Wyniki wyszukiwania - BazTech

1

Strength of High-Density Wood-Based Panels Reinforced with Melamine Films

Lipski Adam, Karolewski Sebastian

Drewno : prace naukowe, doniesienia, komunikaty

|

2025

|

Vol. 68, nr 215

Art. no. 200039

EN

Wood-based panels are a group of products with a wide range of applications. They are not obtained from solid wood, but are made from wood fragments, such as wood chips, sawdust or wood dust, which are usually waste from production. The recycled material, after being mixed with a binder, is compressed. As a consequence of such a process, different types of boards are obtained: MDF (Medium-Density Fiberboard), HDF (High-Density Fiberboard), fiberboard or particleboard. In response to the problems accompanying the use of MDF and HDF boards, a new type of wood-based boards has been developed, called CDF (Compact Density Fiberboard). In this study the strength properties of CDF panels reinforced with melamine films were investigated for four thicknesses: 6.4 mm, 8.4 mm, 10.4 mm and 12.4 mm. Young’s modulus E, tensile strength Rm and percentage total extension at fracture At were determined by a static tensile test. The results of the strength tests of wood-based panels were subjected to statistical analysis to determine the effect of the thickness of the panel on its strength. CDF boards have a low total elongation at break of about 0.5%, and exhibit greater stiffness, with a Young’s modulus of at least 5,600 MPa. The statistical analysis shows that for boards up to 12.4 mm thick, their thickness usually does not affect the strength properties. The only exception is in the Young’s modulus values for a thickness of 12.4 mm.

2

Study of the effect of process factors on the wear rate and surface integrity in incremental point forming of AA6061 aluminum alloy

Mughir Walaa Amer, Jasim Hussein Hatem

Advances in Science and Technology. Research Journal

|

2025

|

Vol. 19, no. 3

84--95

EN

Incremental point forming is a contemporary method employed in sheet metal forming to achieve great flexibility in fabrication of intricate forms, eliminating the requirement for specific mold. According to its exceptional mechanical characteristics and low weight, this method is particularly employed in the production of aluminium alloys. The essential aim of this research is to examine the deformation mechanisms and discuss the mechanical properties of aluminium during the incremental forming process. The aim was to examine how various process parameters influence the surface properties, hardness, and wear resistance of the workpieces using aluminium alloy type AA6061. The parameters under investigation are increment step down size, feed rate, and spindle rotational speed. Furthermore, the impact of these factors on the forming process was investigated using several methodologies, including the Taguchi method for parameter optimization and surface analysis. The findings of this study demonstrate that spindle rotation speed exerted a substantial influence on both surface roughness and hardness, accounting for 63.41% for hardness and 52.19% for roughness. In terms of wear rate, the step size had the most significant impact, accounting for 48.53%.

3

Optimization of tungsten inert gas welding process parameters for joining austenitic stainless steel and copper using the Taguchi method

Bensaid Nabil, Benlamnouar Mohamed Farid, Laksir Yazid Laib Dit, Saadi Tahar, Badji Riad

Advances in Science and Technology. Research Journal

|

2025

|

Vol. 19, no. 1

209--219

EN

This study aims to optimize the Tungsten Inert Gas (TIG) welding parameters for joining AISI 316L stainless steel and Cu-ETP copper using 309L stainless steel filler rods. Welding dissimilar materials is challenging due to their significant differences in thermal and mechanical properties. The high thermal conductivity of Cu-ETP copper leads to rapid heat dissipation, causing uneven heat distribution at the weld interface. To address this issue, the research team applied a 1 mm offset of the welding torch toward the copper side to balance the heat input. They employed statistical analyses using ANOVA and the Taguchi method to determine the optimal process parameters. The results showed that the optimal welding current, welding speed, and gas flow for achieving high tensile strength (Rm) are 90 A, 0.5 mm/s, and 12 l/min, respectively. Among these, welding speed emerged as the most significant factor, influencing 48.74% of the weld characteristics. Mechanical testing confirmed that these parameters produced high-quality welds. Metallurgical analysis revealed minimal diffusion between the materials, preserving their distinct properties while minimizing the formation of undesirable intermetallic phases. These results highlight the effectiveness of TIG welding in creating robust joints between AISI 316L stainless steel and Cu-ETP copper for applications requiring a combination of both materials' properties.

4

Predicting mechanical strength and optimized parameters in FDM-printed polylactic acid parts via artificial neural networks and desirability analysis

Abdulridha HInd H., Abbas Tahseen F., Bedan Aqeel S.

Management Systems in Production Engineering

|

2024

|

nr 3 (32)

428--437

EN

Fused deposition modeling (FDM) is a commonly used additive manufacturing (AM) technique in both domestic and industrial end-product fabrications. It produces prototypes and parts with complex geometric designs, which has the major benefits of eliminating the need for expensive tooling and flexibility. However, the produced parts often face poor part strength due to anisotropic fabrication strategies. The printing procedure, the kind of material utilized, and the printing parameters all have a significant impact on the mechanical characteristics of the printed item. In order to predict the mechanical properties related to printed components made with the use of FDM and Polylactic Acid (PLA) material, this study concentrates on developing a prediction model utilizing Artificial Neural Networks (ANNs). This study used the Taguchi design of experiments technique, utilizing (L25) orthogonal array as well as a Neural Network (NN) method with two layers and 15 neurons. The effect of FDM parameters (layer thickness (mm), percentage of infill density, number of top/bottom layers, shell thickness (mm), and infill overlap percentage) on ultimate tensile and compressive strength (UTS and UCS) was examined through analysis of variance (ANOVA). With an ANOVA result of 67.183% and 40.198%, respectively, infill density percentage was found to be the most significant factor influencing UCS and UTS dependent on other parameters. The predicted results demonstrated valuable agreement with experimental values, with mean squared errors of (0.098) and (0.326) for UTS and UCS, respectively. The predictive model produces flexibility in selecting the optimal setting based on applications.

5

Investigation of workload control methods for shops with re-entrant flows

Prabhu Aruna, Raghunandana K, Yogesh Pai P, Barboza Augustine B.V.

Management Systems in Production Engineering

|

2024

|

nr 1 (32)

145--155

EN

The re-entrant flow with an unpredictable nature of arrival would apparently harm production plans and sched-ules in flow type of shops. The re-entrant flow with varied arrival frequencies in rotor blade manufacturing is quite complicated and results in disproportionate workloads. Hence, an attempt has been made to study the significant influence of disproportionate workloads and research on an innovative order release method to enhance perfor-mance. The manufacturing process was observed thoroughly to incorporate the uncertain events that cause dis-turbance in the production. A simulation model was developed on a discrete event simulation platform by ana-lysing problem phenomena right from the conceptualization phase. The model has been verified and validated to ensure the accuracy. The model was subjected to 288 experiments representing different scenarios that a flow shop undergoes in reality. The factors considered in the experimentation were re-entrant frequency, re-entrant proportions, order release methods and priority dispatching rules. A refined load release policy for disproportion-ate loads has been proposed to judge its effectiveness in terms of profit computation by comparing it with other relevant policies. Results of the experiment revealed that the order release methods contribute 95.93% to throughput performance, in addition, the use of the new re-entrant method policy in the above scenario was productive in improving the overall shop performance.

6

Assessment of the Implementation of a 3D Vision Measuring System on the Production Line in Quality Control of Refractory Products

Niekurzak Mariusz, Kubińska-Jabcoń Ewa

Management and Production Engineering Review

|

2024

|

Vol. 15, No. 4

1--18

EN

The article is a case study on improving the production process of refractory products, where the results of the visual inspection processes of the tested product were used to initiate the improvement. The article presents a systemic process approach to measurement problems and its application using a 3D camera in the refractory industry. The article presents the analysis of the nonconformity structure of the tested product, based on which critical nonconformities were identified and corrective actions were initiated. Special attention was paid to the importance of metrological control (quality control plan) over the process of manufactured products. The requirements for measuring equipment according to quality standards were presented and the principles of their effective use in real conditions were discussed. The analyses carried out have shown that by analysing the results of quality control it is possible to reduce the occurrence of quality problems and thus improve the production process. The originality of the research lies in the identification of significant differences in the quality aspects of products. Research results can contribute to more effective and coherent development activities to achieve a stable and competitive advantage in the market by improving the quality and environmental performance of products. The research results and the conclusions drawn from them can be used by scientists and practitioners to shape the target states of companies in a period of growing commitment to the idea of sustainable production.

7

An Implementation of ANOVA and Six-Sigma for Productivity Improvement in Printing Machines

Kar Avijit, Pal Arun Kiran

Management and Production Engineering Review

|

2024

|

Vol. 15, No. 2

1--24

EN

Increasing productivity is currently the biggest challenge for manufacturing industries in terms of implementation of Industry 4.0 technologies. This article deals with the widely used methods of measuring of overall equipment effectiveness that in combination with statistical approaches confirms the growth in productivity and seems to be simple and novel technique particularly in the field of printing industries. The aim of the present study is to determine quantitatively the productivity, effectiveness, utilization, risk factor and sigma level of some machines in a printing company that are validated by the selected statistical approaches such as six sigma and analysis of variance techniques. Machine operating time, machine downtime and machine idle-time of different machines in a printing house are considered as main variable parameters for analysis of variance and six-sigma analysis. The results show that the proposed methodology can be a promising development towards improvement of productivity parameters of machines in the printing house.

8

Field Measurements and Machine Learning Algorithms to Monitor Water Quality in Lakes Located in Landscape Parks – A Case Study

Walczak Natalia, Walczak Zbigniew, Laks Ireneusz

Journal of Ecological Engineering

|

2024

|

Vol. 25, nr 1

49--64

EN

One of the greatest threats to many lakes is their accelerated eutrophication resulting from anthropogenic pressure, agricultural intensification, and climate change. A very important element of surface water protection in environmentally conserved areas is the proper monitoring of water quality and detection of potential threats by examining the physicochemical properties of water and performing statistical analyses that enable possible exposure of unfavourable trends. The article presents the analyses of the results of measurements made in three lakes located in the Sierakowski Landscape Park. As part of the measurements, water quality indicators i.e., phosphorus, nitrogen, BOD5 and COD, were determined monthly for a year at the inflows and outflows of the studied lakes. The test results of selected water quality indicators were analysed using machine learning algorithms i.e., PCA and k-means. The conducted tests enabled statistical estimation of changes in water quality indicators in the reservoirs and evaluation of their correlation.

9

Parametric multi-response optimisation of various organic Rankine cycle configurations for geothermal heat source application using Taguchi - grey relational analysis

Igbong Dodeye Ina, Obhuo Mafel, Nyong Oku Ekpenyong

Archives of Thermodynamics

|

2024

|

Vol. 45, no. 2

231--246

EN

In this study, statistical methods (Taguchi, analysis of variance (ANOVA), and grey relational analysis (GRA)) are used to evaluate the impact, contribution ratios, and order of importance of parameters on the energy and exergy efficiencies of the simple organic Rankine cycle (SORC) and dual pressure organic Rankine cycle (DORC). The parameters being investigated are the working fluid (A), pinch point temperature difference of the evaporator (B) and condenser (C), degree of superheating (D), evaporator temperature (E), condenser temperature (F), turbine isentropic efficiency (G), pump isentropic efficiency (H), and low-pressure evaporator temperature (J, for DPORC only). Whereas the Taguchi method determines the optimum parameter combination for maximum system performance, ANOVA weighs the influence of individual parameters on the performance of the target function, and GRA optimizes the multi-response characteristic function. The condenser and evaporator temperatures, pinch point temperature difference of the condenser and turbine isentropic efficiency are revealed as the major process parameters for multi-response performance characteristics of SORC, with an influence factor of 44.79%, 20.96%, 14.81% and 10.69%, respectively. While considering three different working fluids: HFE7000 (1), R245fa (2), and R141b (3), the combination A3B2C1D1E3F1G3H3 is determined as the optimum operating condition for multi-response performance characteristic of SORC with first- (energy) and second- (exergy) law efficiencies calculated as 18.64% and 51.69%, respectively. For DPORC, the turbine isentropic efficiency, condenser temperature, and pinch point temperature difference of the condenser and evaporator are the main process parameters for multi-response performance with 41.90%, 17.80%, 14.75%, and 10.47% impact factors, respectively. The best operating condition is obtained as A1B1C1D3E2F1G3H3J2 with first- and second-law efficiencies computed as 13.17% and 57.33%, respectively.

10

Optimization of Surface Finish of Plasma Metal Deposited Stainless Steel 316L Parts by Utilization of Plasma Beam Remelting (PBR) and Taguchi Methodology

Srinivasa Chari V., Jhavar Suyog, Suresh R.

Archives of Metallurgy and Materials

|

2024

|

Vol. 69, iss. 1

223--230

EN

The study aimed to optimize the Plasma Beam Polishing process for 316L stainless steel components to reduce anisotropy and poor surface roughness using statistical analysis. An experimental design investigated the impacts of managing factors on surface roughness, with scanning speed having the ultimate impact, followed by beam power and energy density. For lower values of plasma energy density and scanning speed, and a focal location without changes on the metal surface, there was a strong tendency for the estimated Ra to drop with increasing laser power. The process parameters were changed throughout a broad range of values, making it challenging to model the dependent variable across the whole range of experimental trials. The study supports the potential of PBP as a post-processing method for additive manufacturing components.

11

Analysis of fillet weld leg length in a low-carbon steel

Ghazvinloo H.R.

Archives of Materials Science and Engineering

|

2024

|

Vol. 125, nr 2

58--64

EN

Purpose: The present article analysed the effect of MAG welding parameters (arc voltage-AV, wire feeding speed-WFS, and welding speed-WS) on fillet weld leg length (FWLL) in low-carbon steel S235JR. Design/methodology/approach: In the research, the Taguchi L8 orthogonal array was used to design experiments. The eight experimental experiments were designed based on the Taguchi method, and the average FWLL was measured in each experiment. The analysis of means (ANOM) and analysis of variance (ANOVA) techniques were used to analyse FWLL. Findings: The highest F-value in ANOVA analysis (96.08) confirmed that the welding speed is the most effective parameter on the response (with a per cent contribution of 92.24%), followed by wire feeding speed and arc voltage, with an F-value of 2.82 and 1.25, respectively. Research limitations/implications: The research was focused on MAG welding as a common process used in different industries. Future studies could consider the effect of parameters on fillet weld leg length in other arc welding processes. Due to its many applications in various industries, the low-carbon steel S235JR plate was chosen as the base material, while other steels can be used for future studies. Practical implications: The findings of the present study have significant practical implications for the welding industry. The design of welding joints is a very important part of the design of metal structures. A weld bead with correct and optimal sizes is desirable and accepted in the design of metal structures. The findings of the present study can be used in the optimal design of fillet welds for low-carbon steel. Originality/value: As far as we know, there is relatively little information on the proper balance of fillet weld leg length in low-carbon steels. Therefore, the research results can be used in the appropriate design of welding joints for low-carbon steels.

12

Utilizing Taguchi Method and Regression Analysis for Optimizing Sand Mould Flowability

Abdulamer Dheya, Muhsan Ali A., Hamdi Sinan S.

Archives of Foundry Engineering

|

2024

|

Vol. 24, iss. 3

5--9

EN

Parameters of the moulding process in foundry are usually determined by trial-and-error method, and this way contributes to time taken and adds further cost for production sand. The present work represents an attempt to optimize sand moulding parameters in terms of compactability, compaction time, and air pressure, and to study effect of these factors on the green sand flowability using L4 design of experiments. Regression model, Taguchi method, and experimental verification were used to investigate flow property of sodium bentonite- bonded BP-quartz sand for sand moulding. Analysis of variance (ANOVA) was employed to measure significance and contributions of different moulding variables on flowability of green sand. The values obtained showed that the compaction time factor significantly affected flowability of green sand while compactability and air pressure have slight effects. The comparison results of Taguchi method, regression predictions and experiments exhibited good agreement.

13

Application of EEMD-DFA algorithms and ann classification for detection of knee osteoarthritis using vibroarthrography

Machrowska Anna, Karpiński Robert, Maciejewski Marcin, Jonak Józef, Krakowski Przemysław

Applied Computer Science

|

2024

|

Vol. 20, no. 2

90--108

EN

Osteoarthritis is one of the leading causes of disability around the globe. Up to this date there is no definite cure for cartilage lesions. Only fast and accurate diagnosis enables prolonging joint survivor time. Available diagnostic methods have disadvantages such as high price, radiation, need for experienced radiologists or low availability in some regions. The present study evaluates the use of vibroarthorgraphy as a method of cartilage lesion detection. 47 patients with diagnosed cartilage lesions, and 51 healthy control group patients have been enrolled in this study. The cartilage in the study group was evaluated intraoperatively by experienced orthopaedic surgeon. Signal acquisition was performed in open and closed kinematic chain based on 10 knee joint movements from 0-90 degrees. By using EEMD-DFA algorithms, reducing classifier inputs using ANOVA and then classifying using artificial neural networks (ANN), a classification accuracy of almost 93% was achieved. A sensitivity of 0.93 and a specificity of 0.93 with an AUC of 0.942 were obtained for the multilayer perceptron network. These results allow to apply this testing protocol in a clinical setting in the future.

14

Investigate the Effect of Chemical Post Processing on the Surface Roughness of Fused Deposition Modeling Printed Parts

Abdulridha HInd Hadi, Abbas Tahseen Fadhil, Bedan Aqeel Sabree

Advances in Science and Technology. Research Journal

|

2024

|

Vol. 18, no. 2

47--60

EN

Fused deposition modeling (FDM) technology is one of the rapidly growing techniques used for producing various complicated configurations without the need for any tools or continuous human intervention. However, a low quality of surfaces results for the layered production used in FDM. It is essential to investigate a suitable method for enhancing the accuracy and quality associated with FDM parts. This study aims to investigate the impact of different parameters such as the percentage of infill density, the shell thickness, layer thickness, and the number of top/bottom layers, as well as the percentage of infill overlap on part quality and the improvement of surface finish for printed specimens achieved through post-processing. Polylactic acid (PLA) material is used in building test specimens through the FDM approach. The experiments are carried out based on the Taguchi design of experiment method using (L25) orthogonal array. Using an analysis-of-variance approach (ANOVA), it is possible to understand the significance of the FDM parameters in order to find optimal parameter combinations. The results indicate that the application of the vapour smoothing procedure (VSP) treatment enhances the surface quality of FDM components to a microstage with minimal dimensional variation. The dichloromethane chemical has been found to exhibit excellent surface finish at an infill density of 50%, a layer thickness of 0.1 mm, a shell thickness of 2.8 mm, five top/bottom layer numbers, and 0.25 infill overlap.

15

Application of RRAP reliability optimization as a test of nature-inspired algorithms

Pieprzycki Adam, Filipowicz Bogusław

Science, Technology and Innovation

|

2023

|

Vol. 18, no. 3-4

1--14

EN

This paper presents a discussion on the application of two swarm intelligence algorithms, Cuckoo Search (CS) and Firefly Algorithm (FA), to maximize the reliability of two complex systems with resource constraints, which have been well-known in the literature. The reliability of the systems is also evaluated using several classical methods. The results indicate that although the CS algorithm, which utilizes Lévy flight, is eective, the FA rey algorithm outperformed it in the presented optimization tasks, within the given parameter range. These ndings contribute to the ongoing discussion on using nature-inspired algorithms for solving Reliability Redundancy Allocation Problem (RRAP) problems, and the two test scenarios used in the study can be useful for validating other algorithms in RRAP problems. The paper introduces metrics and methods for analyzing and comparing the performance of algorithms in RRAP optimization, including the comparison of criterion function values and other parameters introduced in the paper. Additionally, the paper discusses statistical analyses of variance (ANOVA) with post-hoc RIR Tuckey tests.

16

A survey of applications of the Kruskal Wallis test in wind power generation

Mbuli Nhlanhla, Diya Mthobisi

Przegląd Elektrotechniczny

|

2023

|

R. 99, nr 4

140--144

EN

The authors present the results of a survey on the use of the Kruskal Wallis test in wind power generation research. An overall assessment of the qualifying publications suggested that they could be categorized into 4 logical application areas. The time series of the annual number of publications indicated a steady trend in the numbers produced annually and most publications were in the category of environmental issues. The survey contributes to the body of knowledge on wind power generation and also creates a depository of references in one source.

PL

e. Autorzy przedstawiają wyniki ankiety dotyczącej wykorzystania testu Kruskala Wallisa w badaniach energetyki wiatrowej. Ogólna ocena kwalifikujących się publikacji sugeruje, że można je podzielić na 4 logiczne obszary zastosowań. Szeregi czasowe rocznej liczby publikacji wskazywały na stały trend w liczbach wydawanych rocznie, a większość publikacji dotyczyła kwestii środowiskowych. Ankieta wzbogaca wiedzę o energetyce wiatrowej, a także tworzy depozyt referencji w jednym źródle.

17

Comparative evaluation of mechanical properties of short aramid fiber on thermoplastic polymers

Arı Ali, Bayram Ali, Karahan Mehmet, Arslan Orhun

Materials Science Poland

|

2023

|

Vol. 41, No. 1

161--176

EN

This study investigated the mechanical performance of short aramid fiber on polypropylene, polyethylene, polyamide 6, and polyamide 12. Extrusion, press molding, and CNC cutting methods were used in the production of composite samples. Tensile, three-point bending, drop weight and hardness tests of the composites were carried out. As the fiber volume fractions increased, the mechanical properties of the composites improved, but the most efficient fiber fractions for each matrix changed. To analyze the performance of the fibers in the matrix on the composites, scanning electron microscope (SEM) images of the fractured surfaces as a result of tensile and drop weight tests were examined. As the fiber volume fractions increased, the fiber deformation increased, and as a result, the mechanical performance of the composites was adversely affected. Analysis of variance (ANOVA) and F test were performed using signal/noise values to analyze in detail the effect of experimental parameters on output values. Finally, the results of a regression equation model were compared with the experimental readings. It was found to be in good agreement with the model and the results of the experiment.

18

Analysis of Ring Spun Yarn Wickability Using the Post-Hoc Test

Elkateb Sherien N.

Fibres & Textiles in Eastern Europe

|

2023

|

Vol. 31, no. 1

78--82

EN

Yarn wickability achieves high thermo-physiological comfort. Therefore, this paper aimed to investigate yarn wickability and analyze statistically factors affecting yarn wicking performance. Methodology consists of testing wicking height for ring spun yarn produced from three levels of fibre types and twist factors at two levels of doubling. Statistical tools such as ANOVA, T-test and Post-hoc tests analyzed the impacts on wicking heights. Findings showed that the Post-hoc test represented the variation between groups more accurately than ANOVA. Furthermore, a comparison of Bonferroni Alpha with T-test p-values revealed that yarn wicking was significantly affected by interactions of fibre type, doubling, and twist level.

19

COVID-19 detection on chest X-ray images using Homomorphic Transformation and VGG inspired deep convolutional neural network

Shibu George Gerosh, Raj Mishra Pratyush, Sinha Panav, Ranjan Prusty Manas

Biocybernetics and Biomedical Engineering

|

2023

|

Vol. 43, no. 1

1--16

EN

COVID-19 had caused the whole world to come to a standstill. The current detection methods are time consuming as well as costly. Using Chest X-rays (CXRs) is a solution to this problem, however, manual examination of CXRs is a cumbersome and difficult process needing specialization in the domain. Most of existing methods used for this application involve the usage of pretrained models such as VGG19, ResNet, DenseNet, Xception, and EfficeintNet which were trained on RGB image datasets. X-rays are fundamentally single channel images, hence using RGB trained model is not appropriate since it increases the operations by involving three channels instead of one. A way of using pretrained model for grayscale images is by replicating the one channel image data to three channel which introduces redundancy and another way is by altering the input layer of pretrained model to take in one channel image data, which comprises the weights in the forward layers that were trained on three channel images which weakens the use of pre-trained weights in a transfer learning approach. A novel approach for identification of COVID-19 using CXRs, Contrast Limited Adaptive Histogram Equalization (CLAHE) along with Homomorphic Transformation Filter which is used to process the pixel data in images and extract features from the CXRs is suggested in this paper. These processed images are then provided as input to a VGG inspired deep Convolutional Neural Network (CNN) model which takes one channel image data as input (grayscale images) to categorize CXRs into three class labels, namely, No-Findings, COVID-19, and Pneumonia. Evaluation of the suggested model is done with the help of two publicly available datasets; one to obtain COVID-19 and No-Finding images and the other to obtain Pneumonia CXRs. The dataset comprises 6750 images in total; 2250 images for each class. Results obtained show that the model has achieved 96.56% for multi-class classification and 98.06% accuracy for binary classification using 5-fold stratified cross validation (CV) method. This result is competitive and up to the mark when compared with the performance shown by existing approaches for COVID-19 classification.

20

Multi-Response Optimization of Electrical Discharge Machining of 17-4 PH SS Using Taguchi-Based Grey Relational Analysis

Gerçekcioğlu Eyyup, Albaşkara Mehmed

Archives of Metallurgy and Materials

|

2023

|

Vol. 68, iss. 3

861--868

EN

Multiple response optimization of the machining of 17-4 PH stainless steel material, which is difficult to process with traditional methods, with EDM was made by Taguchi-based grey relational analysis method. Surface roughness (Ra), material removal rate (MRR), and electrode wear rate (EWR) were the responses, while current, pulse-on time, pulse-off time, and voltage were chosen as process parameters. According to the multi-response optimization, the experiment level that gave the best result was A1B2C2D2. optimum machining outputs were found as A1B3C1D1 using the Taguchi method. As a result of the Taguchi analysis and ANOVA, it was determined that the significant parameters according to multiple performance characteristics were current (56.22%) and voltage (22.40%). The surfaces of the best GRG and optimal sample were examined with XRD, SEM and EDX analysis and the effects on the surfaces were compared.