Faculty Publications
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Item Prediction and Assessment of LHD Machine Breakdowns Using Failure Mode Effect Analysis (FMEA)(Springer Science and Business Media Deutschland GmbH, 2020) Balaraju, J.; Govinda Raj, M.; Murthy, C.S.N.Across the world, production industries are always searching for enhancement of productivity by producing the targeted level of production. In the mining industry, Load Haul Dumper (LHD) is one of the major production equipments generally utilized as an intermediate level technology-based transportation system. LHDs are prone to uneven modes of multiple failures/breakdowns due to harsh operating environmental conditions. This leads to a decrease in the performance of the equipment and increases the maintenance cost, the number of unplanned outages (downtime), as well as loss of production levels. This can be controlled by adequate prediction of machine failures through root cause analysis (RCA). In the present investigation, a well-known fault prediction technique, i.e., failure mode effect analysis (FMEA) was utilized to identify the modes of potential failure, causative factors and recognize the effects of these failures on performance and safety. The risk-based numerical assessment was made by prioritizing the failure modes through the risk priority number (RPN) model. The criticality of failure was estimated using RPN values. They are calculated by the product of risk indexed/ruled parameters [severity (S), occurrence (O) and detection (D)]. Further, an attempt has been made to suggest suitable remedial actions to reduce or eliminate the various potential failures. © 2020, Springer Nature Singapore Pte Ltd.Item Fuzzy-FMEA risk evaluation approach for LHD machine-A case study(Central Mining Institute in Katowice gzyl@gig.katowice.pl, 2019) Balaraju, J.; Govinda Raj, M.; Murthy, C.S.Improvement of productivity has become an important goal for mining industries in order to meet the expected targets of production and increased price competitiveness. Productivity can be improved in different ways. The effective utilization of men and machinery is one such way. Equipment is prone to numerous unexpected potential failures during its operation. Failure Mode and Effect Analysis (FMEA) is one of the suitable techniques of reliability modeling used to investigate the failure behavior of a complex system. In conventional FMEA, the risk level of failures, a ranking of failures and prioritization of necessary actions is made on the basis of estimated Risk Priority Number (RPN). While this approach is easy and uncomplicated, there are a few flaws in acquiring the best approximation of the failure. The estimation of RPN is made by multiplying the Severity (S), Occurrence (O) and Detection (D) alone and irrespective of the degree of importance of each input. Hence, a new risk management approach known as the Fuzzy rule base interface system was proposed in this research in order to mitigate the failures. Fuzzy FMEA is designed in order to acquire the highest Fuzzy RPN value which will be used as the focus of enhancements to reduce the probability of occurrence of some kind of failure for a second time. This study focused on the Root Cause Analysis (RCA) of underground mining machinery such as Load-Haul-Dumper (LHD). 16 potential risks of various sub-system breakdowns were identified in Fuzzy FMEA. The highest value of RPN 168 (for potential failure mode-F9) was obtained for the electrical subsystem (SSE), as was the highest FRPN 117 (F9). There is a difference between the RPN and FRPN values. The FRPN value is obtained from Fuzzy field generation with consideration of the degree of importance of the given input data. In addition, the recommendations were made based on the analysis to reduce the uneven occurrence of failures. © 2019 Central Mining Institute