IM 2016 May 2016 | Page 35

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FLEET MANAGEMENT

algorithms applied to create our reporting. Conversely geology and engineering send data back to the tablets updating production information such as source, destinations and ore block IDs.”

The tablet app collects a host of information that is time stamped in real time allowing management to monitor safety and productivity elements such as pre-start checks and photos; load( time taken to load truck; haul( time taken to destination); return( time taken to return for next load); wait( time taken waiting for production to commence); stop( time taken for breakdowns). The data collected tells the truth about how the operation is performing and highlights opportunities for improvement.

The following reports can be made from data collected via the tablet: n time usage Gantt charts – man and machine n material movement – source and destination n daily unit cost versus forecast n tonnes moved n daily load and haul cost n daily ancillary cost n total mining cost n dig and haul rate n total loads n start and finish times

With the app mining companies are now able to monitor what time the trucks leave and return from the go-line and through education fleets gain an additional 15 minutes production per day( circa 500,000 t / y with a small 12 truck fleet).“ The pre-shift meetings are more succinct, the digger operator gets fast tracked to the digger for bench preparation and trucks return later because the tablets are sending the data throughout the day – alleviating the need for the trucks to finish early so production & pre-start check paper can be collected, validated and tallied.”

“ Having a fleet of trucks all working in unison with minimal queuing and a digger working at full capacity is a sign of a well-organised production team. If one of the truck operators starts to speed( or slow) and returns to the digger early( or late) they will have to wait to be loaded. This may create a gap in production as

well as congestion at the tip head, making the whole haulage fleet inefficient. This is quickly picked up from the queuing, load, haul and return times collected by the app.”

The company points out that budgeting, forecasting and Life of Mine( LOM) planning requires determination of production digger capability( loading times).“ If you don’ t have time and motion data available for your digger you have to rely on user manuals or rule of thumb data which invariably doesn’ t match crew, material or site capability.” On a medium size excavator( bucket 20 m 3), the loading time is circa two to three minutes, but the difference between two and three minutes is the stated 500,000 t / y.

The top right hand corner of the app has a meter that gives the actual cost of running that piece of equipment and ticks over just like a taxi meter. The cost of operation includes fixed and variable costs calculated per second.“ Operators had no idea of the true cost of operating a haul truck and were astounded by how many seconds it took to burn A $ 100. A sense of ownership comes across crews and they start to switch off the engines when any foreseeable idle time was imminent, rather than leaving the engine on to listen to the radio for 30 minutes.”

Finally, if the customer has a contractor fleet, they don’ t want to be paying for equipment that isn’ t operational. Tracking and reporting actual breakdown times can be very hard to achieve and prove, especially at the end of the month when invoicing occurs. The app allows the operator to record exactly when and why the breakdown occurred, as well as when the fitter arrives at the equipment and when the machine returns to the maintenance workshop.

The app feeds into a reporting system that allows the user to track a host of unit costs and total cost of operation.“ For tracking costs against budget, it has become a powerful tool, allowing management to make informed decisions. It also allows tracking of costs on individual pieces of equipment that may have minimum usage hours, or tracking costs on expensive pieces of equipment.”

VIST Group adapts FMS for emerging markets

Russia’ s fleet management system market leader is VIST Group. Its flagship VG KARIER MFMS system has a wide functionality and is adapted to the emerging markets. Costs of implementation and maintenance are on average about 1.5 lower than other vendors. VIST Group also supplies payload systems and on-board equipment for dispatch to the BELAZ mining truck factory in Zhodino, Belarus, and is jointly developing fully autonomous mining equipment with them, which will be included in the next generation MFMS.

VIST’ s current fleet management offering for the mining industry covers automatic optimisation and dispatching with criteria: performance, specific quality of ore required on the mill or unloading area, decreasing delays and idles, maximising availability ratios of mining equipment etc. It covers drill management with high precision navigation and drilling guidance; and ore quality control using information from each bucket of the shovel with high precision navigation.

It incorporates remote diagnostics data from equipment( such as Cummins and MTU engines, suspensions, tyres, hydraulics, vibrations). It can also be set up with tyre management control and prediction of availability; with security management with controlling zones and fuel consumption; automatic road quality monitoring; and the full cycle of fuel monitoring.

The latest addition is an Industrial Safety Management System with automatic work orders creation( EHS). This function is linked to the performance of technology and organisation of work.

Most data in the VG Karier system is available via web-interface, including reports, on-line monitoring, administration tools etc. The webinterface extends the number of users and provides remote access. On-board equipment and software provides 100 % data transmission to the server. Each on-board computer collects data from multiple sensors, stores it and instantly sends the data to the server using the wireless system. If there is no WiFi coverage collected data is stored in the memory of the device and is

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