Artificial intelligence systems for tool condition monitoring in machining: Analysis and critical review

DY Pimenov, A Bustillo, S Wojciechowski… - Journal of Intelligent …, 2023 - Springer
The wear of cutting tools, cutting force determination, surface roughness variations and other
machining responses are of keen interest to latest researchers. The variations of these …

Micromilling: a method for ultra-rapid prototyping of plastic microfluidic devices

DJ Guckenberger, TE De Groot, AMD Wan, DJ Beebe… - Lab on a Chip, 2015 - pubs.rsc.org
This tutorial review offers protocols, tips, insight, and considerations for practitioners
interested in using micromilling to create microfluidic devices. The objective is to provide a …

Prediction of surface roughness in extrusion-based additive manufacturing with machine learning

Z Li, Z Zhang, J Shi, D Wu - Robotics and Computer-Integrated …, 2019 - Elsevier
Additive manufacturing (AM), also known as 3D printing, has been increasingly adopted in
the aerospace, automotive, energy, and healthcare industries over the past few years. While …

An artificial neural network (p, d, q) model for timeseries forecasting

M Khashei, M Bijari - Expert Systems with applications, 2010 - Elsevier
Artificial neural networks (ANNs) are flexible computing frameworks and universal
approximators that can be applied to a wide range of time series forecasting problems with a …

Predicting surface roughness in machining: a review

PG Benardos, GC Vosniakos - International journal of machine tools and …, 2003 - Elsevier
The general manufacturing problem can be described as the achievement of a predefined
product quality with given equipment, cost and time constraints. Unfortunately, for some …

Application of Taguchi method in the optimization of end milling parameters

JA Ghani, IA Choudhury, HH Hassan - Journal of materials processing …, 2004 - Elsevier
This paper outlines the Taguchi optimization methodology, which is applied to optimize
cutting parameters in end milling when machining hardened steel AISI H13 with TiN coated …

Artificial intelligence for automatic prediction of required surface roughness by monitoring wear on face mill teeth

DY Pimenov, A Bustillo, T Mikolajczyk - Journal of Intelligent …, 2018 - Springer
Nowadays, face milling is one of the most widely used machining processes for the
generation of flat surfaces. Following international standards, the quality of a machined …

Design of experiments and focused grid search for neural network parameter optimization

FJ Pontes, GF Amorim, PP Balestrassi, AP Paiva… - Neurocomputing, 2016 - Elsevier
The present work offers some contributions to the area of surface roughness modeling by
Artificial Neural Networks (ANNs) in machining processes. It proposes a method for an …

Hydrogen production optimization from sewage sludge supercritical gasification process using machine learning methods integrated with genetic algorithm

ZU Haq, H Ullah, MNA Khan, SR Naqvi… - … Research and Design, 2022 - Elsevier
Hydrogen production from the supercritical water gasification (SCWG) of sewage sludge
(SS) is a sustainable and efficient process. However, the challenging and intricate task for …

A review of machining monitoring systems based on artificial intelligence process models

JV Abellan-Nebot, F Romero Subirón - The International Journal of …, 2010 - Springer
Many machining monitoring systems based on artificial intelligence (AI) process models
have been successfully developed in the past for optimising, predicting or controlling …