Improvement in the overall efficiency of mining equipment: A case study

Fourie, Herman

doi:10.17159/2411-9717/2016/v116n3a9

Cited by 22 publications

(19 citation statements)

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“…During solidi cation after welding by E2209, weld region was completely governed with DSS. However, in practice it was reported that the DSSs weld solidify in fully ferritic mode (F mode) 27) and austenite nucleate below the ferritic solvus temperature, which mainly depends on the chromium and nickel equivalent (Cr eq /Ni eq ) ratio (>1.95 is F mode) of the steel and has been reported by many researchers 23,28,29) due to strong diffusivity of ferrite former elements (Mo and Cr) in ferrite phase 30) . It was also witnessed that E2209 (in electrode composition) have more Mo and Cr content (shows higher Cr eq ) but less Ni than E309L, which promotes higher Cr eq /Ni eq ratio.…”

Section: Microstructural Characterizationmentioning

confidence: 92%

“…From micro-hardness pro le results, it was evident that the variation in micro-hardness values of weld zone (237.5 HV and 198.8 HV average values) for E2209 and E309L respectively. This difference in the weld hardness could be attributed to the solidi cation mode, morphology and distribution of micro-constituents in the resultant WM due to difference in electrode composition as mentioned above [23][24][25][26][27][28][29][30] . However, E2209 weld solidify in F mode having higher Cr eq or Cr eq /Ni eq ratio than that of E309L.…”

Section: Mechanical Properties 321 Micro-hardnessmentioning

confidence: 99%

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A Comparative Study on the Effect of Electrode on Microstructure and Mechanical Properties of Dissimilar Welds of 2205 Austeno-Ferritic and 316L Austenitic Stainless Steel

et al. 2016

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In the present study, the weldability, microstructures and mechanical properties of dissimilar welds (2205 austeno-ferritic and 316L austenitic stainless steel) was investigated by using shielded metal arc welding (SMAW) with the help of two different electrodes namely duplex (E2209) and austenitic (E309L). After welding, the microstructure of the different zones of joints was evaluated by using optical microscopy and scanning electron microscopy (SEM), while, the localized chemical information was obtained by energy dispersive spectrometer (EDS) attached to the SEM. In E2209 weld metal, the solidi cation was observed as the primary ferrite mode. While, 309L weld metal was observed as the primary ferrite with austenitic matrix. Optimum ferrite content was observed in both the electrode. Finally, it was concluded that for the joints between the 2205 austeno-ferritic and 316L austenitic stainless steel, the E2209 electrode was dominant property wise.

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Section: Microstructural Characterizationmentioning

confidence: 92%

Section: Mechanical Properties 321 Micro-hardnessmentioning

confidence: 99%

A Comparative Study on the Effect of Electrode on Microstructure and Mechanical Properties of Dissimilar Welds of 2205 Austeno-Ferritic and 316L Austenitic Stainless Steel

et al. 2016

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“…The time periods for the forward speed of the longwall shearer as well as its position on The large volume of registered data required the development of IT tools that could archive and analyse such data. Relevant databases were therefore created for the particular groups and the degree of their aggregation, which were subsequently implemented into the data warehouse [17,23]. Figure 4 presents a view of the system part used for registering operation parameters in the database.…”

Section: Resultsmentioning

confidence: 99%

“…In this case, the analysis was also carried out using the Overall Equipment Effectiveness (OEE) model. Studies [22][23][24][25] have also made reference to the effectiveness of mining machines operating in both hard coal and bauxite mines. The above-mentioned publications essentially referred only to the analysis of the effectiveness for single mining machines, while the presented results indicated a low degree of utilisation of the mining machines being analysed.…”

Section: Introductionmentioning

confidence: 99%

Analysing the Utilisation Effectiveness of Mining Machines Using Independent Data Acquisition Systems: A Case Study

Brodny

Tutak

2019

Energies

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Growing competition in the market for energy raw materials needed for power generation has led to an increasing number of measures being undertaken in the mining sector to reduce the unit costs of mining production. One of the areas that offer considerable savings in this regard is the utilisation of the technical resources owned by mines. This article is therefore focussed on analysing the utilisation effectiveness of these machines, based on the data recorded by industrial automation systems, as well as on measurements from independent surveying and chemical analysis of the excavated material’s quality. For this purpose, a methodology was developed to use the data about the operational parameters of the machines in order to analyse the effectiveness of their utilisation. It was assumed that the reliability of this assessment would depend mainly on the quality of the data used to conduct it. It was also assumed that using independent data sources for the analysis would provide objective and reliable information on the operation of the machines, devoid of any subjective feelings of the personnel or other factors. The developed methodology, based on a modified Overall Equipment Effectiveness (OEE) model, was used to analyse four machines that comprise the automated longwall system. Values were determined for each machine, including their availability, performance and product quality. This, in turn, made it possible to determine a total effectiveness indicator, based on a modified Overall Equipment Effectiveness (OEE) model, for the particular machines and the entire technical systems they form. The obtained results were used to assess the effectiveness of their utilisation and recommend corrective measures aimed at improving this metric. Moreover, the analysis results made it possible to assess the utilisation status of the machines in question. They also served as the basis for determining further lines of research, the purpose of which is to improve the effectiveness of the mining sector. The obtained results indicated that this process requires the wide application of IT tools, especially for data archiving and analysis. These tools, along with the developed model and methodology based on the analysis of large volumes of digital data, are in accord with the activities related to the implementation of Industry 4.0 idea in mining. It is the authors’ opinion that the material at hand should find a wide range of practical applications in supporting the management of technical resources within the mining sector.

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“…Maintenance, Reliability and Safety (Schenkelberg, 2017;Asbjörnsson et al, 2016; Summit and Halomoan, 2015;Schenkelberg, 2015;Velmurugan et al, 2014; Dean and Ryde, 2014; Harwini and Singh, 2013;Johnsen, 2011;Fraser, 2011; Barabadi et al, 2010; Johnsen, 2018;Barabady and Kumar, 2008;Kumar et al, 2007; Chan and Kuruppu, 2006;Knights and Oyanader, 2005;Hall and Daneshmend, 2003;Montenegro and Lellis, 2003;Vagenas et al, 2003;Kim and Seong, 2002;Knights, 2001;Samanta, 2001; Shultz and King, 2001;Steinberg, 2001; Roy et al., 2011, Roman andDaneshmend, 2001;Paraszczak, 2000;Nave, 2000;Elerath, 2000;Nolan, 1999;Krellis and Singleton, 1998;Surtees, 1996;Fernie, 1993; Stahura, 1992(a); Stahura, 1992(b); Mackie and Rider, 1990;Nelson et al, 1985;Brouwer, 1979; Bonar;Myntti, 1978; Anon, 1976; Tomlingson, 1973;McIndoo and Woodle, 1968;Bowley, 1963; Willis, 1963;Pundari, 1962; McNickle, 1961; Mason, 1961;Thompson, 1950) [E] System Performance, Productivity and Utilisation (Morrison, 2017; Lukacs, 2016;Fourie, 2016; Tynan, 2016;Khorzoughi and Hall, 2016;Mohammadi et al 2015; Arputharaj, 2015;Kalra et al, 2015; Bruno and Suglo, 2015; Sankha and Dey, 2015;Lumley and McKee, ...…”

Section: [D]mentioning

confidence: 99%

Time utilisation modelling of fully mobile in-pit crushing and conveying systems

Dzakpata¹

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A comprehensive review of literature published during the last two decades shows that Fullymobile In-pit Crushing and Conveying systems (FMIPCC) systems in surface mines have been increasingly studied by the mining industry and have been adopted more often by mines having tabular deposits. In Australia, the majority of FMIPCC implementations have failed to address persistent problems of overestimation of FMIPCC efficiency over the past few decades, leading to low confidence in the uptake of the system. Additionally, current time utilisation models predict single-point values and do not account for the dynamic relationship with the variability of key mine design inputs (including bench width, bench height and bench length) on system utilisation. This research focuses on investigating the influence of key mine design variables (geometry approaches, sequencing and scheduling) on the performance of FMIPCC systems in open pit and open cut applications. The methodology used in this research first establishes the relationship between key mine design variables and FMIPCC performance and then develops a novel approach for predicting FMIPCC utilisation using stochastic variables derived from historic operational data. This research further investigates of the impact of open pit exploitation schemes on FMIPCC utilisations using a case study typical of Australian coal mining. The study result predicts FMIPCC operating time ranging from 3,379 -5,233 hours and 4,347 -4,963 hours based on a confidence interval (CI) of 95% and 50% respectively. The novel contributions of this research include the development of an improved stochastic approach to time utilisation modelling of FMIPCC systems. The potential exists to extend its use to other alternative continuous haulage systems remains. Additionally, this is the first work to comprehensively evaluate the effects of mine planning variables on the overall effective utilisation of FMIPCC systems. A comprehensive historical equipment performance data set is used to document system performance ranges along with simple statistical distributions. Finally, the research has developed the first stochastic tool for modelling the utilisation of FMIPCC, considering variability of the key modelling inputs. This research successfully fulfilled its objectives by providing evidence to support the hypothesis that a source of underperformance is linked to overestimation of productive hours and throughput of FMIPCC systems. Future work should extend this research work to investigate the application of FMIPCC beyond in-pit material handling, including ex-pit environment and integrated study of multiple open pits.

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Improvement in the overall efficiency of mining equipment: A case study

Cited by 22 publications

References 0 publications

A Comparative Study on the Effect of Electrode on Microstructure and Mechanical Properties of Dissimilar Welds of 2205 Austeno-Ferritic and 316L Austenitic Stainless Steel

A Comparative Study on the Effect of Electrode on Microstructure and Mechanical Properties of Dissimilar Welds of 2205 Austeno-Ferritic and 316L Austenitic Stainless Steel

Analysing the Utilisation Effectiveness of Mining Machines Using Independent Data Acquisition Systems: A Case Study

Time utilisation modelling of fully mobile in-pit crushing and conveying systems

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