...Mehmet Albaşkara Purpose This study aims to analyze key performance metrics such as surface roughness and material removal rate in the WEDM of Hardox 450 steel using artificial intelligence-based (ANN) and statistical (RSM) modeling approaches. The study also aims to establish a multidisciplinary...

... mechanisms during the milling of AISI 316 Ti alloy. Furthermore, the study aims to determine the estimation method that gives optimum results by estimating the output parameters using response surface methodology (RSM), artificial neural network (ANN) and adaptive network-based fuzzy inference system (ANFIS...

... consumption (SCEC). Experimental data were modeled using machine learning methods of regression analysis and artificial neural networks (ANN). Findings As a result, the lowest SEC and SCEC values, that is the highest energy efficiency, were obtained at 12 mm tool diameter, 75 m/min cutting speed and 0.25...

... orthogonal array. The experimental measurement findings for Ra and AV were adjusted utilizing the Grey Relational Analysis (GRA), the Response Surface Method (RSM) and Artificial Neural Networks (ANN) to generate prediction values. SEM detected drill-tip adhesions and chip morphology and they were analyzed...

... steel tubular (CFST) columns have gained popularity in construction in recent decades as they offer the benefit of constituent materials and cost-effectiveness. Artificial Neural Networks (ANNs), Support Vector Machines (SVMs), Gene Expression Programming (GEP) and Decision Trees (DTs) are some...

... increased enormously. The purpose of this paper is to study the surface roughness during the turning of Al-10%SiC and Al-5%SiC-5%Gr composites under different cutting conditions. Design/methodology/approach Artificial neural network (ANN) has been effectively employed in solving problems with effortless...

...Prasad Ramchandra Baviskar; Vinod B. Tungikar Purpose – The purpose of this paper is to address the determination of crack location and depth of multiple transverse cracks by monitoring natural frequency and its prediction using Artificial Neural Networks (ANN). An alternative to the existing...

... and it is expensive than nickel base super alloys for such applications. The purpose of this paper is to deal with the optimization of the FW parameters of super austenitic stainless steel using artificial neural network (ANN) simulation and particle swarm optimization (PSO). Design/methodology/approach...

...H. Ahamed; V. Senthilkumar Purpose The aim of this paper is to develop a suitable artificial neural network (ANN) model that fits best in predicting the experimental flow stress values to the closet proximity for mechanically alloyed Al6063/0.75Al2O3/0.75Y2O3 hybrid nanocomposite. Design...