Development of operations in waterjet technology: A review

PM Thakur, DN Raut, PR Lade… - Advances in Materials …, 2024 - Taylor & Francis
Waterjet technology has gained much attention due to its ability to cut almost every material.
The development of operations like milling, spot welding, polishing, etc. has further …

Thermal conductivity prediction of sintered reaction bonded silicon nitride ceramics using a machine learning approach based on process conditions

R Furushima, Y Nakashima, Y Zhou, K Hirao, T Ohji… - Ceramics …, 2024 - Elsevier
Thermal conductivity (TC) of sintered reaction bonded silicon nitride (SRBSN) ceramics was
predicted from process conditions using support vector regression (SVR) as a machine …

Performances of different abrasive materials during swirling impeller abrasive water jet drilling of granite

H Li, Z Huang, J Li, K Cheng, T Jiang… - Rock Mechanics and Rock …, 2023 - Springer
Swirling impeller abrasive water jet (SAWJ) is a viable alternative for larger-diameter drilling
of mining and oil and gas extraction. Abrasive material plays an important role in eco …

Reliability optimization of micro-milling cutting parameters using slime mould sequence algorithm

P Ding, X Huang, X Zhang, Y Li, C Wang - Simulation Modelling Practice …, 2022 - Elsevier
An optimal selection of cutting parameters is of great significance for increasing machining
efficiency, improving accuracy, and reducing the cost of micro-milling. An accurate …

Machine learning-based modelling and meta-heuristic-based optimization of specific tool wear and surface roughness in the milling process

S Pedrammehr, M Hejazian, MR Chalak Qazani… - Axioms, 2022 - mdpi.com
The purpose of this research is to investigate different milling parameters for optimization to
achieve the maximum rate of material removal with the minimum tool wear and surface …

Grinding wheel specification cybernetic recommendation with multi-task multi-imbalanced learning in smart manufacturing system

KC Yao, TL Chen, JC Chen, CR Li - Advanced Engineering Informatics, 2024 - Elsevier
Over the years, the grinding wheels industry has played a crucial role in mechanical
engineering. Grinding wheel specification is composed of various factors such as abrasive …

Multilayer artificial intelligence for thermal-conductivity prediction of silicon nitride ceramics from powder processing conditions and predicted densities

R Furushima, Y Nakashima, Y Zhou, K Hirao, T Ohji… - Ceramics …, 2024 - Elsevier
In this study, we first developed an artificial intelligence (AI) that estimates relative densities
(RD) of silicon nitride ceramics from the process conditions. We then constructed a multi …

Microstructural basis of AI predictions for material properties: A case study of silicon nitride ceramics using t‐SNE

R Furushima, Y Nakashima… - Journal of the …, 2025 - Wiley Online Library
Artificial intelligence (AI) models such as a convolutional neural network (CNN) are powerful
tools for predicting the properties of materials from their microstructural images, etc. It is …

Study of different cutting fluids effect on the coupling characteristics of milling noise-vibration and surface roughness of TA2 pure titanium

S Li, Y Li, Y Li, D Chen - Journal of Manufacturing Processes, 2024 - Elsevier
With the increasing use of titanium alloys, it is essential to improve cutting efficiency.
However, there are various problems such as high noise, strong vibration and difficulty to …

Multi-performance optimization for AWJ drilling process in cutting of ceramic tile: BBD with EOBL-GOA algorithm

A Tamilarasan, A Renugambal… - … Modeling in Materials …, 2023 - emerald.com
Purpose The goal of this study is to determine the values of the process parameters that
should be used during the machining of ceramic tile using the abrasive water jet (AWJ) …