Recent advances on machine learning applications in machining processes
F Aggogeri, N Pellegrini, FL Tagliani - Applied sciences, 2021 - mdpi.com
This study aims to present an overall review of the recent research status regarding Machine
Learning (ML) applications in machining processes. In the current industrial systems …
Learning (ML) applications in machining processes. In the current industrial systems …
Prediction of surface roughness using machine learning approach in MQL turning of AISI 304 steel by varying nanoparticle size in the cutting fluid
Surface roughness is considered as an important measuring parameter in the machining
industry that aids in ensuring the quality of the finished product. In turning operations, the …
industry that aids in ensuring the quality of the finished product. In turning operations, the …
Landslide susceptibility zonation using statistical and machine learning approaches in Northern Lecco, Italy
This study deals with landslide susceptibility map** in the northern part of Lecco Province,
Lombardy Region, Italy. In so doing, a valid landslide inventory map and thirteen …
Lombardy Region, Italy. In so doing, a valid landslide inventory map and thirteen …
Artificial intelligence prediction of the mechanical properties of banana peel-ash and bagasse blended geopolymer concrete
This research explores the application of Artificial Intelligence (AI) techniques to assess the
mechanical properties of geopolymer concrete made from a blend of Banana Peel-Ash …
mechanical properties of geopolymer concrete made from a blend of Banana Peel-Ash …
Study of a multicriterion decision-making approach to the MQL turning of AISI 304 steel using hybrid nanocutting fluid
The enormous use of cutting fluid in machining leads to an increase in machining costs,
along with different health hazards. Cutting fluid can be used efficiently using the MQL …
along with different health hazards. Cutting fluid can be used efficiently using the MQL …
Applying Bayesian Optimization for Machine Learning Models in Predicting the Surface Roughness in Single‐Point Diamond Turning Polycarbonate
This paper deals with the prediction of surface roughness in manufacturing polycarbonate
(PC) by applying Bayesian optimization for machine learning models. The input variables of …
(PC) by applying Bayesian optimization for machine learning models. The input variables of …
Predicting the tool wear of a drilling process using novel machine learning XGBoost-SDA
Tool wear negatively impacts the quality of workpieces produced by the drilling process.
Accurate prediction of tool wear enables the operator to maintain the machine at the …
Accurate prediction of tool wear enables the operator to maintain the machine at the …
[HTML][HTML] Enhanced prediction of corrosion rates of pipeline steels using simulated annealing-optimized ANFIS models
Accurate prediction of corrosion rates is crucial for preventing infrastructure failures,
reducing maintenance costs, and ensuring operational safety. Traditional models often …
reducing maintenance costs, and ensuring operational safety. Traditional models often …
Prediction of surface roughness of an abrasive water jet cut using an artificial neural network
The study's primary purpose was to explore the abrasive water jet (AWJ) cut machinability of
stainless steel X5CrNi18-10 (1.4301). The study analyzed the effects of such process …
stainless steel X5CrNi18-10 (1.4301). The study analyzed the effects of such process …
Estimation and optimization of tool wear in conventional turning of 709M40 alloy steel using support vector machine (SVM) with Bayesian optimization
Cutting tool wear reduces the quality of the product in production processes. The
optimization of both the machining parameters and tool life reliability is an increasing …
optimization of both the machining parameters and tool life reliability is an increasing …