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132 articles for “Machining parameters optimization”
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Optimum Machining Parameters for Al 7075 Hybrid Metal Matrix Composites Using Multi-objective Optimization Technique and the Modified Taguchi Approach
Abstract: Lightweight composite materials with improved mechanical properties are widely used in industries. There is a need to obtain optimum machining parameters of such hybrid composites. This paper uses reliable multi-objective optimization technique and modified Taguchi approach to determine optimal machining parameters such as speed (NS) varying from 1000 rpm to 1500 rpm, feed rate (FR) from 0.10 mm/rev to 0.20 mm/rev, depth-of-cut (DC) varied from 0.5 mm to 1.5 mm …
Published in Journal of Polymer & Composites · Vol. 11, Issue 8, 2023 · pp. 269–278 Read article
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Experimental Investigation and Optimization of Machining Parameters for Al6351 Alloy Using a Modified Taguchi Approach
Abstract: Machining processes encompass both conventional and non-conventional techniques and optimizing machining parameters is crucial for achieving high-quality outcomes. However, simplifying these processes remains a significant challenge. This study focuses on determining the optimal machining parameters—cutting speed, feed rate, and depth-of-cut to enhance performance characteristics in Al6351 alloy plates. The parameters evaluated include surface roughness (Ra), material removal rate (MRR), resultant forces (RF), and temperature at the tool- workpiece interface (Temp). …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1463–1481 Read article
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Dynamic Performance Enhancement of Polymer Composites through Metaheuristic machinining optimization
Abstract: This work aims to provide an optimization of meta-heuristic algorithms in order to improve the dynamic behavior of composite materials utilized in various practical engineering tasks. Based on the Comprehensive literature review it has been observed that composite sandwich panels with PVC foam cores accomplished mechanical characteristics superior than those ones that were produced on PU foam core mainly in flexural, compression, and impact tests Thus the study establishes the …
Published in Journal of Polymer & Composites · Vol. 12, Issue 2, 2024 · pp. 114–129 Read article
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Optimization of Machining Parameters of EN-27 Material Using Wire Electric Discharge Machining (WEDM)
Abstract: The optimization of Wire Electrical Discharge Machining (WEDM) parameters for EN-27 alloy steel, a high-strength material widely utilized in mechanical and structural applications, is the subject of this study's methodical analysis. Due to its hardness and poor machinability by conventional methods, WEDM is preferred for achieving precise dimensional accuracy and surface integrity. The primary objective of this work is to enhance machining performance by identifying optimal process parameters influencing Material …
Published in Journal of Production Research & Management · Vol. 16, Issue 1, 2026 · pp. 32–36 Read article
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Machine Learning Driven Mobile Price Prediction Using Feature Selection and Parameter Optimization
Abstract: Machine learning calculations are utilized in many fields like money, training, industry, medication, and online business. Machine learning calculations show execution contrasts relying upon the dataset and handling steps. Picking the right calculation, preprocessing and post-handling techniques have incredible significance in accomplishing great outcomes. The Random Forest classifier, K-nearest neighbor classifier, and support vector machine methods are evaluated to forecast mobile phone price categories. The “prediction” dataset which is taken …
Published in Current Trends in Information Technology · Vol. 14, Issue 3, 2024 · pp. 18–25 Read article
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Optimal Abrasive Jet Machining Parameters for Glass Fiber Reinforced Plastics
Abstract: Abrasive jet machining (AJM) is a best choice for processing of glass fiber reinforced plastics (GFRP). Inherent to the nonlinear behavior of performance characteristics during repeated experiments are inevitable variations, attributed to measurement errors and unknown influencing input variables. This study employs the Taguchi method with an orthogonal array to systematically identify optimal input variables through a limited number of experiments. The paper introduces a direct and reliable Taguchi-based multi-objective …
Published in Journal of Polymer & Composites · Vol. 11, Issue 8, 2023 · pp. 247–255 Read article
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Explainable Machine Learning for Process Parameter Optimization in Gradient 3D-Printed Polymer Composites
Abstract: The explainable machine learning-based structure may be employed to achieve a favorable process parameter of the graduate 3D-printed polymer composite structures to improve the mechanical and thermal properties without compromising the transparency of the decisions made during the fabrication process. Gradient composite specimens were made by systematically varied process parameters like nozzle temperature, raster orientation, deposition speed, gradient transition rate and fused filament fabrication. A predictive model of tensile strength …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 847–866 Read article
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Optimization of Sustainable Electrochemical Machining Parameters for Polymer based Materials Using AHP Integrated TOPSIS Method
Abstract: The current paper describes the use of the AHP-TOPSIS method to optimize process parameters in sustainable electrochemical machining of polymer composites. Combine lightweight polymer matrices with reinforcing particles or fibers such as TiB₂, SiC, or Al₂O₃, offering high strength-to-weight ratio, corrosion resistance, and design flexibility, making them ideal for aerospace and automotive applications. Non-conductive and heterogeneous nature poses challenges during electrochemical machining, as it affects current distribution and material removal …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1048–1059 Read article
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Machine Learning Assisted Optimization of Nanoscale MOSFET Parameters Using TCAD Simulation
Abstract: This paper presents a machine learning (ML) assisted framework for the multi-objective optimization of nanoscale bulk n-channel metal-oxide-semiconductor field-effect transistors (nMOSFETs) with a 10 nm physical gate length, high-k HfO₂ gate dielectric, and TiN metal gate. Technology computer-aided design (TCAD) simulations employing drift-diffusion transport, Shockley-Read-Hall recombination, Lombardi mobility degradation, and density- gradient quantum correction models are used to generate a parametric dataset of 2,400 device configurations spanning gate length (L), …
Published in Journal of Microelectronics and Solid State Devices · Vol. 13, Issue 1, 2026 · pp. 10–19 Read article
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Integration of Taguchi and MCDM Techniques for the Optimization of Experimental Parameters in Electrical Discharge Machining: A Research
Abstract: Electric discharge machining (EDM) represents a non-conventional approach to machining, particularly beneficial for processing hard-to-machine materials or components with high length-to-diameter ratios or intricate shapes. Widely employed across various industries such as automotive, chemical, aerospace, biomedical, and tool and die, EDM offers a unique method for achieving precise shapes and dimensions. Unlike traditional machining methods where form is attained through the interaction of the tool and workpiece, EDM operates without …
Published in Trends in Mechanical Engineering & Technology · Vol. 14, Issue 1, 2024 · pp. 6–14 Read article
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Intelligent Optimization of Drilling Parameters in Polymer Composites using Machine Learning and Metaheuristic Techniques
Abstract: The study tests different ways to use ML and metaheuristic algorithms to determine the best drilling parameters for polymer matrix composites. The research uses a composite matrix made from 55.25% vinyl ester, 44.0% Nickel–Phosphorous coated glass fiber and 0.75% Al₂O₃ nanowires which are tested for tensile strength (64.57 MPa), flexural strength (85.86 MPa) and impact strength (71.79 kJ/m²). By applying a Taguchi orthogonal array, it is observed that a slower …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1795–1810 Read article
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Parametric Optimization of Aluminum Alloy 6061 Using Wire-EDM for Automotive Applications: A Taguchi-Based Approach
Abstract: Machining hard materials with complex geometries presents numerous challenges, often requiring the use of non-traditional methods such as wire Electric Discharge Machining (EDM). However, wire EDM machines operate at slow speeds, and increasing the speed can negatively impact surface finish, making it a difficult task. The ongoing research investigates the machinability study of Aluminum Alloy 6061 using wire EDM, emphasizing the optimization of process parameters to enhance machining performance and …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 293–302 Read article
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Multi-Response Optimization of Turning Parameters with Vikor-Entropy Method on Machining of AA6061-TiB2 In-Situ Composites
Abstract: In the manufacturing and metal cutting industries, the quality of the surface and strength is essential in defining the surface finish; an excellent surface finish indicates excellent quality in the product. The influence of machining parameters speed, feed and depth of cut on responses like material removal rate, surface roughness and Power consumption on turning of AA6061-TiB2 composites is investigated using the VIKOR-ENTROPY method. The effects of changing parameters on …
Published in Journal of Polymer & Composites · Vol. 11, Issue 8, 2023 · pp. 256–268 Read article
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Performance Evaluation of Eco-friendly Cutting Fluid in Machining Process—An Approach towards Environmentally Friendly Production
Abstract: The machining industry's evolving environmental consciousness has prompted a growing demand for cutting fluids devoid of chlorine and sulphur, thus fostering sustainable machining practices. This surge in demand is driven by mounting apprehensions over environmental contamination and worker safety. As the industry transitions to modern cutting fluids, it becomes imperative to comprehend their effectiveness and the optimal machine parameters required for their deployment in the turning process. In our current …
Published in Journal of Polymer & Composites · Vol. 11, Issue 12, 2023 · pp. 149–160 Read article
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The Convergence of AI and Composites - A Review Anchored in Patent Trends
Abstract: The integration of artificial intelligence (AI) and machine learning (ML) techniques is revolutionizing the design, analysis, and optimization of polymer (PC/FRP), metal (MC), and ceramic matrix composites (CC). Techniques such as artificial neural networks (ANN), deep learning (DL), genetic algorithms (GA), and physics-informed machine learning (PIML) are employed to enhance property estimation, process optimization, and predictive modeling. These AI-driven frameworks enable virtual testing, application-specific material design, and real-time decision-making, while …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 182–198 Read article
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Optimization of Surface Roughness and Material Removal Rate in Turning of Al-6061 Using Taguchi Methodology, Fuzzy Logic, and Measurement System Analysis
Abstract: The optimization of machining parameters please a crucial role in improving product quality and productivity in manufacturing processes. This study focuses on the turning of aluminium 6061 alloy, aiming to optimize two key performance measures: Surface Roughness and Material Removal Rate. An integrated approach combining to Taguchi methodology, fuzzy logic and measurement system analysis (MSA) is proposed to achieve this objective. Taguchi design of experiments using and L9 orthogonal array …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 4, Issue 1, 2026 Read article
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Dimensional Investigation of Material Extrusion Based AM Part
Abstract: Now a day’s additive manufacturing plays a vital role in industrial application. Material Extrusion based 3D printed parts often face inherent limitations in quality, such as geometric inaccuracies, surface roughness, and reduced strength, especially when compared to those made through traditional or more refined manufacturing methods. However, this system provides notable advantages for producing parts from materials like ABS by optimizing critical material extrusion based AM machine process parameters, such …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 442–452 Read article
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Strategic Optimization of CNC Machining in Production Systems: A Managerial Review of Methods, Metrics, and Industry 4.0 Integration
Abstract: Computer numerical control (CNC) machining has significantly influenced modern production systems by enabling higher efficiency, quality, and sustainability. As industrial operations strive for leaner production and strategic competitiveness, optimization of machining parameters—including cutting speed, feed rate, depth of cut, and tool path strategies—has emerged as a cornerstone of production planning. This review evaluates the optimization methodologies developed from 2015 to 2025, spanning traditional mathematical models to artificial intelligence (AI)-driven metaheuristic …
Published in Journal of Production Research & Management · Vol. 15, Issue 2, 2025 · pp. 25–30 Read article
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Optimization of Process Parameters for AISI 304 Using Micro-EDM Drilling Process Through Response Surface Method
Abstract: The increasing demand for micro-parts in high-tech products, such as micro-electromechanical systems (MEMS) applications and micro-electronic devices, has driven significant advancements in micromachining technologies. Among the various micromachining processes, the fabrication of accurate microholes and pins is critical for the performance and reliability of miniature components. Micro-hole drilling plays a vital role by enabling the production of deep holes with excellent straightness, roundness, and surface quality. It is widely used …
Published in International Journal of Manufacturing and Production Engineering · Vol. 3, Issue 1, 2025 · pp. 37–47 Read article
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Application of Grey Wolf Optimizer (GWO) strategy for Malware Analysis
Abstract: The ever-evolving landscape of cybersecurity necessitates continuous advancements in malware analysis techniques. This study explores the deployment of the Grey Wolf Optimizer (GWO) algorithm as a novel bio-inspired optimization mechanism to address the challenges posed by modern malware threats. The primary objective is to enhance various facets of malware analysis, including feature selection, parameter optimization, and the overall efficacy of malware detection models. The study begins by introducing the GWO …
Published in International Journal of Wireless Security and Networks · Vol. 1, Issue 2, 2023 · pp. 43–53 Read article