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Dr. Nick Vayenas, Professor in the School of Engineering at Laurentian University established, in winter 1993, the Laurentian University Mining Automation Laboratory (LUMAL). This laboratory is supported by the School of Engineering and by the Department of Mines Technology of INCO Limited at Copper Cliff, Ontario, Canada. The main objectives of this lab are:
The Educational Objective:
To enhance and support teaching in mining automation/robotics and in the application of new technologies in the mining sector.
At present, Laurentian University is the only Canadian University that offers a compulsory course for the 4th Year undergraduate mining engineering students in mining automation/maintenance of mining equipment. Our students are learning about robotics, kinematics, sensors, navigation technologies, telecommunications in mining as well as aspects of exploration and mining in space (e.g. drilling on the Moon and Mars). Regarding maintenance of mining equipment, students are educated in maintenance of mining equipment, in maintenance strategies, replacement policies and reliability techniques for analyzing failures of mining equipment.
LUMAL is an industrial oriented laboratory. At present, most of the research work at LUMAL is supported by the Mines Technology Department of Inco Limited, a Canadian mining company with a leadership role in the application of new technologies in mining operations. LUMAL's expertise is focused on the following topics:
Engineering Analysis and System Architecture of Tele-remote/Automated Mining Systems
Since 1985, the head and founder of LUMAL (Dr. Vayenas) has been involved in and contributed to the design and implementation of prototype tele-remote/automatic underground mining equipment systems in Sweden and in Canada. In 1990, Dr. Vayenas earned a Ph.D. in the field of mining automation contributing to the analysis and implementation of a prototype remote-controlled/automatic Load-Haul-Dump vehicle in the Swedish mining industry. LUMAL has knowledge and expertise in system analysis, system evaluation and software integration.
LUMAL is gaining an international recognition on its know-how in simulation modelling and 3-D animation tools for evaluating new mining technologies and new mining equipment concepts. LUMAL is instrumental in the application of state-of-the art PC industrial simulators and together with industrial and academic partners (e.g. Inco Limited, Canadian Universities) is presently one of the leading mining labs in understanding and visualizing mining systems and future mining concepts.Since 1994, LUMAL has been creating simulation models of present and possible future underground mining equipment systems. The models are created using the WITNESS v3.07rel.6 simulation software, by The Lanner Group (formerly called AT&T ISTEL) and the AutoMod v9.0 software by Brooks-PRI Automation Inc.. These sophisticated computer models offer the possibility to realize and visualize the potential and limitations of new technologies and implement them in the most beneficial manner.
LUMAL has developed microcomputer discrete-event simulators/animators for dispatch and traffic control of surface and underground vehicle based materials handling systems. These models assist in decision making regarding estimation of optimum number of equipment, production control and route selection for efficient material transportation.
LUMAL has been involved in projects related to the analysis and evaluation of maintenance and reliability characteristics of mobile mine equipment. It has developed a practical methodology for mining engineers to successfully carry out maintenance studies and reliability evaluation by collecting and analyzing repair data and trends in machine failure. Maintenance studies carried out by LUMAL include evaluation of surface mining equipment as well as underground automatic trucks and tele-remotely controlled Load-Haul-Dump vehicles.
Mining Equipment Reliability Assessment Models Based on Genetic Algorithms. This project relates to the formulation, development and testing of models for mining equipment reliability assessment based on Genetic Algorithms (GAs) using maintenance data collected from mine sites. GAs are powerful and broadly applicable stochastic search techniques based on the principles of natural selection and heredity. The reason for selecting GAs is the fact that the reliability of a mining equipment changes over time due to its dependence upon several factors (e.g. the operating environment, number and quality of repairs). These factors create a combined and complex impact on the reliability function. This impact encapsulates and inherits to some degree the characteristics of the factors as they evolve over time. By using GAs, it is intended to capture the impact of the factors on the reliability function of a machine by mimicking the process of heredity and natural selection.
Stereolithography is a well known Rapid Prototyping Technique (RPT) in the manufacturing sector. It produces a physical, three dimensional object from a 3-D Computer Aided Design (CAD) file. A stereolithography machine uses a computer controlled laser to cure a photo-sensitive resin, layer by layer, to create the 3-D part. Producing a pre-production stereolithography prototype can greatly enhance the geometric visualization of a product, accelerate the design process and improve the communication between project team members. Stereolithography is in essence “rapid modelling” since the generated objects do not have the physical, mechanical or thermal properties of the final product. Rapid prototyping techniques (RPTs) such as stereolithography can facilitate mine engineers and geologists to quickly and with satisfactory accuracy to visualize sections of orebodies and evaluate alternative ore extraction techniques using 3D solid models. This project is supported by the Dept. of Mines Technology of Inco Limited and the Materials and Manufacturing of Ontario (MMO).
University of British Columbia, Dept. of Mining and Mineral Process Engineering, Vancouver, British Columbia, Canada. University of Western Ontario, Advanced Communications Engineering Centre, London, Ontario, Canada. Mining Systems Simulation Unit (MSSLab) at the Department of Mining Engineering at the National Technical University of Athens, Greece. Technical University of Luleå, Dept. of Civil and Mining Engineering, Luleå, Sweden. Natural Sciences and Engineering Research Council (NSERC), of Canada. Materials and Manufacturing Ontario (MMO), Mississauga, Ontario, Canada. Inco Limited, Copper Cliff, Ontario, Canada. Falconbridge Limited, Onaping, Ontario, Canada. Sandvik -Tamrock Canada Inc., Lively, Ontario, Canada. Boart Canada Inc., Lively, Ontario, Canada. Williams Operating Corporation, Marathon, Ontario, Canada. Rainbow Concrete Industries Limited, Sudbury, Ontario, Canada. Aitik Mine, Boliden Mineral AB, Sweden. LUMAL members
View a slideshow about discrete event simulation.
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