The profitability and feasibility of a system depends on the optimisation of the work of the subsystem as a unit. Here, the breakdown hours of an LHD machine is predicted by modelling a time series on a Neural Network. By accurately predicting the breakdown hours one can plan for efficient mining operations, maintenance and parts supply chain for replacements.

In this era of intense economic competition as well as harsh and complicated environmental conditions, it is of utmost importance to achieve the high productivity and production of the mining equipment. This paper strives to analyze reliability and maintainability of Load, haul and dump (LHD) machine and to compute inherent availability of LHD machine in Saoner Mine Nagpur India. In this paper, renewal process is used for the modelling of the mechanical failures of the LHD. The validation of data whether it is independent and identically distributed (IID) is done by assessing the presence of trend and serial correlation with the help of graphical method. The parameters of various distributions were found by using Math Wave Easy Fit 5.6 professional software. Chi-square test has been applied for selecting the best fit distribution model. Further the study of the two parameter log normal distribution theory and its parameters is presented using log normal probability theory. The study reflects that analysis of reliability is a powerful tool for determining the intervals of maintenance.

Lubricant degradation is the main cause for low performance of the machine such as heavy engineering machines, mining machinery etc. Lubricants are used for smooth running of gears and they also avoid friction and noise. Its performance is affected by high temperature and shearing, due to high temperature viscosity of oil changes and due to shearing its physical property changed or degraded. This paper analyses the failure behaviour of gear oil used in Load Haul Dumper (Model No: Eimco Elecon – 811MK). Gear oil degradation was measured by oil analysis in two sections: (i) fluid properties and (ii) contamination in the oil. Fluid properties were analysed by Viscometer, Rheometer whereas contamination analysis was done by Fourier Transform Infrared spectrometer (FTIR). All tests were performed carefully and their graphs were plotted. Results show that temperature and shearing were two of the several causes for degradation of oil. Viscosity analysis clearly presents that viscosity of oil exponentially decreases with temperature. Viscosity is also decreasing with shear rate at different temperatures. FTIR analysis confirmed that contamination is increasing with continuous use of oil. Temperature and oxidation are the main reasons for degradation. Different composition forming in used gear oil and those were confirmed by infrared spectroscopy absorption table.

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