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By C Sylvestre

Leaders have invested heavily in traditional safety management to improve safety performance over the years. This primarily involved: • fixing the environment (eliminating the hazard) • improving the system (more/less rules, procedures etc) • making safety more conscious (more/better interactions about the importance of safety). These approaches have helped improve safety performance significantly during the last 50 years and will continue to play a role in the future. Although these approaches may be part of an overall solution, they are not enough to prevent many incidents. Today, these three approaches are used more than before, and are used better than ever before. Yet, workplace fatalities in Australia have stagnated from 2013 to 2019, as have the number of incidents, even serious ones. In the USA, workplace fatalities have increased by 15 per cent in the same period.

May 5, 2022

Although AustraliaÆs coal mining industry is currently experiencing a pleasing period of price relief, long-term trends toward lower real prices will surely continue. Higher price levels attract expansion by existing operators and market entrance by new operators. History clearly demonstrates the relentless long-term march toward ever lower real prices. Therefore, the need for economic returns applies constant pressure to improve productivity. To be sustained, high productivity requires a systematic response based on a solid understanding of critical productivity determinants. The most powerful determinant of productivity is now widely understood to be workplace culture. Culture largely comprises a combination of behaviours, symbols and attitudes. This paper will examine and review scienceÆs latest discoveries in human behaviour. It will provide a proven, practical framework for understanding behaviour and applying this knowledge. Significantly, it will highlight why conventional approaches toward improving productivity often provide disappointing economic returns. The modern understanding of behaviour factors will cover coal face operations. More importantly, because executive and managerial levels in coal mining have significantly greater impact on industry and mine productivity the paper will concentrate on leadership. Particular emphasis will be placed on use of modern systems and in particular use of what are by far the most powerful drivers of behaviours û measurement, analysis and reporting systems. The paper and presentation will show how conventional systems rooted in antiquated American legislation from the early 1900s stifle productivity improvement and drive suboptimal and even counterproductive behaviours. These commonly used systems will be compared with accurate and effective modern methods for assessing performance to improve productivity. These principles are proven in all industries and effective application in mining will be highlighted. Actual results will be used to demonstrate practical approaches successfully applied in both metal and coal mining in Australia and overseas.

Jan 1, 2005

By D R. Chalmers

Coal dust explosions have occurred in coal mines across the world. The Mitsui Miike Coal Mine disaster in 1963 was an example of how this hazard was not managed effectively, resulting in the loss of 458 lives and hundreds of people sustaining permanent brain injury from carbon monoxide poisoning. Management of the risks for this hazard have been well documented and have been implemented in modern coal mines. A recent trend in some mines has seen the abolition of barriers on roadways on the basis that the risks are being managed by the current controls. These controls include stone dust application, trickle dusters, dust analysis and dust removal. This paper explores the science behind such controls and questions the need for barrier protection on belt roads.CITATION:Chalmers, D R, 2013. Cybulski revisited - Lessons on dust, in Proceedings The Australian Mine Ventilation Conference , pp 165-168 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 1, 2013

By R Long

The founder of social psychology is sometimes identified as Kurt Lewin. In a 1947 article, Kurt Lewin coined the term ‘group dynamics’. He described this notion as the way that groups and individuals act and react to changing circumstances. Lewin theorised that when a group is established it becomes a unified system with unique dynamics that cannot be understood by evaluating members individually. The discipline of social psychology really emerged out of World War II and tackled questions associated with human judgement and decision-making by the Nazis. For a comprehensive look at the development of social psychology look at Abelson, Frey and Gregg (2004).Social psychology is concerned with the way social arrangements affect human judgement and decision-making. What the author has done is apply the knowledge of this new discipline to an understanding of risk, safety and leadership. This paper will explain some of the developments in social psychology, such as the discovery of the bystander effect, Groupthink, bounded rationality, heuristics, risk homeostasis and the Milgram effect.The social psychology of risk tackles the way decisions are made about risk in their social context. Unless organisations understand that decision-making is socially conditioned, they are unlikely to be able to tackle the complexities of culture change or the development of risk maturity.The paper will offer a new understanding of why people do what they do, how risk makes sense and why a ‘dumb down’ approach to safety is dangerous. A model will also be presented that shows the pathway to risk maturity.CITATION:Long, R, 2016. The social psychology of risk, safety and leadership maturity, in Proceedings Seventh International Conference and Exhibition on Mass Mining (MassMin 2016), pp 31–42 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2016

By S M. W Rajaratnam, P Varma, T L. Sletten

Mining employees undertaking shift work are at considerable risk of experiencing sleep disturbances and circadian rhythm disruptions. In the complex, high-risk environment of mining, these sleep and circadian disruptions lead to adverse impacts on employee health, alertness and safety. Evidence-based tools that effectively target improvements in sleep health amongst shift workers are needed. Variability in work hours and individual differences in the response to shift work mean that a ‘one-size-fits-all’ solution is often insufficient in complex work environments. Currently no interventions provide tailored support for shift workers based on their rosters, personal commitments and sleep habits. Existing technologies, such as smartphone applications and watches, allow sleep monitoring, but their strategies are targeted towards night sleepers, which does not translate to shift work contexts. To address this, our team has developed an innovative digital tool that implements biomathematical models to provide automated, personalised sleep and circadian intervention strategies to optimise sleep, alertness and performance during shift work. The tool uses mathematical models of sleep and alertness regulation that provide physiologically optimal times for an individual to sleep when experiencing circadian disruption. This program of work included co-designed development of a world-first app with shift workers and the examination of the preliminary efficacy of the intervention for improving sleep, alertness and performance.

Apr 16, 2024

By C Sylvestre

For the last 50 years, traditional safety management has improved safety performance by: • Fixing the environment (eliminating the hazard). • Improving the system (more/less rules, procedures etc). • Making safety more conscious (more/better interactions about the importance of safety). Although these approaches certainly have merit, and may be part of an overall solution, they are not enough to prevent many modern-day incidents. Today, these three approaches are used more than before, and are used better than ever before. Yet, workplace fatalities in Australia have stagnated from 2013 to 2019, as have the number of incidents, even serious ones. In the USA, workplace fatalities have increased by 15 per cent in the same period.

May 5, 2022

By B Yeganeh, A Sam, A Kohsari

The base of separation at Gol-e-Gohar iron ore plant (Sirjan in the south of Iran) is magnetic separation after milling. Magnetic separation in the plant is divided into two parts: dry magnetic separation and wet magnetic separation. Sixty-five per cent of the plant production belongs to the dry magnetic separator section. Therefore, investigation of this part of the plant is necessary. Prediction of plant production is one of the most important subjects in mineral processing plants. That means, before feed enters the plant, specification of production has been calculated with laboratory methods. The purpose of this paper is the prediction concentrate quality has achieved from the dry magnetic separator. The content of iron in the final dry concentrate will be predicted, with laboratory, pilot and modelling methods, before feed enters the plant. Different variables are used in this approach, which consist of: speed of the first dry magnetic separator (rougher), speed of the third dry magnetic separator (cleaner), iron content in plant feed, size of 80 per cent passing of feed, size of 20 per cent passing of feed and iron content in pilot dry magnetic separation concentrate that performs in a standard manner. The artificial neural network is used for modelling and one of its branches is the radial basis network (RBN). Iron content in magnetic separating concentrate in plant will be introduced as the target and will be calculated with the RBN method. In the RBN method, a set of data enters to neural network and they will be trained and simulated. Finally, the target will be predicted. Ultimately, the original target (actual iron content) and the predicted target (predicted iron content) compare and error of them will be calculated. The obtained result is acceptable and satisfactory.

Jan 1, 2007

Risk management has become an essential tool for mining companies to ensure their projects are well-managed and profit expectations are achieved. Risk management has also become a mandatory corporate governance requirement in Australia for publicly listed companies and equally important to attract investors. This paper provides a brief overview of the essential tools needed to implement a practical risk management framework to comply with the internationally recognised ISO 31000:2009 risk management-principles and guidelines from the perspective of small or soon to be producing mining companies. To?successfully?deal with the unknown and to manage the opportunities and risks involved with a mining project requires a clear understanding of the basic risk management principles. These include how to develop a project risk register, how to develop a project risk treatment plan and how to manage and monitor project risks to take full advantage of the opportunities presented.The first step is to identify and fully appreciate the risks that face a mining project. There are many risk identification methods that can be used including checklists, brainstorming and hazard and operability (HAZOP) studies. These often lead to a telephone book full of risks which are near to impossible to manage. A risk library specifically designed?for mining?projects containing no more than 100 risks will cover the major showstoppers, is practical and can be readily implemented and successfully managed.A risk framework also needs to be established which is compatible with the companyÆs structure and objectives. Once each risk has been assessed in regard to consequence and likelihood and the risk control systems are in place they need to be assigned to the responsible manager. The extreme or high risks will require a risk treatment plan to be developed. Risks will change during the life cycle of a mining project. Hence, a reliable monitoring system is also required for compliance.CITATION:Jones, J A, 2012. Mine project risk management, in Proceedings Project Evaluation 2012 , pp 117-122 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 24, 2012

The key issue which determines the use of imaging for explosives and mining research is the question - `What information will I gain by using imaging technology?' This paper will address that question from the point of view of a researcher and cameraman working in industrial imaging and photography. The paper will establish a common set of reference standards for high speed imaging and photography which researchers can apply when deciding which type of imaging technology is appropriate. It will present an overview of current image analysis technologies and practices in use across a range of appropriate scientific fields and draw lines of commonality of approach between these fields and the field of explosives and mining analysis and research. Further to this, the paper will examine the different technologies from an image quality reference point, ease of operation, cost, and reliability parameters. Finally this paper will present an argument for the hybridisation of established and new technologies which could provide a more beneficial approach to the use of imaging as a tool of research and analysis in the explosives and mining industries. This will include a novel approach to high speed filming and analysis in the field which should deliver high quality images in a time frame which is more appropriate to urgent action and solutions.

Jan 1, 1995

By B N. Noller, J C. Ng, S L. Bruce

Mining activities can result in the transfer of harmful elements, including arsenic and lead, into the environment. In Australia, one of the potential future uses of rehabilitated mine land is to stock grazing animals. Elemental uptake is dependent on bioavailable fraction for adsorption upon exposure. Bioavailability data are generally lacking in order to provide realistic health risk assessments relating to harmful elements from mine tailings in Australian conditions. Another key component of risk assessment is the ability to estimate a realistic exposure, or dose rate, of the tailings to the grazing cattle over a set period of time. Hence, we aimed to conduct grazing trials directly on rehabilitated tailings facilities in order to provide valuable in situ information on heavy metal dose rates and associated accumulation. For the laboratory-based evaluation of comparative bioavailability, groups of cattle were fed five days a week on a normal diet spiked with mine tailings or soluble pure salts of target elements (eg sodium arsenate, sodium arsenite and lead acetate) for about eight months. For the field validation, cattle were allowed to graze directly on rehabilitated tailings facilities over a similar length of time. Blood and a biopsy of the muscle and liver were periodically collected to monitor arsenic accumulation. At necropsy, blood, muscle, liver, kidney and other saleable tissues were measured for arsenic concentrations. Although this study was focused on arsenic, lead and other metals were also measured. Predictive models for arsenic and other metals have been established to calculate the maximum grazing duration without the risk of exceeding specific food safety guidelines. The outcome of this study is a predictive model for maximum beneficial use of certain rehabilitated tailings for cattle grazing where grazing activities do not impact on the integrity of the tailings dams.CITATION:Ng, J C, Noller, B N and Bruce, S L, 2014. A predictive model for beneficial use of rehabilitated mine tailings for grazing cattle after mine closure, in Proceedings Life-of-Mine 2014 , pp 563–572 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 16, 2014

By Lewis RW, Tullemans FJ, Gallo JB

Gold mineralization at Kidston occurs in a semicontinuous zone near the margin of a large, late Palaeozoic breccia pipe. The pipe is ovoid in plan, funnel-shaped in cross section and straddles a contact between Proterozoic metamorphic and granitoid rocks which are intruded by a swarm of late Palaeozoic acid dykes. Rock fragments within the breccia pipe reflect the enclosing country rocks and mix in various proportions to form gradational lithological domains. Most of the gold is free and is located in the breccia matrix and in a set of inwardly dipping sheeted quartz veins which kink around the pipe margin. Sulphide minerals, dominantly pyrite, occur as disseminations in the breccia matrix and as aggregates in the cores of quartz veins. Hydrothermal altLration is pervasive within the breccia and is most intense in areas with the highest percentage of acid dyke fragments. Sericite and carbonate are the main alteration minerals. An empirically developed genetic theory for the formation of the breccia pipe and attendant mineralization involves magmatic and post-magmatic processes associated with the intrusion of a granitoid body to a shallow level in the crust. Economic evaluation of the deposit relied heavily on the results of diamond drilling. Both polygonal and geostatistical reserves were calculated and found to be in close agreement. Geostatistical reserves are considered to more closely reflect the tonnes and grade achievable during mining. Daily geological mine routine is strongly biased towards grade control allied with the practical aspects of open-pit mining. Tonnage/ grade correlations between ore blocks geostat- istically generated from exploration diamond core results and ore blocks generated from high

Jan 1, 1986

By J Tibbett, A Colebourn, B Hebblewhite, F Suorineni

The concept of Big Data refers to data sets that are so large, variable and/or complex that traditional data processing applications struggle to integrate the data for effective investigation, analysis and value generation. With advances in sensor technology and smarter equipment, the mining industry is experiencing Big Data, and in a different way to how the intelligence and marketing communities experience Big Data. Future mining will bring larger, more complicated and diverse data sets increasing the strain on traditional data integration and investigation techniques. Block caving is an important mining method for the extraction of massive, low-grade ore deposits due to its low operating cost and high production potential, given the right orebody geometry and ground conditions. This paper focuses on block caving due to its increasing popularity and importance in the future economic extraction of multiple commodities. The block cave mining system (BCMS) is a complex interrelation of factors, and due to the reliance on natural processes within the system, it is one of the least understood mining methods. Obtaining information on the factors within the BCMS generates large, complex data sets on various time scales. Each sensor network within the BCMS combines spatial and temporal information with tens to hundreds of recorded parameters. Data sets are quickly moving from multidimensional to n-dimensional. Optimisation of the BCMS is only possible through a holistic analysis approach, thus involving the integration of multiple, diverse, n-dimensional data sets (Big Data). This paper presents a current example BCMS Big Data situation involving 12 sources of information with differences in volume, data format and frequency of data generation. This suitability of virtual reality scientific visualisation (VRSV) as a solution to BCMS Big Data interpretation difficulties is then discussed. These 12 data sets can be effectively integrated using VRSV for intuitive and accelerated investigation of the BCMS. Potential future Big Data within the BCMS is presented involving 20 sources of information resulting from our increased need for monitoring and advancements in technology. Current methods of defining queries may not be suitable within these future complex, multidimensional data sets, and the potential of artificial intelligence algorithms within this system is discussed. These advancements in technology and machine learning lead to the requirement of live data acquisition and analysis. VRSV is identified as a suitable technology to satisfy the needs of real-time insight into the performance of these future caves for optimised management and reduced risk.CITATION:Tibbett, J, Suorineni, F, Hebblewhite, B and Colebourn, A, 2015. Virtual reality scientific visualisation – a solution for big data analysis of the block cave mining system, in Proceedings Third International Future Mining Conference, pp 109–116 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 4, 2015

By M R. Asef

Although generation of environmentally harmful hydrogen sulfide is considered to be related to sour gas fields, sweet gas reservoirs and waste fluids, travertine springs and geothermal fields may also produce acid gas (H2S and CO2) under certain conditions. The potential parameters influencing such a possibility need to be fully investigated to evaluate the extent of the consequences and predict hydrogen sulfide generation accordingly. Reports on hydrogen sulfide production at different regions and fields were gathered worldwide for the cases when some of them did not have such a problem previously. In order to inspect different aspects of these case studies, some other regions with no hydrogen sulfide content were selected as control. In all cases water samples were taken carefully for chemical analysis in the laboratory. Besides, mineral compositions were characterised in some cases for better evaluation. In order to give a thorough prospect of hydrogen sulfide production, a geochemical model was prepared. In situ engineering geological conditions, especially pressure and temperature, were assigned in the model to investigate the possibility of H2S generation using PHREEQC software. The results of modelling revealed that although many similarities existed between mineral compositions of the cases, certain formations were particularly prone to hydrogen sulfide generation. For better evaluation, important exchangeable cation ratios such as potassium/sodium, calcium/magnesium and ion proportions like sulfate and chloride were calculated as trends of the formations. As expected, the model could successfully monitor a higher ratio of SO42- and Cl- in potential H2S generator formations. Wide variation in percentage of HCO3- was considered as a secondary observatory parameter for better estimation. In addition, it was noticed that higher anion content created an environment ready to absorb any cations and this makes H2S generation easier. Finally, using correlations between predictors and estimators for low depth and deep samples defined the degree of effectiveness for every sample.

Sep 26, 2011

"Geometallurgy is a discipline that seeks to improve the sustainability of the extraction of metals and minerals by promoting the smarter use of non-renewable resources, better energy efficiency and greater use of renewable energy. To achieve these goals, development of innovative technologies and approaches are being developed along the entire commodity value chain, starting with exploration and extraction and extending to reuse and recycling. This paper discusses the geometallurgy of industrial minerals with special emphasis on kaolin, a versatile industrial mineral applied in ceramics, paper, paint, plastics, rubber, pharmaceuticals, cosmetics, ink, sealants, adhesives, sanitary ware, glass fibre, toothpaste, animal feed etc. Aspects of kaolin extraction in south-west UK are analysed from a geometallurgical perspective. While geometallurgy already features in kaolin extraction, its role can be significantly expanded by combining advanced in-pit characterisation and orebody modelling with integrated planning and control of the refining and calcination process. This paper highlights the importance of innovation in realising the full potential of geometallurgy.CITATION:Glass, H J, 2016. Geometallurgy – Driving Innovation in the Mining Value Chain, in Proceedings The Third AusIMM International Geometallurgy Conference (GeoMet) 2016, pp 21–28 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Jun 15, 2016

The organisers of this function have suggested that this presentation should accomplish the following broad goals:set the technical tone for the conference to follow, implying some discussion of the æstate-of-the-artÆ of reserve estimation; and raise some current and common problems or deficiencies in our art in order to be thought provoking. As an engineer it is always easier to raise problems than to solve them with state-of-the-art. Consequently, I have had to limit the extensive list of problems that could have been discussed within this presentation. In regard to the state-of-the-art, this presentation will not be an esoteric discussion of the latest statistical estimation processes, although I intend to challenge those with skills in that area to address some of the thought provoking issues later on. The subtitle of the paper was established after reading an excerpt from æLife on the MississippiÆ by the American humorist Mark Twain in which Twain observed that the Mississippi River had become shorter during his working period on the River due to natural cut-offs and man made channels. Projecting into the future, he calculated that by now, Cairo, Missouri and New Orleans, Louisiana would become a single city with one mayor (the two cities are still separated by some 500 air miles). As a moral to this story Mark Twain observed that one can obtain: æwholesale returns of conjecture out of such a trifling investment of factÆ.

Jan 1, 2000

By D Misra, R Ganguli, S Bandopadhyay

The objective of this paper is to assess the accuracy and applicability of recent state-of-art methods such as the machine learning algorithms (MLA) for mineral resource estimation. Conventional methods such as geostatistics have been predominantly used in the mining industry for this purpose with varying success. Recent advances in the use of MLA have provided a fresh approach to obtain improved accuracy in the estimation of mineral resources. Two MLA methods: the neural network (NN) and the support vector machine (SVM) have been used to estimate a polymetallic ore deposit in Alaska.The general characteristic of SVM and NN emphasises the fact that they can approximate any multivariate non-linear relation among variables. Although neural network models are able to capture the nonlinear spatial relationships that may be present in the data, they are usually difficult to optimise under sparse data settings. Of the various NN alternatives, despite their effectiveness, the model selection and estimation process is typically difficult as it involves solving complex integration and optimisation of parameters. In support vector modelling (SVM), estimating of parameters involves optimisation of a convex cost function. The working principle of SVM makes it robust against noisy and extreme value data. At the same time, it can capture the spatial distribution of ore grade more effectively with careful modelling and selection of SVM parameters.The outcome of the MLA methods were compared to those of the geostatistical ordinary kriging (OK) application to study their generalisation ability. The comparison was made using the following goodness of fit criteria: mean-squared error; mean absolute error; mean error; and coefficient of determination. The results indicated that the MLA methods may improve the predictability of ore deposits and thereby reduce the inherent risk in mineral resource estimation.

Sep 26, 2011

By V Srinivasan, P Knights, C T. Farrelly

By 2025, with the widespread industry adoption of remote operation centres and advanced analytics, mining companies will find themselves making better, more informed decisions across the value chain. Process automation will drive significant business integration and reorganisation. Better collaboration between functions will make cross value chain optimisation a reality. Wherever possible decisions will be automated, based on analytical models and embedded in an enterprise decision management (EDM) architecture. This will take care of many of the minor day-to-day or the minute-to-minute decisions that consume operators and managers today. More flexible information technologies and architectures derived from the extensions to Web 2.0 and service oriented architecture (SOA) will solve many of the integration issues of today. The ongoing business imperatives for doing more with less people will make true collaboration with partners such as mining contractors, equipment vendors, transport providers, suppliers and maintenance contractors commonplace throughout the industry. All these organisations will be linked in and share common goals and objectives in real-time while providing visibility of internal constraints and available capability, allowing optimised decisions to be made across the extended enterprise. Humans will increasingly move to a more supervisory role and will use advanced collaboration to quickly solve complex abnormal issues that span the value chain out to the extended enterprise. The open collaboration and communication models instilled in the workforce through the widespread use of social networking technologies will drive thought leadership far beyond current æbest practiceÆ thinking. This will encourage the mining industry to extract the business value from rapidly converging fields of study such as environmental sciences, neuroscience, psychology, engineering, information technology and business finance. The future of mining will see a more uniform distribution of data savvy workers between the ages of 20 - 40, forcing a change in current operations. This group will drive the adoption of ubiquitous computing, augmented reality, presence and digital labelling. The enterprise will shift from a relatively static disparate set of functions to a digitally aware, integrated and interactive environment with information available, in context and just in time, to those who need it. The networked virtual enterprise will therefore be a reality.

Jan 1, 2008

By C Tapia Cortez, C Sammut, S Saydam, J Coulton

‘Like every other commodity, the value of the metals is subject to variation’ (Ricardo, 1817). Mineral commodity price uncertainties have always been a significant issue in mining business due to the close relation between global economic conditions and commodity prices, which commonly generates significant and unexpected price fluctuations. Price forecasts have been driven by economic theory, which states that in the long-run market will be balanced and that prices tend to the marginal cost of production. However, this theory has been misunderstood in the mining industry and future prices through time, in real terms, are assumed to be unchanged. This is unrealistic due to regardless of the cycling nature of economy and the omission of uncertainties. Furthermore, using historical data in traditional price forecast approaches does not guarantee realistic predictions as past events will not necessarily be repeated at the same intervals and with the same intensity. Mining, finance and economic sectors have made significant research efforts to predict prices and control uncertainties through classic linear, Gaussian and probabilistic simulation approaches. However, by definition, uncertainties cannot be measured or accurately modelled. Uncertainties can be identified to measure and manage the associated risks; therefore, uncertainties in mining projects have been historically misinterpreted, erroneously measured and poorly controlled. It is widely known that supply and demand functions drive market prices. While technological development noticeably influences supply, demand is strongly driven by psychological factors, mainly related to customer preferences and lifestyle expectations. Thus, human behaviour is one, or if not, the most important variable to determine commodity prices in a competitive market. During the last decades, alternative methodologies have been used to study uncertainties in human, environmental and market behaviours. Chaos theory, fractals, artificial intelligence and econophysics have been widely and successfully used to investigate complex dynamic systems to address uncertainties over time in the fields of neurosciences, meteorology, aviation and market trading. The application of these techniques in the market suggests a more realistic approach to the business environment. Through the combination of the methodologies above a novel long-run price uncertainties simulation approach that emphasise the differences between risks and uncertainties is proposed in this paper. CITATION:Tapia Cortez, C, Saydam, S, Coulton, J and Sammut, C, 2015. Copper price uncertainties – chaos theory to manage risks in mining projects, in Proceedings Third International Future Mining Conference, pp 261–272 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 4, 2015

People in economically developed societies demonstrate inherent human care for Earth and want to stop pollution. Yet efforts to clean Earth seem bogged in confusion from wildly contradictory and alarmist predictions of æclimate crisisÆ. Supposed experts openly disagree yet weÆre told thereÆs universal agreement humans are causing æthe end of life as we know itÆ. The turmoil combines with peopleÆs feelings of fear, guilt, anger, hopelessness and even resignation and apathy to trigger æclimate alarmÆ. The paper enables people to rediscover clarity, hope and support for Earth by understanding how climate alarm and confusion were created and how they actually increase pollution. Many people seem to think global warming is as serious as pollution and worry that questioning alarm will enable pollution. Yet theyÆre different. We need be even more concerned about climate alarm because history shows repeatedly that when buried by ignorance and panic real problems grow overwhelming. Environmental credibility is endangered by confused politicians and sensationalist media. When weÆre willing to re-evaluate what weÆve been told we replace fear and confusion with facts and freedom to identify opportunities. Combining this with practical understanding of human behaviour and leadership enables opportunities to be identified and action taken. The paper shows how confident, informed leadership leads and supports higher productivity and effective care for the natural environment.

Jan 1, 2009

In both exploration and mining, the laboratory is often seen as a cost rather than a profit centre. The aim in most mining companies is to increase profits by reducing costs, so the budget for the laboratory is under constant pressure.There is another option; to see the laboratory as the brain of the operation. By lifting the status of the laboratory and treating it as a profit centre, mine costs may be reduced in other ways, e.g. reduction in milling costs. This change of status will require investing more capital in better equipment, more training for employees and more employees to carry out project research.There are many examples of major costs being incurred because of inadequate laboratory work. Conversely, by spending more money on laboratories and their activities, overall costs can be reduced or profits enhanced.

Jan 1, 2002