Håkan Schunnesson

Rock characterisation using percussive drilling

Abstract Despite considerable advantages such as reliable hardware, no disturbance in production, fast analysis and presentation of results and very low operational cost, the use of percussive drill monitoring to retrieve geological and geomechanical information concerns the drilled rock has not become a standard investigation tool in the underground industry. One major obstacle is the analysis of data. The monitored “raw” data can be affected by a significant influence from the operator, who often adjusts the drill settings in order to achieve the best drilling result. Furthermore, the advanced control system on a modern drill rig adjusts drill parameters independently to avoid drilling problems and damage to the drill string and machine. In order to use percussive drill monitoring in industrial applications, the performed analysis must be able to handle variations among monitored drill parameters, but still separate rock dependent variation from other influences on the monitored drilling data. Once the external influences on the drilling data have been normalised only leaving the rock dependant variation, rock properties can be predicted using theoretical or heuristic relations, or calibrated with observed rock conditions using statistical analysis. The method of analysis suggested in this paper is based on a step-wise normalisation of raw drilling data, where hole length dependent variation initially is removed, followed by a normalisation of the thrust dependent variation, and finally, by removing the influence of penetration rate on torque pressure. The analysis shows that major classification errors can be made if raw data are used instead of normalised data. The technique is applied on modern drill monitoring data from three different drilling sites, in crystalline rock masses in Sweden. The drill data selected were obtained during normal drilling conditions, where no special steps had been taken to promote the analysis or the interpretation. Examples from each site show good potential to predict ore boundaries and fracturing based on normalised drill parameters from percussive drilling.

The influence of the operating environment on manual and automated load-haul-dump machines : a fault tree analysis

The automated load-haul-dump (LHD) machines have the potential to increase productivity and improve safety, but there are many issues to be considered when optimising the operation of LHDs. Todays focus on improved equipment reliability is part of the problem, and another difficult issue is the special conditions and constraints of the operating environment. For automated LHDs, the latter issue is even more important, as humans have been removed from the production area and are not close by to solve the problems. The purpose of this paper is to find the causes of LHD idle time and to study their impact on the operation of LHDs. In this study, real-time process data and maintenance data from an underground mine in Sweden have been refined and integrated. The study takes into account the complexity of the mine environment, discusses the factors to be considered when optimising and automating the operation and uses fault tree analysis (FTA) to analyse the idle time.

Production and maintenance performance analysis: manual versus semi‐automatic LHDs

Purpose – The purpose of this paper is to evaluate and analyse the production and maintenance performance of a manual and a semi‐automatic load haul dump (LHD) machine to find similarities and differences.Design/methodology/approach – Real time process‐, operational‐ and maintenance data, from an underground mine in Sweden, have been refined and aggregated into KPIs in order to make the comparison between the LHDs.Findings – The main finding is the demonstration of how production and maintenance data can be improved through information fusion, showing some unexpected results for maintenance of automatic and semi‐automatic LHDs in the mining industry. It was found that up to one third of the manually entered workshop data are not consistent with the automatically recorded production times. It is found that there are similarities in utilization and filling rate but differences in produced tonnes/machine hour between the two machines.Originality/value – The originality in this paper is the information fusion...

Reliability Analysis and Comparison Between Automatic and Manual Load Haul Dump Machines

Todays trend of replacing manually operated vehicles with automated ones will have an impact not only on machine design, working environment and procedures but also on machine breakdown and maintenance procedures. In the harsh environment of underground mines, the transition from manual to automatic operation is believed to fundamentally change the basis for break downs, maintenance and machine design. In this paper, differences and similarities between manual and automatic underground loading equipment is analysed from a reliability point of view. The analysis is based on a case study performed at a Swedish underground mine. In the contrary of common thoughts, this paper proves that there is a difference between the manual and semi-automatic machines and in particular for the transmission, in favour of the manual one. This paper also shows a path for detailed reliability analysis, and the results may be used for improving maintenance programmes for other types of mobile equipment. Copyright

Optimisation of track geometry inspection interval

The measurement and improvement of track quality are key issues in determining the time at which railway maintenance must be performed and its cost. Efficient track maintenance ensures optimum allocation of limited maintenance resources which has an enormous effect on maintenance efficiency. Applying an appropriate tamping strategy helps reduce maintenance costs, making operations more cost-effective and leading to increased safety and passenger comfort levels. This paper discusses optimisation of the track geometry inspection interval with a view to minimising the total ballast maintenance costs per unit traffic load. The proposed model considers inspection time, the maintenance-planning horizon time after inspection and takes into account the costs associated with inspection, tamping and risk of accidents due to poor track quality. It draws on track geometry data from the iron ore line (Malmbanan) in northern Sweden, used by both passenger and freight trains, to find the probability distribution of geometry faults.

Evaluation of track geometry maintenance for a heavy haul railroad in Sweden: A case study

The measurement and improvement of track quality are key issues in determining both the restoration time and cost of railway maintenance. Applying the optimal tamping strategy helps reduce maintenance costs, making operations more cost-effective and leading to increased safety and passenger comfort. In this paper, track geometry data from the iron ore line (Malmbanan) in northern Sweden, which handles both passenger and freight trains, are used to evaluate track geometry maintenance in a cold climate. The paper describes Trafikverket’s (Swedish Transport Administration) tamping strategy and evaluates its effectiveness in measuring, reporting and improving track quality. Finally, it evaluates the performance of the maintenance contractor and discusses the importance of the functional requirements stated in the outsourcing contracts.

The use of discrete event simulation for underground haulage mining equipment selection

The selection of equipment for haulage in underground mines is a challenge due to its impact on both production rates and costs. The selected equipment should create an optimal match for the complete system and the point when equipment is to be added or replaced needs to be identified before the change is made. The use of discrete event simulation to compare two different haulage units of different size with the aim of improving production is presented. The feasibility of the production targets was also analysed. The result shows that, the smaller unit improves the average production from 52% to 75% while the bigger unit improves to 83% of the planned production target. This shows that the production will rise by 8% when smaller units are replaced by bigger units. This may need to be justified financially as the costs associated with changing the truck size might be recuperated by extra production gained. Furthermore, the study showed that current production targets were not feasible under the given circumstances.

Evaluation of Rock Mass Characteristics Using Measurement While Drilling in Boliden Minerals Aitik Copper Mine, Sweden

In the mining industry, rock mass characterization is necessary for both short term and long term production planning, but it is a challenge to get detailed information on the geo-mechanical properties of rock mass. Measurement While Drilling (MWD) is a well-established technique to retrieve data on the mechanical response of the rock mass in penetrated horizons. With this data the mining process could be improved regarding drilling cycle time, blast design, loading, hauling, crushing energy and grinding energy for present and underlying benches. This paper presents an attempt to characterize the rock mass in Boliden Minerals Aitik Mine, the largest open pit copper mine of Europe, located in the Northern part of Sweden. Penetration rate and specific energy are used to describe how subsequent benches (upper and lower) are inter-related. The behavior of Specific Energy and Penetration Rate is further evaluated and analyzed.

Development of a Markov model for production performance optimisation. Application for semi-automatic and manual LHD machines in underground mines

This paper compares three ways to operate a load haul dump (LHD) machine, manual operation, automatic operation (fleet operation) and semi-automatic operation, to find the best operating mode. In a fault tree analysis, different failures are classified and analysed, but the way to recover from certain states is not accounted for, which is something a Markov model can handle. The paper is based on the analysis of real data from an underground mine. A Markov model has been built for mining application and it is shown that a semi-automatic LHD has the highest probability of being in a productive state since it has the advantage of changing operating modes (manual and automatic) depending on the need and situation. Hence, the semi-automatic LHD is the best choice from an operational point of view. The paper fills a gap in the literature on manual vs. automatically operated LHDs by providing a new way of evaluating the operating mode of LHDs using Markov modelling, while considering the operating environment.

Intelligent Scheduling for Underground Mobile Mining Equipment

Many studies have been carried out and many commercial software applications have been developed to improve the performances of surface mining operations, especially for the loader-trucks cycle of surface mining. However, there have been quite few studies aiming to improve the mining process of underground mines. In underground mines, mobile mining equipment is mostly scheduled instinctively, without theoretical support for these decisions. Furthermore, in case of unexpected events, it is hard for miners to rapidly find solutions to reschedule and to adapt the changes. This investigation first introduces the motivation, the technical background, and then the objective of the study. A decision support instrument (i.e. schedule optimizer for mobile mining equipment) is proposed and described to address this issue. The method and related algorithms which are used in this instrument are presented and discussed. The proposed method was tested by using a real case of Kittilä mine located in Finland. The result suggests that the proposed method can considerably improve the working efficiency and reduce the working time of the underground mine.