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The Mine Vehicle Inspection Simulator (MVIS), based on virtual reality, provides a method of training that is superior in several ways to traditional methods. It allows the user to learn through interaction rather than by viewing static material. It is cost-effective because a vehicle need not be taken out of production for practice inspections. It automatically records the user's progress and is fully configurable so that different scenarios can be created and tested. Further work on the simulator is outlined., The Mine Vehicle Inspection Simulator (MVIS), based on virtual reality, provides a method of training that is superior in several ways to traditional methods. It allows the user to learn through interaction rather than by viewing static material. It is cost-effective because a vehicle need not be taken out of production for practice inspections. It automatically records the user's progress and is fully configurable so that different scenarios can be created and tested. Further work on the simulator is outlined.

Analysis of used oil can, over a series of analyses, predict the life of components and thus contribute to maintenance cost estimation. It also provides data on classic root causes of oil deterioration, leading to eventual maintenance costs. However, it can only predict costs for individual oil-filled components, which account for about 50% of total plant costs. As yet there has been little research into total proactive maintenance, which treats plant items as an entire unit. Condition monitoring systems are gaining in popularity, especially for large dump trucks, but the technologies used are still embryonic and no attempt has been made to correlate reports to running costs. The real root causes leading to increased maintenance expenditure may be other factors, such as operator skill, environment or ground conditions. These manifest themselves as water, fuel or soil contaminants in oil, as a consequence of poor daily and periodic maintenance., Analysis of used oil can, over a series of analyses, predict the life of components and thus contribute to maintenance cost estimation. It also provides data on classic root causes of oil deterioration, leading to eventual maintenance costs. However, it can only predict costs for individual oil-filled components, which account for about 50% of total plant costs. As yet there has been little research into total proactive maintenance, which treats plant items as an entire unit. Condition monitoring systems are gaining in popularity, especially for large dump trucks, but the technologies used are still embryonic and no attempt has been made to correlate reports to running costs. The real root causes leading to increased maintenance expenditure may be other factors, such as operator skill, environment or ground conditions. These manifest themselves as water, fuel or soil contaminants in oil, as a consequence of poor daily and periodic maintenance.