Prediction and classification of tool wear and its state in sustainable machining of Bohler steel with different machine learning models

ME Korkmaz, MK Gupta, M Kuntoğlu, AD Patange… - Measurement, 2023 - Elsevier
Abstract Machine learning has numerous advantages, especially in the rapid digitization of
the manufacturing industry that combines data from manufacturing processes and quality …

Impact of mechanical engineering innovations in biomedical advancements

SM Kennedy, A Vasanthanathan, RB Jeen Robert… - In vitro models, 2024 - Springer
The principal objective of the present paper is to meticulously review the family of
biomaterials used in implants. A spectrum of applications of biomaterials in the perspective …

Novel study on investigating the mechanical, microstructure morphological, and dry sliding wear characteristics of grey cast iron GG25 with copper additions for valve …

B Singh, J Singh Grewal, R Kumar, S Sharma… - Frontiers in …, 2024 - frontiersin.org
Introduction: The performance functionality efficacy of the engine's valve train assembly is
considerably affected by the valve guide. Material selection is impacted by the prolonged …

Machine learning models and machinability analysis for comparison of various cooling and lubricating mediums during milling of Hardox 400 steel

A Aslan - Tribology International, 2024 - Elsevier
Martensitic steels are widely used in many areas such as automotive, mining, and
agriculture mostly thanks to their thermal loading ability property. On the other hand, these …

Experimental and machine learning comparison for measurement the machinability of nickel based alloy in pursuit of sustainability

R Binali - Measurement, 2024 - Elsevier
Inconel 718 super alloy, which is widely used in the aerospace industry, has a high fracture
resistance, and withstand to high temperatures. The alloy contains mainly Nickel, Chromium …

Prediction of power consumption and its signals in sustainable turning of PH13-8Mo steel with different machine learning models

H Yurtkuran, ME Korkmaz, MK Gupta, H Yılmaz… - … International Journal of …, 2024 - Springer
Due to extensive distribution and huge demand of energy efficient processes, the energy-
saving of machining processes draws more and more attention, and a significant variety of …

Optimizing CNC turning of AISI D3 tool steel using Al₂O₃/graphene nanofluid and machine learning algorithms

LD Gemechu, DA Efa, R Abebe - Heliyon, 2024 - cell.com
Abstract Turning AISI (American Iron and Steel Institute) D3 tool steel can be challenging
due to a lack of optimal process parameters and proper coolant application to achieve high …

Optimizing end milling parameters for custom 450 stainless steel using ant lion optimization and TOPSIS analysis

C Devi, SK Mahalingam, R Cep… - Frontiers in Mechanical …, 2024 - frontiersin.org
The current research examines the effectiveness of cryogenically treated (CT) tungsten
carbide cutting inserts on Custom450 stainless steel using multi-objective soft computing …

Prediction of tool wear during micro-milling Inconel 718 based on long short-term memory network

X Lu, F Zeng, K Xv, Y Zhang, SY Liang - Precision Engineering, 2024 - Elsevier
Tool wear is inevitable due to the thermal-mechanical coupling in micro-milling, Micro-
milling of difficult-to-cut material Inconel 718 leads to significant flank wear on the cutting …

Triboinformatic Machine Learning Model for Frictional Behavior and Wear Volume Loss Prediction of SS316L Alloy Clad with WC/NiCrBSi

LM Birada, V Pullela, BR Thella - Journal of Bio-and Tribo-Corrosion, 2024 - Springer
This study uses a laser cladding approach to clad NiCrBSi and reinforced WC particles on
SS316L. The wear characteristics of a laser cladded material were examined under dry …