Reducing the Variability in Dragline Operator Performance

Australian coal mines have spent considerable capital on dragline improvements over the last two years. This has included ~$30 M on UDD conversions, >$20 M on new buckets, boom upgrades, electrical upgrades, etc. This is a natural part of the response of mining companies to technology and replacement programs. Capital expenditure is a normal part of the ongoing success of most companies. There is however, a tendency for some people to rely on the capital alone to provide the ongoing improvements in equipment productivity. Implementing new technology through capital expenditure is only part of the equation in continuous improvement. For 80 - 90 per cent of the year, the operator controls the productivity achieved by the dragline. Variation between operators is huge. The average standard deviation in productivity is 12 per cent and maintenance impact is over 40 per cent. Robbins 2003, states: Contrary to what we were taught in grade school, we werenÆt all created equal. Most of us are to the left of the median on some normally distributed ability curve. Further, he states: The issue is knowing how people differ in abilities and using that knowledge to increase the likelihood that an employee will perform his or her job well. There are two options for reducing variability between operators; improving operator ability and getting the machine to take over what the operator is doing (automation). Dragline automation will be discussed, however, this paper will focus more on the æhuman factorÆ and how to establish a dragline with minimum variability between operators.