Reducing the Variability in Dragline Operator Performance

摘要

Australian coal mines have spent considerable capital on draglinernimprovements over the last two years. This has included ~$30 M on UDDrnconversions, >$20 M on new buckets, boom upgrades, electricalrnupgrades, etc. This is a natural part of the response of mining companiesrnto technology and replacement programs. Capital expenditure is a normalrnpart of the ongoing success of most companies. There is however, arntendency for some people to rely on the capital alone to provide thernongoing improvements in equipment productivity. Implementing newrntechnology through capital expenditure is only part of the equation inrncontinuous improvement. For 80 - 90 per cent of the year, the operatorrncontrols the productivity achieved by the dragline.rnVariation between operators is huge. The average standard deviation inrnproductivity is 12 per cent and maintenance impact is over 40 per cent.rnRobbins 2003, states:rnContrary to what we were taught in grade school, wernweren’t all created equal. Most of us are to the left ofrnthe median on some normally distributed ability curve.rnFurther, he states:rnThe issue is knowing how people differ in abilities andrnusing that knowledge to increase the likelihood that anrnemployee will perform his or her job well.rnThere are two options for reducing variability between operators;rnimproving operator ability and getting the machine to take over what thernoperator is doing (automation). Dragline automation will be discussed,rnhowever, this paper will focus more on the ‘human factor’ and how tornestablish a dragline with minimum variability between operators.