Mine automation has been in development since the 1980s and began to be implemented in the 1990s with the biggest drivers being safety, reduced maintenance and increased productivity. Automation is used in many different mining methods performing a variety of tasks. However, very few studies have been conducted regarding the performance of automatic vehicles in real world mines, neither has much research been done when comparing automated and manual loading. The purpose of this thesis is twofold. First it is to identify and produce metrics that can be used to compare automatic and manual loading in an underground mining environment. A literary study is presented as a basis for these metrics where the development history is chronicled and the mechanics by which an automated system controls an automatic vehicle is explained. Also included is a description of different mining methods and the part that automation plays in them. Secondly, the goal is to use these metrics in a real world case study of automated loading in an actual operational mine. The Garpenberg mine, owned by Boliden Minerals, is an underground metal mine located in Dalarna, Sweden, and mining has been done there since the 1200s. Load-Haul-Dump (LHD) machines are used to load and haul ore ether using automation or tele operation. For this study information is extracted from Bolidens internal databases to calculate the metrics which are then used to analyze the performance and reliability of automated loaders, and also to compare manual and automatic loading. There are mainly three types of metrics that are relevant to automatic and manual loading, these being time related metrics, production related metrics and reliability related metrics. Since the LHDs dealt with in this thesis are operated both manually and automatically the main use of the time related metrics is to find the relationship between modes of operation in regards to engine hours spent in action, the amount and character of downtime that occurred during the analyzed time span, and the utilization of automatic LHDs during the workday. The most straightforward comparison between manual and automatic loading is the production, i.e. the tonnage of loaded material per unit time. In this thesis production will be analyzed per hour and per loading activity (which run between 3 and 4 hours). Lastly automated and manual loading will be compared on the basis of availability and maintenance, the reason being that LHDs are driven in different ways depending on the mode of operation. The results show that automatic loading consists of between 14 and 29% of production time while contributing to between 17 and 28% of downtime. No clear connection can be seen between downtime and the relationship of automatic to manual loading, as the difference is not bigger than 10% either way. Manual loading constitutes between 2500 and 3250 engine hours, while time spent during automatic loading constitutes between 420 and 1095 engine hours. The majority of all downtime is not specific to either mode of operation, although automatic specific stops constitutes up to 50% of total downtime for two of the LHDs studied. The distribution of loading activities is similar for both manual and automatic loading, with the number of concurrent activities dipping during lunch breaks and stopping entirely during shift changes. Manual loading peaks around 1000 concurrent jobs while automatic peaks at just fewer than 200. Regarding production the results show that manual loading is more effective in the short term, as three out of four LHDs has had a higher tonnage loaded per hour. However, when locking at the tonnage loaded per activity, automatic loading catches up to manual loading and produces more tonnage in the long term, with three out of four LHDs getting this higher production. One interesting result can be found in regards to fuel economy, as one of the LHDs show a reduced consumption of fuel while at the same time having had the largest percentage of time spent in automatic mode. No clear connection can be seen with the rest of the LHDs however, as they show no clear connection between time spent in ether mode of operation and the amount of fuel consumed. Automatic loading proved to have slightly higher availability than manual loading. In all cases however, the difference in no more than 10% and both modes of operation is above 90% availability. The higher availability of automatic loading is attributed to the fact that manual loading constitutes much more time than automatic loading, and thus there has been more time for breakdowns and production stops to occur for manual loading. The relationship of preventive and corrective maintenance is the same for all four LHDs irrespective of amount of time spent in ether operating mode. Preventive maintenance jobs accounts for more than 90% of the number maintenance actions for all LHDs. When analyzing what kinds of production stops are the most prevalent, there are differences between manual and automatic loading. For manual loading the most common stops are those that have to do with external circumstances in the mine such as blocked access and fallen boulders, and those to do with minor breakdowns of the LHD. For automatic loading the most common stops are those to do with the automatic system and the equipment used to operate the automated LHD, followed by those caused by external circumstances, similarly to manual loading. Automatic loading has proportionally fewer stops than manual loading in all categories except those unique to automation, which is in turn the biggest category of all production stops. The conclusions that can be drawn from these results are that automatic loading can outperform manual loading in the long term, but that continuous uninterrupted loading activates are important to achieve this. Automatic and manual loading show comparable reliability when it comes to maintenance and repairs (serious breakdowns are very rare). Availability and the relationship of preventive and corrective maintenance are similar between both modes of operation. The analysis of production stops show that the biggest problem with automatic loading is the automatic systems and the specialized equipments inability to handle the underground environment. Problems with recorded routes and falsely tripped safety systems are the most common stops. Recommendations to Boliden Minerals regarding the automatic system consist of improving remote troubleshooting and streamlining of problem solving dealing with automation software and hardware. Steps should also be takes towards tailoring the underground environment to better suit automation. Suggestions to further research consist of deeper studies of all the metrics presented in this thesis to better analyze the role of automation in the global mining industry. Another avenue of study is the combination of the findings in this thesis with the actual environment and layout in the Garpenberg mine to better understand the connection between operating environment and the reliability and productivity of the automatic system.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:ltu-64900 |
| Date | January 2017 |
| Creators | Marklund, Simon |
| Publisher | Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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