Discrete element approach for mine dump stability analysis

Mine overburden dumps have posed significant safety issues in the operations of various unit operations of open pit min-ing especially the external dumps. The external dumps are composed of a mixture of fragmented rocks and loose soil. Their charac-teristic is comparable to heavily discontinuous solid mass. The conventional approach of limit equilibrium methods provide safety factors for the slope but nothing about the stress-strain characteristics of the large dump mass. The designs of dump location and their respective geometry are integrated for the know-how of the stability characteristics of these dumps. The discrete element method uses a circular disk to represent the granular solid mass and their interactions are described by the Newton’s third law of motion. The displacement is described by the sliding of the circular disk. This work is focused on the modeling efficiency of the discrete element methods to represent the behaviour of mine dump masses with the specified joint plane for the limit equilibrium method. The advantage of the work lies on the ease of information retrieval at any point at the dump mass concerning the stress and strain histories, displacement, failures etc. which when integrated produces a better understanding of the stability of the dump masses.

Numerical analysis of rainfall effects in external overburden dump

The effect of slope angle for external overburden dump in response to average and heavy rainfall has been analyzed using a two dimensional finite difference method of transient water flow through unsaturated–saturated soil. The external dump stability is evaluated for five geomaterial types on the basis of globally accepted safety factor analysis technique, based on shear strength reduction approach using finite difference method. The results obtained from the finite difference method of analysis indicate that the external dump with more than 30° slope angle is greatly influenced by the rainfall under the studied conditions for geomaterial 3, 4 and 5, whereas dumps with geomaterial 1 and 2 remain safe. The analysis shows that major slope failure is out of preview for the studied rainfall conditions.

Industry 4.0 Application in Manufacturing for Real-Time Monitoring and Control

Modern manufacturing aims to reduce downtime and track process anomalies to make profitable business decisions.This ideology is strengthened by Industry 4.0,which aims to continuously monitor high-value manufacturing assets.This article builds upon the Industry 4.0 concept to improve the efficiency of manufacturing systems.The major contribution is a framework for continuous monitoring and feedback-based control in the friction stir welding(FSW)process.It consists of a CNC manufacturing machine,sensors,edge,cloud systems,and deep neural networks,all working cohesively in real time.The edge device,located near the FSW machine,consists of a neural network that receives sensory information and predicts weld quality in real time.It addresses time-critical manufacturing decisions.Cloud receives the sensory data if weld quality is poor,and a second neural network predicts the new set of welding parameters that are sent as feedback to the welding machine.Several experiments are conducted for training the neural networks.The framework successfully tracks process quality and improves the welding by controlling it in real time.The system enables faster monitoring and control achieved in less than 1 s.The framework is validated through several experiments.