Blast fragmentation size distribution and thus blast design have been found to have a direct impact on the load and haul cycle through excavator dig time and bucket payload. Previous studies have demonstrated that by reducing the excavator dig time and increasing bucket payload, significant improvements can be made in both productivity and unit cost. Simulation work reported in the literature indicates that a 20 per cent improvement in dig time may result in only a three per cent improvement in load and haul productivity and unit cost. At the same time, a ten per cent improvement in bucket payload will directly translate to a ten per cent improvement in load and haul productivity and unit cost. Based upon these findings, extensive laboratory and field work have been undertaken in the past to correlate blast fragmentation distribution to bucket payload. In contrast, the literature reports limited studies quantifying the impact of blast fragmentation on excavator dig time. Field work was conducted at Placer Dome Asia Pacific's Granny Smith Mine (Wallaby Pit) in Western Australia, concentrating on quantifying the impact of blast fragmentation on the dig time of a Liebherr 994 hydraulic excavator (shovel attachment with 14 m~3 bucket). Fragmentation was assessed for each truck load of material using the Split Desktop system, while the excavator cycle analysis was conducted manually. Measured fragmentation P_(80) (fragment size at which 80 per cent of material passes) values ranged from 200 mm to 1200 mm. The field study investigated the impact of various fragmentation parameters (P_(20), P_(50), P_(80), cumulative per cent passing 250 mm size fraction, and uniformity index) on the average and total dig times. The results indicate that the fragmentation P_(80) provides the best correlation to average dig time (total dig time divided by the number of bucket passes to load a truck). The total dig time was found to be dependant upon the fragmentation P_(80) and the number of bucket passes to fill a truck. Monte Carlo simulation results, based upon these relationships, indicate a 26 per cent improvement in average dig time and a 12 per cent to 46 per cent improvement in total dig time (bucket passes ranging from 4 to 8), with a change in fragmentation P_(80) from 600 mm to 200 mm.
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机译：已经发现爆破碎片尺寸分布并因此发现爆炸设计通过挖掘机挖掘时间和铲斗有效载荷对负载和运输周期产生直接影响。以前的研究表明，通过减少挖掘机挖掘时间并增加铲斗有效载荷，可以在生产率和单位成本中进行显着的改进。文献中报告的仿真工作表明，挖掘时间20％的改善可能导致负载和运输生产率和单位成本的增加三个百分之三。与此同时，桶有效载荷的10％改善将直接转化为负荷和运输生产率和单位成本的10％。基于这些调查结果，过去已经进行了广泛的实验室和野外工作，以将爆破碎片分配与桶有效载荷相关联。相比之下，文献报告了有限的研究量化爆炸片段对挖掘机挖掘时间的影响。在澳大利亚州亚澳大利亚亚澳大利亚亚太地区的奶奶史密斯矿（袋鼠）进行了野外工作，专注于量化爆破碎片对Liebherr R 994液压挖掘机的挖掘时间的影响（铲斗附件，带14米〜3桶）。使用分割桌面系统对每个卡车负荷进行分段，而手动进行挖掘机循环分析。测量的碎片P_（80）（片段尺寸，其中80％的材料通过）值的值范围为200mm至1200mm。田间研究研究了各种碎片参数的影响（P_（20），P_（50），P_（80），累积百分比通过250mm尺寸分数和均匀性指数的累积次数）。结果表明，碎片P_（80）提供与平均跳转时间的最佳相关性（总跳转时间除以铲斗的数量以装载卡车）。发现总挖掘时间依赖于碎片P_（80），并且铲斗的数量通过以填充卡车。基于这些关系的蒙特卡罗模拟结果表明平均跳转时间26％，总跳转时间（铲斗通过4至8的铲斗通过46％），改变碎片P_ （80）从600 mm到200毫米。
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