metallurgical plant closures the Kidd concentrator products were shipped off site for treatment. The majority of the copper concentrate is now processed at the Xstrata Copper Horne smelter in Rouyn-Noranda, Quebec with the majority of the zinc concentrate processed at Canadian Electrolytic Zinc Ltd. in Valleyfield, Quebec."

Jan 1, 2013

By A. A. Wessels, D. P. Allison

"Mine hoists are built to handle a certain nameplate capacity; they are specified and designed according to the required duty. However, as production capacity increases in other parts of an operation, the hoist capacity can become the critical constraint. Such a situation occurred at Lundin Mining’s Neves-Corvo operation. This paper examines how each component of the existing hoisting system was examined and optimized. Through a combination of engineering study and hoist simulations, the annual hoisting capacity was improved by 24% through increases in payload capacity and available hoisting time combined with a reduction in cycle time, while no changes were made to the hoist motor, drum or headframe. The additional payload capacity was achieved by reducing the mass of the hoist ropes and skips, and improving load monitoring systems. The cycle time was reduced through the shortening of the creep distances and increased availability through the installation of a shaft collar safety platform, alternative guide rope bushes, and superior liners for both the skips and underground measuring flasks. Enhanced cooling of the hoist electrical system was also incorporated to increase hoist availability by reducing downtime during hot summer months. The changes will increase the capacity from the current 4.5 mega tonnes per annum (Mtpa) to a planned 5.6 Mtpa and are being implemented over a 2-year period whilst maintaining the mine production during the upgrade work. INTRODUCTION Neves-Corvo Mine Neves-Corvo is primarily a copper and zinc mine producing copper, zinc and lead concentrates. The operation is owned and operated by Somincor, the Portuguese subsidiary of Lundin Mining. Located in the Alentejo district of southern Portugal, the operation is situated approximately 15 km southeast of the town of Castro Verde, where summer temperatures can reach as high as 45ºC, and approximately 220 km southeast of Lisbon. The principal means of mine access is via a ramp from surface, with the vertical shaft used to hoist ore and waste from the 700 m level, while conveyors descend from the 700 m level to transport ore and waste up from the deeper levels of the mine. The mine is highly mechanized and several different stoping methods are employed, with the most significant being bench-and-fill and drift-and-fill. The Neves-Corvo mine currently exploits five orebodies: Neves, Corvo, Graça, Zambujal and Lombador for copper and zinc-lead ores which are processed in one of two plants. All the orebodies are currently exploited over their full elevation with the exception of Lombador which is only mined down to the 220 m level, approximately the top 50% of the orebody, known as Lombador Phase 1."

Jan 1, 2019

Breakwater Resources Ltd is a Canadian base metals producer with Cu-Pb-Zn operations in Canada, Honduras, and Chile. Two of its operations contain economical gold levels which are recovered in both gravity and flotation concentrates. The gold payable terms in zinc concentrate are poor when compared to gold concentrates or copper concentrates and various flow sheets have been evaluated by Breakwater staff to maximise gold reporting in higher value products. The Myra Falls mine in British Columbia recovers coarse gold in the grinding circuit, part of which is upgraded and sold as a gravity-gold concentrate with the balance being directed to the copper concentrate. A sampling survey showed that there was potential gravity-recoverable gold in the copper regrind circuit. Installing a gravity concentrator in the copper regrind circuit increased the gold grade and recovery in the higher revenue copper concentrate and reduced the quantity reporting to the less well paid zinc concentrate. The El Toqui Mine in southern Chile has distinct high-and low-gold orebodies which are campaigned separately through the flotation plant. The high gold zone yields both a gravity concentrate and an unusual gold flotation concentrate. The gravity concentrate undergoes intensive cyanidation and electrowinning on-site to produce dore, while the fl otation concentrate is sold to gold producers. The zinc concentrate contains signifi cant gold values. The paper describes efforts over the past few years to improve gold returns at Breakwater's operations and highlights the different approaches dictated by the mineralogy of the gold occurrences at these two operations.

Aug 1, 2010

By M T. Grigoleit, M S. Schneider

The iron ore industry in Australia has, in recent years, experienced an unprecedented growth phase. But now that major expansions are moving into the operation phase, new challenges have emerged. Whereas initial planning may involve a few modelling studies, ongoing performance monitoring and improvement requires a different, more intense approach. This is especially important in the face of changing factors such as commodity prices, exchange rates and labour markets. Response time is key. As a mining operation proceeds from initial planning to daily operations, the time window for analysis shortens, going from months to weeks to days as the business matures.Simulation models and analysis tools are typically built and run by specialists in the planning phase, but then what? The investment has been made, but realised only once. What if further analysis could be carried out in-house, re-using existing models using up-to-the-minute data? Can we create virtual mines that run in parallel to live operations that allow computers to identify areas of a value creation or operational improvement? These questions can be answered by the innovative application of big data, simulation and predictive analytics. The future will be having this all integrated into one platform that offers, for the first time, an opportunity for non-experts to apply existing modelling and analysis assets – combined with live data – to deliver support for continuous improvement, and the ability to respond quickly to external changes in the best possible way, before they become big problems. These techniques will represent a step change in the ability for operations to maximise efficiency and will underpin the intelligent operations of the future. These issues are addressed in this paper.CITATION:Schneider, M S and Grigoleit, M T, 2015. Maximising productivity through big data, simulation and predictive analytics, in Proceedings Iron Ore 2015, pp 475–480 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 13, 2015

By Lock PR

The Silver Swan nickel mine is located at the Black Swan Nickel Project, 53 kin north east of Kalgoorlie, Western Australia. The Silver Swan orebody is a massive sulphide nickel deposit dipping 70¦ east with an average in situ grade of 14 per cent. Mining of the massive orebody is by Mechanised Ramp Cut and Fill (MRCF). A mining recovery of 98 per cent and minimising dilution are primary goals in extracting the high-grade ore. Placing a distinguishable marker bed (working platform) on rock fill was identified as a key method to achieving these goals. Gravel from a pit located onsite was considered the most suitable material for the marker beds. Research undertaken to design the marker beds using the gravel revealed conventional methods used in mining would not suffice, but that road stabilisation methods could be a viable alternative. Trials used a road recycler to mix cement and gravel in situ and several test beds were constructed on the surface to determine the final design. The trials attempted to replicate a marker bed's life cycle of construction and placement and mucking of ore from the marker bed.

Jan 1, 1998

By A Singh, C Da Corte

Banded Iron Formations or more commonly known as BIF are sedimentary rock formations with alternating silica-rich layers and iron-rich layers that are typically composed of iron oxides (hematite and magnetite), iron-rich carbonates, and/or iron-rich silicates. Considering the depletion of highgrade iron ore reserves in South Africa, there is a need to maximise resource utilisation through the exploitation of sterile resources in particular BIF material which makes up greater than 65 per cent of current reserves. BIF, like most resources, is non-renewable and the deposition of BIF is thought to have come about by the reaction of Fe2+ ions in the ocean water with dissolved oxygen billions of years ago. BIF ore derived from the Limpopo region in South Africa (SA) located in the Penge Iron Formation is according to Cairncross, Kramers and Villa (2018) equivalent to that contained within the Asbestos Hills Iron Formation of the Transvaal Supergroup in the Northern Cape, SA. Considering that these are one of the largest iron ore deposits in SA, the case study involved mineralogical characterisation followed by beneficiation of BIF from these two regions to ascertain the comparability. Coarse and fines gravity separation comprising of Heavy Liquid Separation/Dense Media Separation on the +1.18 mm size fraction and shaking table on the -1.18 mm size fraction was conducted to ascertain whether an on-grade product or blended feedstock could be produced. The Limpopo mixed and Northern Cape conglomerate BIF samples achieved similar overall responses due to the conglomerate sample containing 15.3 per cent additional -1.18 mm fines. A combined coarse and fines product grading at 60 per cent Fe could be achieved at a yield and recovery of 43.9– 53.0 per cent and 62.2–63.8 per cent respectively. Increasing the grade to 63 per cent Fe reduces the overall recovery by 13.3 per cent. At the higher target grade, the contaminant specifications could be achieved for both samples. The Northern Cape laminated BIF sample is the most promising of the three samples studied. At the two iron target grades overall yields and iron recoveries of 72.9–65.4 per cent and 85.2– 80.2 per cent was achieved. In both instances the silica grade exceeded the product specification, however if the silica content is the driver the target iron grade should increase to 63.32 per cent. This will result in a minimal decrease in recovery of 0.4 per cent. The promising results of this study indicate that coarse beneficiation of BIF material is possible. These ore types could be blended with superior grade products to improve overall yields and recoveries or sold directly at a 63 per cent Fe product grade whilst sacrificing 0.4–13.3 per cent recovery.

Nov 8, 2021

By Gareth Barnes

Traditional approach to improvement is driven by good ideas from good people, but whilst the business case may sound good, when the project is complete, we often have not delivered on expectations.  Why not? The best way to successfully predict the outcomes of an improvement effort in a complex process is through using statistical modelling, which considers the impact of uncertainty within interacting processes.  Applying Theory of Constraints in a model helps leaders to quickly determine: Where the constraining process(es) is/are Where improvements will add the most value How much improvement should be targeted - before the next constraint takes over The confidence level of achieving a given target, which gives us a clear pathway to improvement. This paper presents an analysis of statistical modelling applications at Vale’s Manitoba Operations to achieve the 2025 targets. Using statistical modelling of the Business Structure, the team identified a series of process improvements through a Theory of Constraints Analysis. Value Stream Maps (VSMs) were used to define the required data, apply statistical modelling, and conduct training sessions enabling the Manitoba team to identify the constraining influences. Scenario testing in the Statistical models helped identify the Hierarchy of Constraints and specify the pathway to improvement. How to Improve a Business Video link https://vimeo.com/344418155

May 4, 2025

In the minerals industry allocating capital for setting up a new project or for upgrading an existing facility usually requires that a compromise be found between the initial cost of equipment, its operating performance and on-going operating costs. To maximise the return on the investment usually requires that various possible combinations and layouts of equipment be assessed. This task is both difficult and time consuming. Computer simulation can be used as a means of determining the expected operating performance of a range of alternate equipment configurations. Simulation is a particularly important technique for analysis as it is one of the few approaches that allows the analyst to take into account the variability inherent in a mining process. While computer simulation is a well established technique its use, until recent years, has been limited to large organisations with access to substantial computing facilities. However, with the current availability of low cost computing platforms combined with easily understood animated displays, simulation is now becoming more widely used across the industry.

Jan 1, 1990

By A A. Latscha, D O’Connor

Increasing orebody complexity, restrictions in ground access, and longer lead times for disturbance approvals, have generated the need for the Resource Development Team within Rio Tinto Iron Ore (RTIO), to explore optimised drill design techniques that deliver resource conversion value while maximising program outcomes. In response to this challenge, the Team initiated a case study to produce an AI assisted/designed drill program using a non-machine learning AI. The case study involved the assessment and implementation of an AI generated drill program at one of RTIO’s Pilbara iron ore deposits, located in the Hamersley Province of Western Australia. The Mineral Resource is currently classified as 100 per cent Inferred. Access constraints inherent to topography, and the presence of exclusions zones have prevented adequate drilling coverage, resulting in lower resource confidence and a poor definition of the orebody extents and geometry. The drill campaign, planned in Q1 2023, needs to consider access constraints, complex topology and the limitations related to additional ground clearance, while addressing the requirement of improving orebody knowledge. The drill plan had to address two objectives. The first and main aim of drilling was to upgrade the Resource Classification to allow for possible conversion to Ore Reserve. The input for this objective was a volumetric representation of the areas currently not meeting pre-defined quantitative Resource Classification upgrade criteria. The second objective was to better define the orebody extents and geometry. For the second objective, the input to the drilling optimiser was a volumetric representation (blocks) of the areas of high uncertainty in the mineralisation/waste boundary, which were defined using an indicator conditional simulation technique. The drilling optimiser output was a range of compliant drill plans. A set of KPIs based on economic and orebody knowledge criteria were used to assess the plans and to select the most optimal drill design to be drilled in 2023. The geology and management teams were able to make better informed, objective decisions using the trade-off between cost and orebody knowledge gained. As part of the assessment, the AI generated plans were compared to our current planning practises. The AI assisted plans, when gauged against the project KPIs, showed clear and measurable improvements in both meeting project objectives and in managing operational risk.

May 24, 2023

By Rob Morrison, Andrew Scott

"Long before a modern mine commences operations it has already become a wealth of information. After start up, it can generate enormous quantities of data - especially with semi-automated data acquisition by instrumented mine equipment.However, much of this data is of limited use for evaluation of (potential) performance unless it links in some way to the site business model.An underlying reason for this waste of data is that the different cultures, financial, technical, community, environmental, etc, not only have many areas of interest but also have very different conceptual models by which they evaluate performance.It is too ambitious to attempt to bring all of these cultures together - in a single step.However, the success of the Mine to Mill - project has demonstrated that substantial operational value can be added by using a more integrated approach to comminution. The next logical step is to integrate measurement and then to track performance from ore body model to saleable product and waste disposal. From resource to product also represents a path from very sparse, highly variable data to much more detailed measurement and more representative sampling.However, in both cases the data collected is strongly focused on the technical requirements - not on the business model.This paper considers how to define at least some of the key decision points in terms of some case studies.Performance data from many areas might be used to derive simple models which can then be used for forecasting and optimisation of planning."

Jan 1, 2003

By A Kleinitz, J Halilovic, K Trappitt

Mine operators use grade control to determine the destination of each block of material in the mine. In polymetallic mines, grades are best expressed in dollars: the Net Smelter Return, NSR, per tonne. To estimate NSRs, geologists working on grade control develop models for each geometallurgical domain in the mine. These models may incorporate observations on the mineralogy and grain sizes of the material being examined. The site’s mill operators contribute to the models by providing geologists with statistical analyses that relate assay results and mineralogical compositions to metallurgical parameters, such as the rates of recovery of each economic metal to each of the concentrates produced, and the compositions of those concentrates. The team responsible for sales and marketing of the site’s products contributes to the NSR models by providing details of the costs of shipping concentrates to smelters and refineries; and by providing figures that are specified in the smelter contracts, such as the payability of the metals in each concentrate and the fees charged by the smelter. The mill operators also provide, for the NSR models, equations to estimate the rates of recovery of deleterious materials to each concentrate. Deleterious materials comprise mostly halogens and amphoteric elements, both of which reduce the efficiency of smelters. Furthermore, deleterious materials such as antimony and arsenic may be poisonous to people and to the environment. The sales and marketing team provide specifics of the penalties that smelters impose upon deleterious materials. These penalties may reduce NSRs by tens of percent, possibly to levels below the cut-off grade. Thus, in the blocks that are subject to grade control, mine geologists monitor not only the concentrations of economic metals, but also the presence and abundance of deleterious materials. The preparation and maintenance of models, to estimate NSRs and to assess changes in the levels of potentially toxic materials to be mined, requires close and continuing consultation between corporate departments. There must be strong communication of mine geologists with the mill operators; with the people who market the mine’s concentrates; and, should there be a risk of encountering toxic levels of deleterious materials, with the mine’s health, safety and environmental officers. This co-operation could require radical changes in the structure of many organisations. However, experience suggests that such changes can significantly improve the profitability of a mine.

Mar 22, 2022

By Rob Morrison, Andrew Scott

"Long before a modern mine commences operations it has already become a wealth of information. After start up, it can generate enormous quantities of data – especially with semi-automated data acquisition by instrumented mine equipment. Much of this data is of limited use for evaluation of (potential) performance unless it links in some way to the site business model.An underlying reason for this waste of data is that the different cultures, financial, technical, community, environmental, etc, not only have many areas of interest but also have very different conceptual models by which they evaluate performance.It is too ambitious to attempt to bring all of these cultures together – in a single step. However, the success of the Mine to Mill ™ project has demonstrated that substantial operational value can be added by using a more integrated approach to comminution. The next logical step is to integrate measured data and then to track performance from ore body model to saleable product and waste disposal.The path from resource to product also represents a path from very sparse, highly variable data to much more detailed measurement and more representative sampling. However, in both cases the data collected is usually strongly focused on the technical requirements – not on the business model.This paper emphasises the difference between data and information. There is considerable potential for confusion between the two as both data and information are often expressed as numbers. For the purpose of this paper, data and information are distinguished by their uses.A data point (or datum) is a measurement. By way of contrast, information provides a basis for decision making."

Jan 1, 2003

The mining industry continues to faces significant challenges due to increasing resource constraints (quality of ore bodies, water, energy, human resources) and increasing license to operate requirements (safety, health, environment, location) from society, employees and shareholders. Technology advancements and hence research are necessary to ensure that the industry remains viable in this changing environment. Collaborative research is an important part of a company's research portfolio and offers the opportunity for the industry to work on generic issues that it is facing. Obvious benefits include the reduced cost to individual companies by sharing the costs, the opportunity to leverage government funding and the opportunity to conduct longer term projects resulting in skills development (PhD and MSc). Limitations of collaborative research include the reduced focus on company specific issues and the loss of competitive advantage from owning the outcomes of the research. The challenge for researchers and research managers is for them to demonstrate the value derived from longer term, pre-competitive collaborative research. The competitive advantage is not necessarily derived only from the outcomes of the research but rather from the company's ability to direct the research, translate the generic research outcomes to address company specific issues and to implement improvements at its operations. Implementation remains the greatest challenge. In this paper, case studies of selected collaborative research projects are presented to demonstrate key success factors required for implementation of research outcomes. This is an ABSTRACT ONLY. A full-length paper was not prepared for this presentation.

Sep 13, 2010

By B Murphy, S O’Connell, J L. Heath

In the 1989 best-seller The 7 Habits of Highly Effective People, the author, Stephen Covey, highlights the importance of maintaining not only ‘production’, but also, ‘production capacity’. When operating a modern flotation concentrator, production is often measured in terms of concentrate tonnage, tonnes milled and plant utilisation. There are very few metrics that focus directly on flotation equipment condition in relation to performance, which is analogous to Covey’s production capacity principal. It is evident on many mine sites that flotation equipment condition is not monitored on a proactive basis and that the prevailing culture is to wait for a failure, before addressing an issue.This paper discusses examples of how poor equipment condition can lead to production loss through poor metallurgical performance. Actual examples are given where these problems have occurred in operating plants. An outline is provided on how metallurgical and maintenance departments can work together to protect production capacity and gain more from existing equipment.CITATION:Murphy, B, O’Connell, S and Heath, J L, 2014. Maximising value through maintaining your flotation equipment, in Proceedings 12th AusIMM Mill Operators’ Conference 2014 , pp 71–76 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 1, 2014

By Edgard Atencia, Manuel Vega

Sociedad Minera El Brocal se dedica a la exploración, desarrollo, explotación y tratamiento de minerales polimetálicos. Con el objetivo de incrementar la producción, se buscó maximizar la recuperación de los pilares dejados post minado de tajos primarios, utilizando equipos ITH con sistema Wassara, el cual permite tener mayor alcance y menor desviación que los sistemas con martillo en cabeza (Top Hammer).

Sep 30, 2022