NDLI: Reliability-based preventive maintainability analysis of shovel-dumper system in surface coal mine using ANN and isograph reliability workbench

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Reliability-based preventive maintainability analysis of shovel-dumper system in surface coal mine using ANN and isograph reliability workbench

Content Provider	Semantic Scholar
Author	Kumar, Narayanan Harish Choudhary, R. N. P. Murthy, Ch. S. N.
Copyright Year	2018
Abstract	Received: 2 October 2018 Accepted: 23 November 2018 Shovel-Dumper system is utilized as a loading and transporting machines for intermediate mechanization in surface mining. For survival in the exceptional competition in the global business environment in recent years, it is basic that the Shovel – Dumper system should be reliable and maintained adequately and effectively. This paper seeks to study the reliability, availability, and preventive maintenance of one shovel and four dumpers in a surface coal mine with failure and repair data by Isograph Reliability Workbench (RWB) in the case of a non-parametric statistical method such as K-S test. The constraints and reasons for machine unavailability are outlined. The reliability and availability of the shovel-dumper system are evaluated and also evaluated the maintenance time interval to improve the 80% of reliability for each system. The reliability, availability and preventive maintenance have been validated with the artificial neural network (ANN). ANN model is then connected to a reliability method, K-S test to predict the failure probability of shovel and dumper.
File Format	PDF HTM / HTML
DOI	10.18280/mmep.050414
Alternate Webpage(s)	http://iieta.org/sites/default/files/Journals/MMEP/05.04_14.pdf
Alternate Webpage(s)	https://doi.org/10.18280/mmep.050414
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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