Advanced data collection and analysis in data-driven manufacturing process
The rapidly increasing demand and complexity of manufacturing process potentiates the
usage of manufacturing data with the highest priority to achieve precise analyze and control …
usage of manufacturing data with the highest priority to achieve precise analyze and control …
Deep learning-based tool wear prediction and its application for machining process using multi-scale feature fusion and channel attention mechanism
X Xu, J Wang, B Zhong, W Ming, M Chen - Measurement, 2021 - Elsevier
Tool wear is a key factor in the cutting process, which directly affects the machining precision
and part quality. Accurate tool wear prediction can make proper tool change at an early …
and part quality. Accurate tool wear prediction can make proper tool change at an early …
[HTML][HTML] Effect of machinability, microstructure and hardness of deep cryogenic treatment in hard turning of AISI D2 steel with ceramic cutting
This study examined the hard turning of AISI D2 cold work tool steel subjected to deep
cryogenic processing and tempering and investigated the effects on surface roughness and …
cryogenic processing and tempering and investigated the effects on surface roughness and …
Dynamic damping of machining vibration: a review
Machining is one of the important manufacturing processes used in industry. Dynamic
interaction between the tool and the workpiece may lead to the occurrence of chatter …
interaction between the tool and the workpiece may lead to the occurrence of chatter …
[HTML][HTML] A data-driven approach to predict the compressive strength of alkali-activated materials and correlation of influencing parameters using SHapley Additive …
This research used gene expression programming (GEP) and multi expression
programming (MEP) to determine the compressive strength (CS) of alkali-activated material …
programming (MEP) to determine the compressive strength (CS) of alkali-activated material …
Convolution and long short-term memory hybrid deep neural networks for remaining useful life prognostics
Z Kong, Y Cui, Z Xia, H Lv - Applied Sciences, 2019 - mdpi.com
Reliable prediction of remaining useful life (RUL) plays an indispensable role in prognostics
and health management (PHM) by reason of the increasing safety requirements of industrial …
and health management (PHM) by reason of the increasing safety requirements of industrial …
Self-optimizing machining systems
In this paper the idea of Self-Optimizing Machining Systems (SOMS) is introduced and
discussed. Against the background of Industry 4.0, here the focus is the technological level …
discussed. Against the background of Industry 4.0, here the focus is the technological level …
Multi-objective optimization of seeding performance of a pneumatic precision seed metering device using integrated ANN-MOPSO approach
CM Pareek, VK Tewari, R Machavaram - Engineering Applications of …, 2023 - Elsevier
Uniform seed spacing within the row is the most desirable prerequisite for better crop yield.
The seeding uniformity of a pneumatic seed metering device is significantly affected by its …
The seeding uniformity of a pneumatic seed metering device is significantly affected by its …
Improving the accuracy of machine-learning models with data from machine test repetitions
A Bustillo, R Reis, AR Machado… - Journal of Intelligent …, 2022 - Springer
The modelling of machining processes by means of machine-learning algorithms is still
based on principles that are especially adapted to mechanical approaches, in which very …
based on principles that are especially adapted to mechanical approaches, in which very …
Study on machinability of additively manufactured and conventional titanium alloys in micro-milling process
Abstract Capability of Additive Manufacturing (AM) technology in the production of complex
parts with high flexibility has led to the growing interest in their application as an alternative …
parts with high flexibility has led to the growing interest in their application as an alternative …