Taguchi Design Research Articles

Experimental investigation on optimizing wire-cut EDM process parameters of hybrid MMC(AA7475/ZrO2/Gr) using artificial neural network

Abstract Wire cut Electrical discharge machining (WCEDM) is a widely used method for machining complex shapes in advanced materials like metal matrix composites (MMCs) and hybrid metal matrix composites (HMMCs). To address these challenges, this study focusses on the wire-cut EDM (WCEDM) process of a workpiece made from zirconium dioxide and graphite-reinforced aluminium alloy 7475 with a molybdenum electrode. The effects of input process variables such as peak current (IP), pulse-on-time (TON), and flushing pressure (PF) on the output response features are investigated. These output responses include material removal rate (MRR), surface roughness (SR), and wire wear ratio (WWR). To optimise the process parameters, the Taguchi design technique is used. An artificial neural network (ANN) with a feed-forward back propagation architecture is utilised to find the best fit for the optimisation challenges. ANN predicted the results with an accuracy of 97.81% for MRR, 97.95% for SR and 95.865% for WWR. The results reveal that the WCEDM of AA7475/ZrO2/Gr with a molybdenum electrode achieved minimal WWR and SR, while maximizing the MRR.

Formulation and Optimization of Solid Lipid Nanoparticle-based Gel for Dermal Delivery of Linezolid Using Taguchi Design.

Linezolid (LNZ) is a synthetic oxazolidinone antibiotic approved for the treatment of uncomplicated and complicated skin and soft tissue infections caused by gram-positive bacteria. Typically, LNZ is administered orally or intravenously in most cases. However, prolonged therapy is associated with various side effects and life threatening complications. Cutaneous application of LNZ will assist in reducing the dose, hence minimizing the unwanted side/adverse effects associated with oral administration. Dermal delivery provides an alternative route of administration, facilitating a local and sustained concentration of the antimicrobial at the site of infection. The current research work aimed to formulate solid lipid nanoparticles (SLNs) based gel for dermal delivery of LNZ in the management of uncomplicated skin and soft tissue infections to maximise its benefits and minimise the side effects. SLNs were prepared by high-shear homogenisation and ultrasound method using Dynasan 114 as solid lipid and Pluronic F-68 as surfactant. The effect of surfactant concentration, drug-to-lipid ratio, and sonication time was investigated on particle size, zeta potential, and entrapment efficiency using the Taguchi design. The main effect plot of means and signal-to-noise ratio were generated to determine the optimized formulation. The optimized batch was formulated into a gel, and ex-vivo permeation study, in-vitro and in-vivo antibacterial activity were conducted. The optimised process parameters to achieve results were 2% surfactant concentration, a drug-to-lipid ratio of 1:2, and 360 s of sonication time. The optimized batch was 206.3± 0.17nm in size with a surface charge of -24.4± 4.67mV and entrapment efficiency of 80.90 ± 0.45%. SLN-based gel demonstrated anomalous transport with an 85.43% in vitro drug release. The gel showed a 5 cm zone of inhibition while evaluated for in vitro antibacterial activity against Staphylococcus aureus. Ex-vivo skin permeation studies demonstrated 20.308% drug permeation and 54.96% cutaneous deposition. In-vivo results showed a significant reduction in colony-forming units in the group treated with LNZ SLN-based gel. Ex-vivo studies ascertain the presence of the drug at the desired site and improve therapy. In-vivo results demonstrated the ability of SLN-based gel to significantly reduce the number of bacteria in the stripped infection model. The utilization of SLN as an LNZ carrier holds significant promise in dermal delivery.

Effect of Drilling Parameters and Tool Diameter on Delamination and Thrust Force in the Drilling of High-Performance Glass/Epoxy Composites for Aerospace Structures with a New Design Drill

Real service requirements of the assembly performance and joining properties of design components are critical for composite usage in the aerospace industry. This experimental study offers a novel and comprehensive analysis of dry drilling optimization for glass-reinforced, high-performance epoxy matrix composites used in aerospace structures, focusing on thrust force and delamination. The study presents a first-time investigation into the combined effects of spindle speed (1000, 2250, 4000 and 5750 rpm), feed rate (0.2, 0.4, 0.6 and 0.8 mm/rev) and tool diameter (3 and 5 mm) using a custom-designed drill tool specifically developed for this application, filling a gap in the current literature. By employing the Taguchi design of experiments, the study identified that medium spindle speeds (2250–4000 rpm), lower feed rates (0.2 mm/rev) and smaller tool diameters (3 mm) provided optimal conditions for minimizing thrust force and delamination. These results present actionable insights into improving the structural integrity and performance of drilled aerospace-grade composite components, offering innovative advancements in both the aerospace and defense industries.

Optimization of slot parameters for performance enhancement of slotted Savonius hydrokinetic turbine using Taguchi analysis

Hydrokinetic technology is an innovative approach to generate sustainable energy from river systems by using the kinetic energy of free-flowing water. To utilize such energy hydrokinetic turbines are being employed to harness the kinetic energy from flowing water. In this paper, a CFD study has been carried out to improve the efficiency of the Savonius turbine with the application of proposed slotted blades and validated with the experimental study. Also, this study aims for the optimization of a slotted blade Savonius hydrokinetic turbine (SHT) performance by examining different design parameters and their relationship using the Taguchi method. This study reveals that slot gap (y) has the greatest influence on turbine performance, followed by slot shape factor (ε), slot position (f), and tip speed ratio (λ). Moreover, the optimal combination of four parameters for maximising the efficiency of the slotted SHT is y = 1.5 mm, ε = 0.6, f = 1 % of blade diameter, and λ = 0.7 based on signal-to-noise (S/N) ratio. At this optimum combination of slotted blade profile, performance of slotted blade SHT increases by 45.19 % compared to conventional SHT. There is a slight difference of 4.16 % between experimental and computational results obtained for optimum Taguchi design.

Biocompatible cationic 5-fluorouracil loaded elastic liposomes for ocular delivery: In vitro, ex vivo, and in vivo evaluation

5-fluorouracil (5-FU) is used to treat scleral and episcleral fibroblast proliferations (scarring process) in the eyes. Frequent washing of the conventional solution results in limited drug access to the eyes. Taguchi and central composite design (CCD) oriented optimized mucoadhesive cationic elastic liposomes were prepared and characterized. The optimized F-CEL8 (composed of 85 mg of dipalmitoyl-phosphatidylcholine, 15 mg of sodium cholate, 10 mg of 5-FU, 7 mg of ethanol, and 883 mg of buffer) and its gel were studied for in vitro and ex vivo drug release profiles as compared to the drug solution and the liposomes. In vitro hemolysis and Draize studies corroborated safety concerns. An in vivo pharmacokinetics study was studied in rats. Each mL of F-CEL8 contained dipalmitoyl-phosphatidylcholine (X1), sodium cholate, and ethanol to deliver 10 mg of 5-FU with optimal vesicle size, low polydispersity index (PDI), and high zeta potential (ZP). The %EE value of spherical F-CEL8 was quite high (82.3 ± 7.1 %) as compared to liposomes (∼53 %) due to the large volume of the inner aqueous chamber of vesicles. F-CEL8-gel exhibited relatively high viscosity for slow and sustained release for 24 h as compared to others. The percent permeation of 5-FU from the solution, F-CEL8, F-CEL8-gel, and the liposomes were found to be 28.6 ± 4.6 %, 69.6 ± 7.4 %, 76.89 ± 12.4 %, and 54.8 ± 5.3 %, respectively. All isotonic formulations did not exhibit hemolysis and irritation to the eyes. The gel illustrated the highest values of pharmacokinetics parameters as compared to the solution and the liposomes, which may be attributed to the maximum residence time achieved through electrostatic interaction (the vesicle internalization with the mucosal layer of eyes).

Optimization methodology combining Taguchi design and response surface method to maximize a compression ignition engine efficiency fueled with oxygenated synthetic fuel

This research examines the potential of a synthetic e-diesel and oxymethylene dimethyl ether blend in a heavy-duty single-cylinder engine. The main purpose is to find the optimal engine settings that maximize engine efficiency and minimize emissions. As the first step, a methodology was developed and applied to simplify the engine’s map into five characteristic points to be representative of the World Harmonized Transient Cycle, assigning weights to each load region. This simplification reported low error estimations for fuel consumption and NOx emissions over the cycle. After obtaining the five points, a drop-in analysis was assessed, where the fuel was evaluated with the same settings as diesel, revealing more advanced and shorter combustion with great reductions in soot emissions. Then, a group of three air management and three injection parameters was selected for optimization. A novel methodology combining Taguchi Design and Response Surface Methodology is developed and applied to find the best engine settings. By integrating these two methods, the research reduced the number of required experiments if only one method were used and maintained the goal of achieving higher thermal efficiencies with the new fuel blend compared to the diesel baseline. Significant statistical results were obtained in the Taguchi design, revealing the air management factors that most affected the responses; meanwhile, second-order models with high accuracy helped in finding the best injection parameters. Subsequently, the best settings were experimentally evaluated, and optimal conditions determined by the two methods were validated, confirming the effectiveness of the methodology. Optimization results revealed an improvement of around 2% higher efficiencies for the five tested points while achieving important average reductions of 28% less in NOx with additional decreases in CO, HC, and soot levels, all outperforming traditional diesel benchmarks. Finally, a well-to-wheel analysis using the simplified cycle confirmed a substantial reduction in carbon impact when replacing diesel with this alternative fuel. The successful application of this methodology to recalibrate an engine with an alternative fuel blend shows the potential of using these fuels in existing engines and offers a novel methodology that can be escalated and applied under the engine calibration context.

Biomechanics of the Human Knee Joint in Maximum Voluntary Isometric Flexion: Study of Changes in Applied Moment, Agonist-Antagonist Participations, Joint Center, and Flexion Angle.

Estimation of the knee joint strength by maximum voluntary isometric contraction (MVIC) is a common practice to assess strength, coordination, safety to return to work or engage in sports after an injury, and to evaluate the efficacy of treatment modalities and rehabilitation strategies. In this study, we utilize a previously validated coupled finite element-musculoskeletal model of the lower extremity to explore the sensitivity of output measures (posterior cruciate ligament [PCL]/muscle/contact forces and passive moments) in knee MVIC flexion exercises at seated position. To do so, at three knee flexion angles (KFA), input measures (resistance moment and contribution moments of quadriceps and gastrocnemii) were varied at four levels each using the Taguchi design of experiment. Our findings reveal significant increases in PCL forces with KFA (p < 0.01), net MVIC moment (p < 0.01), and resistance moment of quadriceps (p < 0.01). In contrast, they drop at larger activity in gastrocnemii (p < 0.01). Tibiofemoral (TF) contact forces increase with the net MVIC moment (p < 0.01). The passive knee flexion moment, while highly dependent on the location at which computed, also increases with the net MVIC moment (p < 0.01). Changes in KFA, MVIC moment, and proportions thereof carried by quadriceps and/or gastrocnemii substantially affect biomechanics of the joint. Compared with level walking and stair ascent, slightly larger contact forces/stresses and much greater PCL forces are computed. This study improves our understanding of the knee joint behavior during MVIC in effective evaluation and rehabilitation interventions. Besides, it emphasizes the importance of positioning the joint center in model studies.

Coupling Taguchi experimental designs with deep adaptive learning enhanced AI process models for experimental cost savings in manufacturing process development

The Aluminum alloy AA7075 workpiece material is observed under dry finishing turning operation. This work is an investigation reporting promising potential of deep adaptive learning enhanced artificial intelligence process models for L18 (6133) Taguchi orthogonal array experiments and major cost saving potential in machining process optimization. Six different tool inserts are used as categorical parameter along with three continuous operational parameters i.e., depth of cut, feed rate and cutting speed to study the effect of these parameters on workpiece surface roughness and tool life. The data obtained from special L18 (6133) orthogonal array experimental design in dry finishing turning process is used to train AI models. Multi-layer perceptron based artificial neural networks (MLP-ANNs), support vector machines (SVMs) and decision trees are compared for better understanding ability of low resolution experimental design. The AI models can be used with low resolution experimental design to obtain causal relationships between input and output variables. The best performing operational input ranges are identified for output parameters. AI-response surfaces indicate different tool life behavior for alloy based coated tool inserts and non-alloy based coated tool inserts. The AI-Taguchi hybrid modelling and optimization technique helped in achieving 26% of experimental savings (obtaining causal relation with 26% less number of experiments) compared to conventional Taguchi design combined with two screened factors three levels full factorial experimentation.

Dimensional Error Analysis of Cortical Screw during Threading of Magnesium AZ31

Developments in manufacturing to achieve large productivity and high-quality products in the modern era have necessitated the need of using suitable methods. Taguchi or robust design method has been implemented to optimise a process in a single response. This experiment aims to analyse the cutting parameters of geometrical errors of threads. Machining trials were conducted on the diameter of the workpiece (10, 14 and 18 mm), depth of cut (0.23, 0.3067 and 0.46 mm) and spindle speed (212, 318 and 424 rpm). Three responses, namely, pitch, height threads and angle thread error, were investigated. The external thread selected is metric M1,5 with three levels of three factors. Results show that spindle speed was the most significant factor that affected pitch error and height thread error. Depth of cut and diameter of the workpiece significantly affected thread angle error. The optimal condition to produce low thread angle error included machining at level 1 diameter of the tool, level 3 depth of cut of and level 3 spindle speed.

Investigation of Tribological Behavior of PTFE Composites Reinforced with Bronze Particles by Taguchi Method

Reinforced PTFE materials can be designed to show high mechanical stability against harder materials under sliding wear conditions. Especially bearing metal-reinforced PTFE is of high practical interest. In this class of materials, bronze-filled PTFE was reported to obtain high wear resistance, a low coefficient of friction (COF), and excellent self-lubrication properties in sliding conditions. In the statistical approach of this work, PTFE composites reinforced with 25 vol%, 40 vol%, and 60 vol% bronze particles were evaluated against pure PTFE regarding wear behavior under varied wear test parameters, i.e., material, normal load, and sliding speed. Wear tests were planned to use a standard orthogonal array based on the Taguchi design method. An analysis of variance test was utilized to quantify the effects of test parameters on the wear behavior of the bronze/PTFE composites and pure PTFE. According to the variance analysis, the material type has the largest influence on the COF and the specific wear rate (SWR) under test conditions of this work. Both COF and SWR were found to be influenced by the material type (29.83% and 96.16%), the normal load (33.34% and 0.95%), and sliding speed (9.14% and 1.28%). The lowest SWR and COF values were achieved at the optimum wear test conditions where the wear test parameters were 1 m/s sliding speed (A4B2C2) at PTFE + 60 vol.% bronze reinforced composite 50 N application load and 0.32 m/s sliding speed (A4B3C1) at PTFE + 60 vol.% bronze reinforced composite 100 N application load, respectively.

Optimising the acquisition conditions of high information quality low-field NMR signals based on a cutting-edge approach applying information theory and Taguchi's experimental designs – Virgin olive oil as an application example

BackgroundDeveloping a new spectrometric analytical method based on a fingerprinting approach requires optimization of the experimental stage, particularly with novel instruments like benchtop low-field NMR spectrometers. To ensure high-quality LF-NMR spectra before developing the multivariate model, an experimental design to optimize instrument conditions is essential. However, difficult-to-control factors may be critical for optimization. Taguchi methodology addresses these factors to obtain a system robust to variation. This study uses the Taguchi methodology to optimize instrument settings for acquiring high-quality 1H and 13C LF-NMR signals in a short time from virgin olive oil (VOO). ResultsTwo experimental trials (for 1H and 13C signals, respectively) were carried out and analysed to find an optimal and robust combination of instrument settings against changes in two difficult-to-control factors: ambient temperature and small deviations of the NMR tube volume (700 ± 50 μL). The responses to be optimised, run time and spectral information quality, were analysed separately and jointly, as some factors showed opposite behaviour in the effect on the responses. Multiple response analysis based on suitable desirability functions yielded a combination of factors resulting in desirability values above 0.8 for 1H LF-NMR signals and almost 1.0 for 13C LF-NMR signals.In addition, a novel approach to assess the information quality of an analytical signal was proposed, addressing a major challenge in analytical chemistry. By applying information theory and calculating information entropy, this approach demonstrated its potential for selecting the highest quality (i.e. most informative) analytical signals. SignificanceThe acquisition instrument conditions of LF-NMR were successfully optimised using Taguchi methodology to acquire highly informative 1H and 13C spectra in a minimum run time. The importance lies in the future development of non-targeted analytical applications for VOO quality control. In addition, the innovative use of information entropy to a priori assess the signal quality represents a significant advance and proposes a solution to a long-standing challenge in analytical chemistry.

Feasibility study of underground CO2 storage through Water Alternative Gas (WAG) operation: A case study in Southwestern Ontario

Geological CO2 storage (GCS) offers a promising, low-risk, long-term solution for carbon sequestration. This study assesses the feasibility of GCS water-alternating-gas (WAG) operations in a brine formation targeted for the Western Ontario GCS plan. The Cambrian strata shows potential for CO2 storage but faces challenges like limited lateral extension and geopolitical issues from plume migration. To mitigate these risks, a deep evaluation of CO2 trapping mechanisms is crucial. CO2 dissolution into brine provides secure storage by reducing the free plume. The proposed WAG operation promotes dissolution, using a vertical equilibrium model coupled with a black oil model to estimate CO2 trapping proportions during and post-injection. The Taguchi design of experiments investigates various WAG scenarios with minimal simulations, reducing numerical costs. Sensitivity analysis/optimization of WAG parameters, including water extraction rate (WER), water injection rate (WIT), and CO2 injection time (CIT), ranked their effectiveness in CO2 dissolution. Optimal WAG operations can reduce the free plume by 49 % and increase the dissolution ratio from 0.26 to 0.52. CIT and WIT were found to be the most influential factors, contributing 42 % and 31 % to CO2 dissolution, and 43 % and 34 % to overall CO2 trapping, respectively, while WER exhibited a lower impact of 8–9%.

On the Optimization of Roughness and Corrosion Resistance of Laser Beam Powder Bed Fusion Fabricated Ti–6Al–4V Parts—An Electrochemical Approach

Laser beam powder bed fusion is emerging as a technology for fabricating components made of advanced alloys, such as Ti–6Al–4V. However, it suffers from rough as‐built (AB) surfaces, necessitating postprocessing for desired quality and performance. Electrochemical methods such as electrochemical polishing (ECP) and anodization (AN) are promising postprocessing methods; ECP can effectively smoothen surfaces irrespective of their complexity and hardness, while AN enhances the material's corrosion resistance. However, literature lacks research that discusses combined ECP and AN treatment on surface texture evaluation and corrosion behavior. This work presents a detailed study on the effects of different processing factor levels using a Taguchi design of experiment (DOE) approach and discusses the underlying process mechanisms. The optimized treatment conditions to achieve highest roughness improvement and best corrosion resistance are discussed and the most influential postprocessing factors are revealed and ranked. The treatment that achieved smooth surfaces and high corrosion resistance is ECP at 20 V and 15 °C for 20 min, followed by AN at 15 V for 5 min. This treatment achieves a 72% roughness improvement, providing an arithmetic areal surface roughness of 2.63 μm and a corrosion current density of 0.09 μA cm−2, which is almost similar to the AB part.

Material Selection and Optimization of Green Drilling of Aluminium Alloys: MCDM-Pareto ANOVA and T-SRC

Abstract The widespread use of aluminium alloys in the automotive, aerospace, and structural sectors necessitates the establishment of exploratory selection criteria to harness optimality at the various stages of product development. This study utilizes multi-criteria decision-making approaches to determine the most suitable aluminium alloy for thermal friction drilling. Additionally, the process optimization was done using the Taguchi super ranking concept (T-SRC), and the confirmation test using explicit dynamics simulation using ANSYS software. The ideal material selection was evaluated based on several factors, including yield strength, tensile strength, thermal conductivity, impact resistance, density, specific heat capacity, coefficient of thermal expansion, and percentage elongation. The best-ranked AA2024-T4 aluminium alloy underwent an integrated Taguchi Design of Experiments and optimization using Pareto ANOVA and subsequently ANSYS Explicit Dynamics process simulation. The MCDM Expert System derived from AHP, and ranking of materials using TOPSIS, EDAS, and VIKOR proved to be an effective material selection strategy from a set of alternatives for the thermal friction drilling process. By combining Multi-Criteria decision making (MCDM) with process simulation, material selection concerns in different industrial processes can be resolved, therefore eliminating the need for laborious tests.

Efficient optimization of the multi-response problem in the taguchi method through advanced data envelopment analysis formulations integration

This study introduces an innovative strategy to address the multi-response challenge inherent in the Taguchi Method, frequently encountered in the enhancement of production processes and productivity indices. By integrating the Taguchi Method with Data Envelopment Analysis (DEA), experimental trials are transformed into Decision Making Units (DMUs), with response variables categorized as inputs and outputs. Advanced DEA models, including simultaneous DEA and super-efficiency models, are employed to determine the DMUs’ relative and cross efficiencies, thus retaining the advantages of the Taguchi Design of Experiments (DoE) while offering an optimal solution for enhancing multiple quality responses. The superiority of this approach is validated by the Addictive Model for Factor Effects, demonstrating enhanced outcomes and reduced computational effort compared to existing empirical and scholarly solutions. These findings have significant implications for advancing manufacturing practices that require multi-response optimization, marking a notable contribution to the field.

Properties of foam glass produced with the use of soot from a cement factory as a foaming agent: A Study Based on Taguchi Design of Experiments

Cellular glass is a lightweight, porous medium with excellent heat transfer resistance that can be used in a variety of industries. This study investigated the use of soot from cement plants as a new foaming agent for producing foam glass. The experiments were designed using the Taguchi Design of Experiments (DOE) method. By applying this approach, instead of creating and testing 27 different groups of samples, only 9 groups were produced. The properties of the remaining 18 sample groups were then predicted based on Taguchi analysis. Soot and silicon carbide were used simultaneously (at weight ratios of 2% and 3%) as foaming agents in the samples. Alumina was also used as a modifier with weight ratios of 4%, and 8%. Mechanical strength, water absorption, density, and thermal resistance were evaluated. The findings indicated a direct correlation between elevated soot content and increased water absorption (open porosity), coupled with a reduction in compressive strength and overall density of the foam glass. Electron microscopy observations revealed a wide range of crystallite morphologies in the resulting foam glass, which results in diverse properties in the material. The developed glass foams exhibit a density spanning from 125 to 700 kg/m3, with compressive strength varying between 1.2 and 6.7 MPa, and thermal conductivity in the range of 0.08–0.5 W/m·K. The samples with 3% soot, 0% alumina, and 3% SiC exhibited exceptional thermal insulation properties. In contrast, the samples containing 1% soot, 8% alumina, and 1% SiC demonstrated the highest compressive strength. Overall, this study found that soot from cement plants is a viable foaming agent for producing foam glass with desirable properties. The use of soot from cement plants can not only reduce the dispersion of pollution in the environment but also produce a wide range of foam glass with different properties at a lower cost.

Airfoil Design and Aerodynamics Characteristics of Energy-Efficient Race Car: CFD Analysis

The use of land transportation, primarily cars, is increasing annually. The energy required will increase along with the number of vehicles. Thus far, car manufacturers are required to improve car designs and propose fuel-efficient and environmentally friendly cars. The energy-efficient car competition, namely, Kontes Mobil Hemat Energi Indonesia, is organised for mechanical engineering students to contribute directly to research related to energy-efficient cars in Indonesia. One of the ways to save fuel is to reduce the aerodynamic force drag on the vehicle. This study aims to optimize the prototype vehicle airfoil design in producing the smallest possible coefficient of drag (Cd) and lift (Cl). A Taguchi design of experimental (DoE) is applied to set the 9 designs for this study, with three different values considered for each design parameters: Defiant Canard BL110, Clark YM15, Gottingen 256 for side airfoil shapes and Gottingen 410, Gottingen 460, and Boeing 737 Root for top airfoil shapes. This aerodynamic analysis uses the ANSYS 2020 R1 software, which is carried out at a speed of 30 km/h. Then the Cd and Cl values obtained will be analyzed. The results obtained for the optimal design of the Cd with variations in the side airfoil design Defiant Canard BL110 and top airfoil is Gottingen 410 with a Cd value of 0,1119. As for the optimal design of the Cl with variations in the side airfoil design Gottingen 256 and top airfoil is Gottingen 460 with a Cl value of 0,0250.

Analysis, modelling, and optimization of force in ultra-precision hard turning of cold work hardened steel using the CBN tool

The machinability of high-performance materials such as superalloys, composites, and hardened steel has been a big challenge due to their mechanical, physical, and chemical properties, which give them inherent complex machining characteristics. Additionally, majority of machinability tests conducted on these materials have been carried out on conventional and less precise lathes based on Taguchi, composite, and other designs of experiments that do not exploit all the possible combinations of cutting parameters. This work reports an investigation on ultra-precision hard turning (UHT) of cold work hardened AISI D2 steel of HRC 62, based on the full factorial design of experiment, carried out on an ultra-precision lathe. A theoretical analysis of the force components generated is reported. Modelling of the process, based on the resultant force, is also reported through a machine learning model. The model was developed from the experimental data and statistically evaluated with validation data. Its average MAPE values of 1.47%, 4.81%, and 10.66% for training, testing, and validation, respectively, attest to its robustness. The excellent coefficient of determination values, R2, also justify the model’s robustness. Multi-objective optimization was also conducted to optimize material removal rate (MRR), resultant force, and vibration simultaneously. For sustainable and efficient UHT, optimal cutting velocity (158.8 m/min), feed (0.125 mm/rev), and depth of cut (0.074 mm) were proposed to generate optimal resultant force (224.8 N), MRR (2603.6 mm3/min), and vibration (0.03 m/s^2) simultaneously. These results can be beneficial in planning UHT processes for high-performance materials.

Prediction of surface roughness at the machining of densified wood surfaces

ABSTRACT In this research, modeling and interpretation of the effects of the machining parameters on surface roughness (Rz) using artificial neural networks (ANN) and analysis methods (MLP, LVQ and Taguchi Design analysis) werw studied. Black poplar (Populus nigra) was selected as the experimental material. Specimens, which were transversal densified by a thermo-mechanical (TM) process at 0%, 20% and 40% compression ratios. The densified wood was processed at 1000, 1500 and 2000 mm/min feed speeds and in 12,000, 15,000, and 18,000 rpm rotation speeds in a CNC machine by using two different cutters. Rz surface-roughness values were measured. The modeling of Rz with artificial neural networks (ANN) is discussed. While 97% success was achieved in the classification made with multilayer perceptron (MLP) in estimating Rz, this success rate is 100% in the classification made with learning vector quantization (LVQ). MLP and LVQ are operations in the MATLAB R2019b software. Taguchi values were compared with the experimental data results, it was seen that the MSE value was 4.6%, the MAE value was 1.8%, and the RMSE value was 2.1%. These results showed that the presented models can accurately determine the appropriate parameters for the desired Rz. The prediction results and presented models can be applied for targeted industrial applications.

Co-production of cellulose and lignin by Taguchi-optimized one-pot deep eutectic solvent-assisted ball milling pretreatment of raw oil palm leaves

This study explores an eco-friendly delignification technique for raw oil palm leaves (OPL), highlighting the optimized conditions of choline chloride-lactic acid deep eutectic solvent (DES)-mediated ball milling pretreatment to maximize the co-production yields of highly crystalline cellulose and lignin. Our five-level-four-factor Taguchi design identified the optimal reaction settings for cellulose production (85.83 % yield, 47.28 % crystallinity) as 90-minute milling, 1500 rpm, mill-ball size ratio of 30:10, ball-to-sample mass ratio of 20:1, DES-to-sample mass ratio of 3:1. Conversely, the maximal lignin extraction yield (35.23 %) occurred optimally at 120-minute milling, 600 rpm, mill-ball size ratio of 25:5, ball-to-sample mass ratio of 20:1 and DES-to-sample mass ratio of 9:1. Statistical results showed that milling frequency (p-value ≤ 0.0001) was highly significant in improving cellulose crystallinity and yield, while DES-to-sample mass ratio (p-value ≤ 0.0001) was the most impacting on lignin yield. The thermogravimetric method affirmed the elevated cellulose thermal stability, corroborating the enhanced cellulose content (40.14 % to 73.67 %) alongside elevated crystallinity and crystallite size (3.31 to 4.72 nm) shown by X-ray diffractograms. The increased surface roughness seen in micrographs mirrored the above-said post-treatment changes. In short, our optimized one-pot dual-action pretreatment effectively delignified the raw OPL to produce cellulose-rich material with enhanced crystallinity and lignin solidity.