Optimizing Quarry Equipment Maintenance Through Reconditioning of Components Subject to Abrasive Wear | Chapter 1 | Engineering Research: Perspectives on Recent Advances Vol. 9

 

This study rigorously analyses the operational reliability and maintainability of critical metal components susceptible to abrasive wear within the technological equipment of the Pătârș basalt quarry. By integrating tribological wear parameter analysis with robust reliability and maintainability modelling, the research quantifies their direct impact on equipment efficiency and lifespan. We assessed components such as the Komatsu WA470 front loader bucket knife, Komatsu HB365 excavator bucket teeth, and the sorting station trough, alongside evaluating alternative materials like Hardox 400 steel and Pucest panels with perforated metallic inserts. Our methodology employed statistical distributions (lognormal and three-parameter Weibull) for reliability and maintainability, complemented by laboratory tribological tests on rock-metal pairs to quantify wear. Key findings reveal significant reliability degradation across all components with increased operating time, necessitating proactive maintenance. Notably, weld reconditioning proved highly effective, achieving a 68% increase in the operational lifespan of reconditioned bucket teeth. Furthermore, an economic analysis demonstrated that while alternative materials like Hardox 400 and Pucest have higher initial costs, their significantly extended operational lifespans (achieving 80% reliability for 157 and 251 days, respectively, compared to 105 days for the original material) promise substantial long-term cost-effectiveness through reduced replacement frequency and minimised downtime. This comprehensive study provides a robust framework for optimising quarry operations by strategically evaluating critical component reliability and implementing targeted maintenance interventions.

Author(s) Details

Mihaela TODERAȘ

Mining Engineering, Surveying and Civil Engineering Department, Faculty of Mines, University of Petrosani, 332006 Petrosani, Romania.

 Vlad Alexandru FLOREA|
Department of Mechanical, Industrial and Transportation Engineering, University of Petrosani, 332006 Petrosani, Romania.

 

Please see the book here:- https://doi.org/10.9734/bpi/erpra/v9/5788

Taguchi and Neural Network Analysis for Predicting Abrasive Wear Behavior of Carbon Epoxy Composites | Chapter 3 | Recent Progress in Science and Technology Vol. 7

 In this study, an approach for calling the three-body nasty wear behavior of unfilled and element filled element fabric supported epoxy composite using two displaying techniques - Taguchi reasoning and artificial interconnected system are presented. A set of experiments were transported using an orthogonal array established Taguchi techniques to achieve data in a reserved manner. The results showed that the adding of graphite coarse into carbon binding material composite led to a decrease in its caustic wear resistance, and the wear deficit increased accompanying an increase in abrading distance and loads. To investigate the effect of control limits on the wear behavior of the composites, an reasoning of variance was acted, and the S/N ratio was determined. The results found that the normal load had the best physical in addition to statistical influence on the nasty wear of the composites followed by abrading distance and stuffing content. To predict the wear possessions of composites as a function of testing environments, 3-[5]1-1 neural network architecture accompanying Levenberg Marquardt (LM) training treasure was used. By equating the correlations obtained by Taguchi reversion analysis and affected neural network accompanying the experimental results it was raise that the artificial neural network thinks the wear rate better than regression reasoning. Therefore, a well-trained pretended neural network system maybe very helpful in judging the weight deficit in the complex three-body abrasive wear position of polymer composites.

Author(s) Details:

K. Sudarshan Rao,
Department of Mechanical Engineering, Shri Madhwa Vadiraja Institute of Technology and Management, Bantakal, Udupi, Karnataka, India.

Please see the link here: https://stm.bookpi.org/RPST-V7/article/view/9949