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By John Fulton

Early in the year 1875, some difficulty was experienced in the " Old blast-furnaces " of the Cambria Iron Company, at Johnstown, Pennsylvania, arising from the increased use of native coke, prepared in Belgian ovens near the furnaces, in mixture with Connellsville coke, in the production of Bessemer pig-iron. This was the more surprising at that time, because a very caulplete coal-crushing and washing apparatus, after the Bradford plan, had just been put into successful operation, affording a pure coal for coke-making. It was confidently expected that this thorough cleansing of the coal would improve the quality of the coke and fit it for the increasing manufacture of Bessemer pig-iron. But the trouble with the native coke continued. Experiments in fuel charges-increasing and reducing them—failed to correct the irregular working of these furnaces. Increasing the charge of native coke produced abnormal heat at the top of the furnace, reducing it cooled the furnace below. At this stage of affairs, the Hon. Daniel J. Morrell, general manager of the Cambria Iron Company, requested the writer to make the requisite investigation to determine the nature of this coke-difficulty, and to ascertain why the Johnstown coke could not be used in blastfurnace work as well as Connellsville. This task at first did not appear to present any special difficulties, but subsequently it expanded into proportions that caused no little anxiety. The first effort was directed to procuring average samples of Johnstown and Connellsville coke. At this period of the investigation, it was assumed that the whole matter could be intelligently solved by comparing the chemical analyses of the two cokes: Johnstown Coke. Connellsville Coke. Moisture,.......... 0.30 Volatile matter,......... 0.46 Fixed carbon,.90.48 89.57 Ash,.8.96 9.11 Sulphur,.0.56 0.82 Phosphorus,..... 0.014 100.00 100.274 Analysts, T. T. Morrell. A. S. McCreath.

Jan 1, 1884

By L. P. Meade

The need to feed an established talc mill from a crude ore source located closer to the mill prompted the 1986 drilling of a previously mapped, talc-carbonate deposit. This talc-bearing rock had never been considered a potential source of crude talc ore because of the high carbonate content and other deleterious minerals observed in outcrops. Selective mining, in-pit grade control and creative processing have allowed this deposit to be developed into an ore body. By definition, an ore body has to be a source of positive cash flow. With industrial minerals, this is determined as much by market acceptance as by ore tenor.

Jan 1, 1994

By L. P. Meade

The need to feed an established talc mill from a crude are source located closer to the mill prompted the drilling in 1986 of a previously mapped talc-carbonate deposit. This talc-bearing rock had never been considered as a potential source of crude talc are because of the high carbonate content and other deleterious minerals that were observed in outcrops. Selective mining, in-pit grade control and creative processing has allowed this deposit to be developed into an orebody. By definition, an orebody has to be a source of positive cash flow. With industrial minerals, this is determined as much by market acceptance as by are tenor.

Jan 1, 1992

By P. G. Terrazas Prado

This paper presents the results of research on the development and application of a custom-made truck cycle and delay automated data collection system (TCD-ADCS) in a surface coal mining. Truck cycle and delay field data are locally stored in trucks and then synchronized and replicated through a wireless network into a centralized server containing an already-developed integrated production management system (IPMS). The system relies on motion sensing and distance travelled in order to automatically define the cycle starting/ending points, cycle time, position, and delay time. Connectivity and communication between loading equipment and trucks are also established. Communication between the equipment operators and TCD-ADCS system is via a user-friendly graphic interface. The hardware used for the development of this system consists of a rugged touch-screen personal computer, 2.4 GHz radio transmitter antenna, and a commercial GPS receiver. The system was developed, tested, and deployed at a surface coal mine in the USA. Keywords surface coal mining, truck and shovel, data collection, information systems.

Nov 1, 2013

By P. Walshe

A common belief among Itlnl.ng operators today is that computer based truck m:mitoring and dispatching systems are only applicable to, or affordable by, very large scale open pit mines. Before the advent of microcomputer technology this belief was generally a valid one. Microcomputer technology as it currently exists has reached a high level of sophistication and capability, rapidly approaching that of the minicomputer standard. When coupled with reliable software and data communications packages, it now provides the means to make truck monitoring and dispatching a viable and attractive management aid to mines of all sizes. This paper briefly addresses the evolution and current state of computer truck dispatching and examines a microcomputer based system in this context. To demonstrate the effectiveness of this approach to truck dispatching a recent installation in a medium sized mine is presented. Preliminary field data from the case mine are presented to illustrate the methodology.

Jan 1, 1989

By P. K. Chatterjee

"The operations of a large-scale open-cut mine are simulated to produce a user-oriented interactive digital model. SIMULA is chosen as the programming language and a sophisticated data base system is designed to consider the complex information network of large mines. The main features of the program are the mine planning and mine evaluation modules. These modules are responsible for the computation of truck-shovel performance and other equipment details in a mine. Stochastic methods are employed to generate event times. The use of a Data Base Management System and the data base provide an efficient method of information storage and retrieval. Truck allocation techniques have been examined in detail and comparisons between random dispatching and conventional methods are made. The model is intended for mine operators and engineers and the program is well structured and very readable. It is hoped that these features will make the model readily acceptable.IntroductionThe Department of Mining and Metallurgical Engineering at the University of Queensland has been conducting research into computer simulation methods in mining since 1972. The research has been mainly applied to actual operations, with both open-cut and underground mining being equally emphasized. The results of the research to date have not only strengthened the methodology of the approach to complex mining problems, but have also increased confidence in the use of modelling and computer simulation technique s in mining.The model described in this paper translates a complex LHD situation into a user-oriented interactive digital model using SIMULA. The present methods of evaluating truck dispatching and trolley assist are tedious and laborious. This model provide s the engineer with readily acceptable means of rapidly assessing the relative merits of these techniques in a large-scale open-pit operation. Poor utilization figures in many current operations (for example, 40% for trucks, 70% for shovels) are of serious concern to mine officials and computer-controlled dynamic truck dispatching systems have been considered by some of these mines to improve equipment utilization ."

Jan 1, 1981

By Edward R. Mueller

As an alternative to a million dollar, sensor based, computer dispatching system, Cyprus Pima Mining Company has installed a home¬made analog computer. The device is used in conjunction with a standard radio-dispatching system; it is inexpensive and very simple to build and operate. It enables the dispatcher to make near opti¬mum dispatching decisions and to identify all off schedule haulage trucks. Since installation, Cyprus Pima has experienced significant increases in pit productivity.

Jan 1, 1977

By H. Askari-Nasab, S. Upadhyay, A. Moradi-Afrapoli

Material handling in surface mines accounts for around 50% of the operational cost. Optimum truck dispatching plays a critical role in the reduction of this operational cost in truck and shovel surface mines. Researchers in this field have presented several mathematical models to solve the truck dispatching problem optimally. However, a critical survey of the literature has shown that three significant drawbacks exist in the available truck dispatching models. The published models underestimate the importance of the interaction between truck fleet, shovel fleet, and the processing plants. They also disregard goals set by strategic-level plans. Moreover, none of the available models account for the uncertainty associated with the input parameters. In this paper we present a new truck dispatching model that covers all of these drawbacks, using a fuzzy linear programming method. The performance of the developed model was evaluated through implementatin in an active surface mining operation. The results show a significant improvement in production and fleet utilization.

Sep 1, 2021

By Yashar Pourrahimian, Roberto Noriega

Truck fleet dispatching plays a crucial role in reducing operational costs and fulfilling operational targets in open-pit mining operations and is subject to large uncertainty arising from the operating cycles of trucks and loading equipment. This paper proposes a reinforcement learning-based truck dispatching system. Reinforcement learning is a machine learning area that deals with learning an optimal sequential decision-making strategy in an uncertain environment. An open-pit load-and-haul simulation is developed that also captures the truck movements and interactions in the shared road network, and a Neural Network is successfully trained to suggest truck dispatching decisions in a real-time manner.

Jun 25, 2023

Aitik, a Boliden owned and operated open pit mine located in northern Sweden, will expand production from 18 Mt per year today to 36 Mt per year copper ore during 2010. The challenge for the mine operation is to double production with a planned increase of the shovel and truck fleet of only 50 per cent. This will be achieved through improved shovel and truck utilisation and productivity. In early 2005 Aitik started projects to enhance the utilisation of truck engine hours and to reduce fuel consumption. Both projects were successful, within a year efficient2 utilisation of engine hours increased from 60 per cent to 75 per cent and fuel consumption was reduced by six to eight per cent. The truck utilisation project focused on minimising idle truck hours by for example four operators on three trucks thus reducing idle engine hours to minimise lost time for breaks and shift changes. Other measures included focusing on improved dispatch usage, parking trucks when overtrucked, etc. Eco-driving was a project together with Swedish Road Administration with the objective to combine economical and environmental savings. To keep the focus on eco-driving a reward was set up for the shift team with the lowest fuel rate over rolling 15 weeks periods. Both activities included a comprehensive training program for mine foremen, dispatchers and truck operators focusing on efficient use of trucks from economic driving to optimised truck dispatching and minimising idle engine hours. Online monitoring of trucks activities and fuel consumption combined with continuous reporting gave shift foremen and management a tool to discuss and follow trends and individual shift team performance. The combination of close monitoring of mainly organisational practices and operator training resulted in significant productivity increase and lower operating costs without any capital investments.

Jan 1, 2007

A brief history of the significant haulage truck feature changes and the factors that influenced those changes during the 60's and 70's provide a basis for forecasting the changes that can be expected in the 1980's. A review of the impact factors and changing requirements that currently exist that will create changes. Define the critical requirements of a successful haulage truck design and discuss the availability of bigger engines and better electric drive componetry to provide deeper pit capability and improve reliability. The Unit Rig Trolley Assist System to provide improved productivity and diesel fuel savings and an economic analysis to evaluate the Trolley System is covered. The Unit Rig Automatic Truck System for a driverless truck is covered in concept and discussed from the point of view of the experience in a test in a New Mexico mine. INTRODUCTION A good basis for trying to forecast what is going to happen in the future is to go back a little bit in history, to see what the influencing elements were in different periods of time as a foundation for the forecast. INFLUENTIAL FACTORS IN THE 1960'S If you look at the truck development that occurred in the 1960's, there were some identifiable factors that give us insight. (See Fig. 1) Several things happened at the beginning of the 1960's. Mechanical drive haulage trucks were introduced that were

Jan 1, 1982

By Tom Bilson

TO recover the remaining ore tonnages along the south side of the Inspiration orebody, the company began open-pit operations in early 1948 in addition to underground mining. Due to the differences in elevation between the orebody and the existing ore handling and treating plants, the truck haulage operation is up hill. Road grades were established at 7 pct maximum.

Jan 8, 1951

By S P. Young, K R. Monro

Reducing metal prices have forced mining operations to become more efficient and innovate in order to do more with the existing base. Much of this effort has focused on improving the efficiency of load and haul operations. The key to this is to understand and quantify where delays and missed opportunities exist. Metrics such as utilisation of availability, efficiency utilisation and asset availability are helpful indicators of performance; however, uptime-based time usage models and performance analysis tools using productive operating time models help to identify additional improvement opportunities.Phu Kham is a copper-gold mine operated in the Lao People’s Democratic Republic (Laos) since 2008 by PanAust Limited. The mine is a single large open pit of 450 m depth, running a fleet of 51 100 t class rigid dump trucks and 300 t and 200 t shovels controlled with the aid of a fleet management system in order to achieve ex-pit material movements of 56 Mt/a.Commencing in late 2014, a range of initiatives were implemented in order to improve the efficiency of the mine haulage fleet. These include hot seating of all operator changeouts via changeout ramps, split shifting of crews to minimise queuing delays, maximising blast volumes and minimising blast event days to reduce blast exclusion delay events including opportune refuelling of equipment during blasting events, inspections of trucks during refuelling events, implementation of a dedicated haul road services team to help reduce wet weather related delays and infrastructure development for haul path efficiency improvements.These and other initiatives have allowed the mine haulage fleet utilisation of availability (UofA) to be sustainably increased from 85 per cent to 97 per cent (see Figure 1), efficiency utilisation to increase from 85 per cent to 90 per cent, and productive operating time (POT) to increase from 73 per cent to 84 per cent. The corresponding increases in efficiency of the haulage fleet has allowed an equivalent reduction of eight haul trucks from the fleet to meet continuing life-of-mine production requirements.CITATION:Monro, K R and Young, S P, 2016. Truck haulage improvements at the Phu Kham mine – the journey to 97 per cent utilisation of availability, in Proceedings International Mine Management Conference, pp 339-346 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jun 22, 2016

By Brzezniak W

Conversion to trolley assist is a means of minimizing diesel fuel consumption, which in many mining situations offers a rapid payback of capital investment plus the inherent flexi- bility and maneuverability of truck shovel op- eration. Whendiesel electric truck shovel mining opera- tion with trolley assist is compared to alter- native mining methods such as conveyor systems, the trolley assist system can be easily justi- fied in terms of return on investment, payback and increased productivity. A review of present technology, performance requirements and past experience in the min- ing industry has led to the development of a trolley assist system for diesel electric haulage trucks which, is proven in the mining environment, offers significant reduction in fuel consumption and increased productivity.

Jan 1, 1981

By David M. Lake

Conversion to trolley assist is a means of minimizing diesel fuel consumption, which in many mining situations offers a rapid payback of capital investment plus the inherent flexibility and maneuverability of truck shovel operation. When diesel electric truck shovel mining operation with trolley assist is compared to alternative mining methods such as conveyor systems, the trolley assist system can be easily justified in terms of return on investment, payback and increased productivity. A review of present technology, performance requirements and past experience in the mining industry has led to the development of a trolley assist system for diesel electric haulage trucks which, is proven in the mining environment, offers significant reduction in fuel consumption and increased productivity.

Jan 1, 1981

? CONSTRUCTION AND MINING COSTS ARE HIGH IN THE ARCTIC ? VERTICAL KIMBERLITE PIPES WITH HIGH STRIP RATIOS ? SITE SPECIFIC GEOMETRIC CONSTRAINTS ? OPEN PIT FOLLOWED BY UNDERGROUND MINING ? HIGH KIMBERLITE UNIT COSTS TRACK INSTALLED ON PIT WALL ? INTENDED TO REPLACE MAIN HAUL RAMP ? 5 MIN HOIST CYCLE TIME ? KEY ADVANTAGES - REDUCED CYCLE AND STRIPPING RATIO ? TECHNOLOGY EXISTS IN OTHER APPLICATIONS

May 1, 2003

By T. M. Anderson

From the start of production in 1915 until 1948, underground block caving operations accounted for all of the ore production of Inspiration Consolidated Copper Co. Open pit development work began in 1947, and ore production from the open pit commenced in March 1948. Thus began the transition from underground to open pit mining which continued until August 1954. Since then, open pit mining has accounted for all ore production which presently averages 105,000 tons of ore and 75,000 tons of waste rock each week. Open pit mining operations at Inspiration is carried on in two separate pits-the Live Oak Pit and the Thornton Pit. The Live Oak Pit covers an area of approximately 1500x3000 ft and the Thornton Pit, 2500x2000 ft. The geographic centers of the two pits are 4000 ft apart and, at their nearest point, the surface slopes are 500 ft apart.

Jan 1, 1961

By L. Price, R. Hortie

Movement of ore and waste from the Hilton Mines pit is accomplished by truck haulage. With the aim of reducing costs, a study of truck fleet replacement was initiated. The study included on-site short-term tests and longer-term rental purchase agreements for haulage trucks. The operation and maintenance characteristics of different trucks, along with projected haulage conditions, were used to prepare cash flows, from which the most advantageous trucks were selected. The results of the study and implementation of the recommendations gave a cost saving greater than had been estimated. The study also indicated areas where improvements could be made, and resulted in much more attention being paid to road conditions, the training of operators and mechanics, and the development of a practical preventative maintenance scheme.

Jan 1, 1971

Purpose of TSUG Continuous Improvement in Mining Share Best Practises Exchange Ideas Network for Frontline Supervisors and Middle Management Meetings ? Two per Year -Spring and Fall ? Thirty Five to Forty Attendees ? Rotate Between Host Properties ? Host Mine Provides ? Meeting Room for One Day Tour of Mine and Maintenance facilities on Second Day

May 1, 2010

TSUG Presentation Overview What/Who we are? Objectives & Mandate How to become a member (who qualifies)? Meeting Agenda?s & Frequency Q & A SMART is an association of mining companies that meet regularly to coordinate the technology development needed by the mining industry. Since 1995, the member companies and institutions have directed research and influenced the manufacturers and suppliers to improve surface mining technology and services. SMART actively supports learning seminars, collaborative research projects, and user groups. Members of SMART include some of the major surface mining companies in North America and Australia. These companies have recognized the value that collaboration can bring to the needs of individual organizations as well as the global mining industry.

May 1, 2008