Illumination of parameter contributions on uneven break phenomenon in underground stoping mines

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Abstract

One of the most serious conundrum facing the stope production in underground metalliferous mining is uneven break (UB: unplanned dilution and ore-loss). Although the UB has a huge economic fallout to the entire mining process, it is practically unavoidable due to the complex causing mechanism. In this study, the contribution of ten major UB causative parameters has been scrutinised based on a published UB predicting artificial neuron network (ANN) model to put UB under the engineering management. Two typical ANN sensitivity analysis methods, i.e., connection weight algorithm (CWA) and profile method (PM) have been applied. As a result of CWA and PM applications, adjusted Q rate (AQ) revealed as the most influential parameter to UB with contribution of 22.40% in CWA and 20.48% in PM respectively. The findings of this study can be used as an important reference in stope design, production, and reconciliation stages on underground stoping mine.

Introduction

In underground metalliferous mining, stoping is the most commonly utilised mining method among various others. Adoption of stoping method has been steadily increased due to the ability to mechanisation into larger scale and the flexible applicability to various ground conditions. Many researchers have been reporting the popularity of stoping method. According to Pakalnis et al. [1], open stoping method accounts for half of underground metalliferous mine production in Canada. Once again, Pakalnis and Hughes [2] noted that in excess of 60% of underground mine production in North America relies on sublevel stoping method. Additionally, after investigation on major metalliferous underground mines in Australia, Jang et al. [3] reported that over 85% are operating by various stoping methods.

In spite of the popularity of stoping method, most of the mines are suffering from excessive dilution and ore-loss. Dilution and ore-loss can be simply defined as unwanted influx and remaining materials into planned ore production and in stope even after the production. These phenomena can be broadly classified into planned and unplanned which have been illustrated along with the stope production procedures in Fig. 1. As shown in Fig. 1b and d, planned dilution and ore-loss are determined at the stope planning stage while unplanned dilution and ore-loss can be confirmed after stope production.

Both planned and unplanned dilutions are basically unavoidable. Indeed, planned dilution and ore-loss can be minimised on the stope planning stage by thorough consideration to maximise net profit but not completely eliminated. Likewise, unplanned dilution and ore-loss are inevitable as long as stope is excavated by drilling and blasting method. In fact, the most important task to maximise the productivity of stope production is reducing unplanned dilution and ore-loss. To minimise the unplanned dilution and ore-loss, the causing mechanism and contributions of influencing parameters must be comprehensively investigated in preference.

The aim of this study is to illuminate the causing mechanism of unplanned dilution and ore-loss (uneven break: UB) based on a published uneven break prediction artificial neural network (ANN) model by Jang et al. [3]. The ANN model has been developed through comprehensive investigations on 1067 stope production results from underground mines in Western Australia. Justifications of choosing the uneven break prediction ANN model are; the model achieves the statistical significant with the correlation coefficient of 0.719 with ten major UB causative factors and is the unique model that covers both unplanned dilution and ore-loss simultaneously.

The remainder of this paper is divided into four sections. Section 2 reviews previous studies on uneven break phenomenon. Section 3 expounds the published UB prediction ANN and analyse the parameter contributions with representing essential findings. Subsequently in Section 4, the study will be concluded with comments on proper UB management system in underground stoping mines, and future works.

Section snippets

Uneven break management in underground stoping mines

Minimising uneven break (UB) in stope production is one of the most challenging tasks but cannot be abandoned. Because it is directly influencing not only to the productivity of stope production but also the profitability throughout whole mining operations. For instance, the inflexed low grade and waste material contaminate and downgrade the planned ore stream that burdens production cycles with extra mucking and hauling. Also, the remaining ore-loss in stope directly causes a diminution in

UB predicting ANN model and parameter contribution analysis

As mentioned in Section 1, a reliable UB predicting ANN model was introduced by Jang [14]. The model is comprised of ten UB causative factors under three categories, i.e., blasting, stope design, and geology. Five stope production blasting related factors were collected, i.e., average length of blasthole (Blen), powder factor (Pf), angle difference between the hole and wall (AHW), blasthole diameter (Bdia), and space and burden ratio (SbR). Three representative stope design factors, such as the

Conclusions

Uneven break (UB), unplanned dilution and ore-loss, is one of the most adverse phenomenon in underground stope production. It is often considered as an unavoidable and unpredictable phenomenon due to complexity of accruing mechanism. To minimise the unfavourable uneven break, a thorough examination on the causing mechanism and contributions of the influencing parameters to UB must be conducted. In this study, contributions of ten major UB causative factors and their general trends have been

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