International Journal of Machining and Machinability of Materials (14 papers in press)

Regular Issues

• Machinability study of hybrid epoxy/ (BaTiO3 + CaCu3Ti4O12) composite in abrasive jet machining  
  by Ajit Kumar Behera, Punyapriya Mishra, Trupti Ranjan Mahapatra, Punyatoya Mishra, Debadutta Mishra 
  Abstract: This study investigates the machinability characteristics of epoxy composites reinforced with barium titanate (BT: BaTiO3) and calcium copper titanate (CCT: CaCu3Ti4O12) using the abrasive jet machining (AJM) process. Various proportions of BT and CCT (BT:CCT=100:0, 40:60, 50:50, 60:40, 0:100) were mixed with epoxy resin matrix in a 20:80 ratio, forming requisite composite samples via compression molding. The density, microhardness, tensile, flexural, and impact strengths of the samples were measured according to ASTM standards. While density decreased as BT was replaced by CCT, the hybridization of BT and CCT exhibited improved mechanical properties. Subsequently, the machinability of these epoxy-ceramic hybrid composites was then examined using AJM with 150 mesh size silicon carbide abrasive particles. The rate of material removal (RMR) and surface roughness (Ra) were measured according to the Taguchi design of experiments, and the significance of control factors (BT and CCT proportions, pressure, and stand-off distance) was determined through ANOVA. Optimal settings of these factors for individual responses were identified, and grey relational analysis (GRA) was used for simultaneous optimization of performance characteristics.
  Keywords: Epoxy-ceramic composite; BT; CCT; Taguchi methodology; Abrasive Jet Machining; GRA.
  DOI: 10.1504/IJMMM.2025.10069321
   
  
• EFFECT OF COOLED COMPRESSED AIR ON THE MACHINING FORCE AND SURFACE ROUGHNESS GENERATED BY FACE MILLING OF CW50/PEEK  
  by Carlos Aita, André Souza, Émerson Passari, Arnaldo Gonzalez, Guilherme Schirmer, Jeferson Jesus 
  Abstract: This study examines the effect of cooled compressed air (CCA) at -60
  Keywords: Face milling; CW50/PEEK; Machining force; Surface roughness; Box-Behnken Design; Abbott-Firestone Curve; Probability Density Function; SEM.
  DOI: 10.1504/IJMMM.2025.10069852
   
  
• Optimizing Tool Flank Wear in Turning Operations Using Non-Edible Vegetable Oil-Based Cutting Fluids  
  by Balwan Singh, Tushar Gupta, Pankaj Kumar Singh, Narender Singh, Gurpreet Singh Saini 
  Abstract: The study assessed the efficacy of cutting fluids derived from non-edible vegetable oils, focusing on flood cooling during mild steel turning. Karanja and neem oils were blended in varying ratios, and MIRANDA S-400 high-speed steel tools measured flank wear during machining. The Taguchi method, employing an L9 orthogonal array, analysed the impact of cutting fluid on tool flank wear, correlating variables like cutting speed, cutting feed, and depth of cut. Statistical techniques including S/N ratio and Analysis of Variance were utilized, with Minitab 18 software for analysis. Optimal machining parameters (v1-f2-d1-CF1) were identified, resulting in a 48.30% reduction in tool flank wear. This research provides valuable insights into minimizing wear on tool flanks during machining processes.
  Keywords: Taguchi Method; Tool Flank Wear; Lathe Turning; Cutting Fluid; Karanja; Neem.
  DOI: 10.1504/IJMMM.2025.10070427
   
  
• Effect of deep cryogenic treatment on different graphite electrodes for EDM performance  
  by Israa Dheyaa Khalaf Alrubaye, Gualtiero Fantoni, Davide Melis, Massimo Arcion, Dario Clori, Francesco Grazzi, Leonardo Del Rosso 
  Abstract: In the present investigation, cryogenic treatment (CT) has been used to enhance the efficiency of electrical discharge machining (EDM). Different cylindrical electrodes, made of high-quality (QG) and standard (SG) graphite have been cryogenically treated at temperatures of 185 C and 196 C with varying soaking durations using liquid nitrogen and helium gas as a cooling system. Raman spectroscopy has been employed to monitor the microstructural changes in the graphite material. The impact of cryogenic treatment on the graphite electrode microstructure has been investigated using a scanning electron microscope (SEM). While the microstructure of the machined workpiece has been investigated using optical microscopy (OM). The EDM experiments showed that cryogenically treated standard graphite electrode for 24 h (liquid nitrogen system) reduced the total machining time by 45% and machined surface roughness by 15%, compared to untreated electrode. These findings highlight the benefits of cryogenic treatment for enhancing EDM performance when using graphite electrodes.
  Keywords: deep cryogenic treatment; electrical discharge machining; EDM; graphite electrode; cooling system; Raman spectroscopy; machined surface roughness.
  DOI: 10.1504/IJMMM.2025.10070925
   
  
• Investigation on machinability characterisation of Al7075-fly ash composite using Taguchi approach  
  by Ankit Verma, Pardeep Kumar Sood, Sant Ram Chauhan, Kali Dass 
  Abstract: In this research investigation, stir casting was used to fabricate metal matrix composites (MMCs) using (150 um) fly ash particulates as reinforcement and Al7075 aluminium alloy as the matrix. Machining tests were performed on a CNC turning machine with cermet tool insert. The addition of fly ash improved tensile strength and hardness. Microstructural analysis shows a uniform dispersion of particles. The effects of process parameters on main cutting force, power consumption and surface roughness were investigated using a L9 orthogonal array and ANOVA. Main cutting force, power consumption and surface roughness were compared to cutting speed, feed rate and depth of cut. The results showed straight proportionality with cutting speed (100180 m/min), feed rate (0.100.16 mm/rev), depth of cut (0.10.3 mm) and increased with reinforcement (2.57.5 wt. %). Microstructure, chip formation and tool wear were analysis using scanning electron microscopy.
  Keywords: metal matrix composite; Al7075; fly ash; cutting force; power consumption; surface roughness; chip formation; tool wear.
  DOI: 10.1504/IJMMM.2025.10070926
   
  
• Optimisation of surface roughness and tool wear in high-speed milling machining of INCONEL 718 using uncoated tools  
  by A.K.M. Nurul Amin, Sinthea Khatun, Tasfia Saba, Mashiat Iqbal, Md Jalal Uddin Rumi 
  Abstract: The current study investigates the application of high-speed milling techniques on INCONEL 718 using uncoated tools. The study employed nano-MQL (NMQL), incorporating a combination of palm oil and AlO at different concentrations. The effects of various control parameters, including cutting speed, feed rate, and nano-powder concentration, on surface roughness and tool wear were examined. The investigation focused on evaluating different combinations of process parameters using the design of experiments (DoE) with a central composite design (CCD) tool. The goal was to identify the most effective parameter combinations for optimal results. Mathematical models for surface roughness (Ra, Rt), tool nose wear, and flank wear were developed using ANOVA. Genetic algorithm (GA) was employed to implement an alternative optimisation approach based on the results of response surface methodology (RSM) analysis. The graphs generated through DoE were used to analyse the individual impact of parameters on responses. Surface characteristics were assessed using scanning electron microscopy (SEM).
  Keywords: surface roughness; tool nose wear; tool flank wear; response surface methodology; RSM; central composite design; CCD; genetic algorithm; GA; scanning electron microscopy; SEM; carbide tools; nano-MQL; Al2O3 nano-powder.
  DOI: 10.1504/IJMMM.2025.10071053
   
  
• Evaluation of machining parameters on specific cutting energy consumption in the turning of Al 7075 alloy in dry conditions using Taguchi and desirability approach  
  by A. Kannan, N.M. Sivaram 
  Abstract: In the present study, Al 7075 alloy was turned using an uncoated tungsten carbide cutting tool. The number of experiments conducted was 27, as per the Taguchi L27 OA design plan. Turning operation was performed without the presence of cutting fluid, which makes it to be the most sustainable form of machining. Evaluating the specific cutting energy (SCE) required to remove the unit volume of material is the novelty of the present study. Responses considered were SCE and surface roughness (Ra). Optimisation of the input parameters was executed for individual cases using the Taguchi approach, and simultaneous optimisation was carried out using the desirability approach (DA). The 100 m/min cutting speed, 0.1 mm/rev feed rate, and 1 mm depth of cut combination produces the optimal value for SCE, and the 200 m/min cutting speed, 0.05 mm/rev feed rate, and 1 mm depth of cut combination makes the optimal value for Ra, considering the individual response optimisation. This study optimised the turning of Al 7075 alloy using a tungsten carbide tool in a dry, sustainable process. Through 27 Taguchi designed experiments, optimal parameters for minimising specific cutting energy (SCE) and surface roughness (Ra) were identified. The best combined setting (200 m/min speed, 0.075 mm/rev feed, 1 mm depth) reduced SCE by 88.31% and Ra by 14.48%, achieving a low SCE of 0.166 J/mm
  Keywords: machining; Al 7075 alloy; specific cutting energy; SCE; Taguchi method; composite desirability; CD; sustainability.
  DOI: 10.1504/IJMMM.2025.10071074
   
  
• Investigating the feasibility of utilising cactus oil as a minimum quantity lubrication eco-friendly coolant for machining 42CrMo4 steel  
  by Nada K. Elbadawy, Mohamed A. Daha, Galal Ali Nassef, Ibrahem Maher 
  Abstract: Lubricants are essential in machining, serving as coolants and cutting fluids. Traditionally, petroleum-based oils were used, but their environmental impact has led to a shift towards eco-friendly options. This research investigated soluble and non-edible cactus oils as cutting fluids in minimum quantity lubrication for turning 42CrMo4 steel with cemented carbide inserts. Minitab software, Taguchi L9 orthogonal array design, and ANOVA were utilised to evaluate the effects of cutting fluid and depth of cut on surface roughness and flank tool wear. The study aimed to enhance surface roughness and tool wear. Results indicated that surface roughness decreased by 17% with soluble oil and 28% with cactus oil at a 1 mm cutting depth compared to dry conditions. Flank tool wear was reduced by 8% with soluble oil and 16% with cactus oil. Cactus oil improved surface roughness by 13% and tool wear by 9% over soluble oil at the same depth.
  Keywords: eco-friendly coolant; dry machining; cactus oil; MQL; surface roughness; flank tool wear; contact angle; dynamic viscosity; viscosity index; rheology; wettability; 42CrMo4.
  DOI: 10.1504/IJMMM.2025.10071129
   
  
• A smart swarm-based optimisation framework for computing the optimal surface finish value for machining Ti-alloy  
  by K. Srinivasulu, G. Krishna Mohana Rao 
  Abstract: High corrosion and wear resistance makes Ti-alloys the best choice for manufacturing aerospace, automobile and power plant machinery parts. Surface roughness (SR) in Ti-alloy can arise from machining processes. This paper focuses on computing the optimal value of cutting speed, feed rate, depth of cut for minimising SR of Ti-alloy under different machining conditions by uncoated, chemical vapour deposition (CVD) and physical vapour deposition (PVD) based carbide tools. For this purpose, artificial neural network (ANN) is employed to model the SR. With the help of optimal ANN parameters, the objective functions are developed which are then optimised by particle swarm optimisation (PSO) method. The result obtained from the PSO method is validated by performing a confirmatory experiment. On comparison the absolute percentage error varied in the range of 1%6% for dry, synthetic and mineral oil machining by uncoated, PVD and CVD coated carbide tools.
  Keywords: Ti-alloys; surface roughness; artificial neural network; ANN; objective functions; particle swarm optimisation; PSO.
  DOI: 10.1504/IJMMM.2025.10071383
   
  
• Machinability analysis of carbon nanotubes reinforced PMMA composites: a comparative study  
  by Prabhat Kumar Nanda, Narasingh Deep, Punyapriya Mishra, Trupti Ranjan Mahapatra, Punyatoya Mishra 
  Abstract: This study investigates the machinability criteria of carbon nanotube (CNT)-reinforced polymethyl methacrylate (PMMA) composites using ultrasonic machining (USM) and abrasive jet machining (AJM) processes. The composite materials were fabricated with varying weight percentages of CNTs, and their density, hardness, and impact strengths were acquired. The hardness improved progressively, whereas the impact strength diminished with the wt.% of CNT reinforcement. Subsequently, machining operations were carried out considering the material removal rate (MRR) and the surface roughness as the response indicators. The micrographs of the machined surfaces were also studied. The comparative analysis revealed significant differences in the machining behaviour of the CNT reinforced PMMA composites under USM and AJM. AJM exhibited higher MRRs, whereas lower surface roughness is achieved in USM.
  Keywords: carbon nanotube; CNT; PMMA composites; machinability; ultrasonic machining; USM; abrasive jet machining; AJM.
  DOI: 10.1504/IJMMM.2025.10071555
   
  
• Multi-criteria decision making approach for selecting the best Ti alloy turning parameters by analysing the influence of cutting force on surface finish under different conditions  
  by K. Srinivasulu, G. Krishna Mohana Rao 
  Abstract: Ti-alloys are known for their supreme physical properties and high industrial applications. The surface finish of the Ti-alloy is compromised when the high material removal rate desired. Hence, computing the best turning parameter of Ti-alloy is a multi-criteria decision making (MCDM) problem. Therefore, a risk minimisation based MCDM model is developed to determine the best turning parameter of Ti-alloy. The weight of the criteria is determined by the entropy method. The proposed model determined that the machining speed (MS) of 52 mm/min, feed 0.245 mm/rev, depth of cut (DOC) is 0.6 mm with synthetic oil as lubricant is the best for turning Ti-alloy by uncoated carbide tool. Whereas, MC of 96 mm/min, feed 0.29 mm/rev, DOC 0.6 mm with synthetic oil as lubricant used best for turning Ti-alloy by chemical and physical vapour deposited carbide tool. Finally, a sensitivity analysis is conducted to test the stability of the model.
  Keywords: Ti-alloy; surface finish; multi-criteria decision making; MCDM; cutting forces; surface roughness; sensitivity analysis.
  DOI: 10.1504/IJMMM.2025.10071587
   
  
• A review of the progress in smart machining to incorporate artificial intelligence, internet of things, and data-driven approaches for precision manufacturing  
  by Milon Selvam Dennison, Kirubanidhi Jebabalan Sundarrajan, Faith Natukunda 
  Abstract: This review article investigates the significant progress in smart machining achieved through the incorporation of artificial intelligence (AI), the internet of things (IoT), and data-driven methods. It demonstrates the transformative impact of these technologies on precision manufacturing through improvements in productivity, accuracy, and adaptability. AI has facilitated advanced predictive maintenance, enhanced optimisation of machining settings, and improved the detection of defects. Concurrently, IoT has enabled real-time monitoring and the generation of actionable perceptions. The data-driven approaches have significantly enhanced the optimisation of processes and the ability to predict future outcomes through analytics. However, with these developments, it is imperative to tackle issues such as the incorporation of technology, efficient handling of data, and safeguarding against cybersecurity threats. This review highlights the potential of new technologies such as sophisticated machine learning (ML), edge computing, and next-generation IoT devices in promoting future advancements. Through promoting interdisciplinary and industry-academia collaborations, the manufacturing industry may utilise these innovations to attain more intelligent, efficient, and sustainable machining processes, ultimately improving competitiveness and contributing to broader sustainability objectives.
  Keywords: smart machining; AI in manufacturing; internet of things; IoT; data-driven manufacturing; precision machining; Industry 4.0; cyber physical systems.
  DOI: 10.1504/IJMMM.2025.10071909
   
  
• Evaluation of the impact of ecofriendly lubrication techniques on the surface roughness during AISI 8640 steel turning  
  by Gustavo Henrique Correia Leandro, André Alves De Resende 
  Abstract: This study investigated the use of eco-friendly cutting fluids on surface roughness during the turning process of AISI 8640 steel. The lubrication conditions of dry cutting, minimum quantity lubrication (MQL), and MQL combined with solid lubricant (MQL + SL) was compared. The experimental results revealed that both MQL techniques significantly enhance surface quality, with the MQL + SL configuration resulting in the best results. The statistical analyses confirmed the significance of the cutting speed effects, feed rate, and lubrication conditions on the roughness. Furthermore, the study emphasised the minimal variation in roughness with changes in cutting speed but find the adverse effects of higher feed rates on surface finish. The results indicated that the best lubrication condition was MQL + SL since it produced surfaces with the lowest surface roughness. The roughness values for the MQL + SL condition were approximately 40% better than those of the MQL system and 60% better than those of dry cutting.
  Keywords: ecofriendly cutting fluids; surface roughness; tool life; minimum quantity lubrication; MQL.
  DOI: 10.1504/IJMMM.2025.10071977
   
  
• Comparative study of turning two engineering plastics (POM-C and PA-6) and optimisation using GA, SA, GRA and COPRAS with and without weighting (entropy, critic, Swara, ROC)  
  by Mounia Kaddeche, Septi Boucherit, Salim Belhadi, Mohamed Athmane Yallese 
  Abstract: This paper focuses on a comparative study of the machinability of two semi-crystalline polymers (POM-C) and (PA-6), during dry turning operations. The aim is to experimentally examine the impact of cutting parameters, namely cutting speed, feed, and depth of cut on surface roughness, cutting force, cutting power, and material removal rate. A series of experiments according to a Taguchi L18 plan was implemented. The ANOVA analysis revealed that the type of material a substantial effect on surface roughness, followed by feed, whereas cutting force and cutting power are more affected by depth of cut. Linear regression models with interactions proved effective in predicting the studied responses, and single-objective optimisation using SA and GA methods were applied to optimise each response. The GRA and COPRAS methods coupled with weighting methods CRITIC, ROC, SWARA, and Entropy are used for multi-objective optimisation of the considered responses. The results showed that the combination of the COPRAS method with the SWARA method provides a better compromise, which is of crucial interest for researchers in the field of optimisation in polymer material machining.
  Keywords: engineering plastics; turning; optimisation; ANOVA; revolutionary algorithm; MCDM methods.
  DOI: 10.1504/IJMMM.2025.10073163