Open AccessPrediction of breakdown hours of load haul dumper by long short term memory network
Author(s) -
Vaibhav Bisht,
Shubham Kumar,
Anil K. Agrawal,
Mohd Ahtesham Hussain Siddiqui,
Somnath Chattopadhyaya
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1104/1/012006
Subject(s) - profitability index , term (time) , computer science , reliability engineering , artificial neural network , work (physics) , engineering , mechanical engineering , machine learning , business , finance , physics , quantum mechanics
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.