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Öğe Configuration of tool wear and its mechanism in sustainable machining of titanium alloys with energy signals(Springer London Ltd, 2024) Vashishtha, Govind; Chauhan, Sumika; Gupta, Munish Kumar; Korkmaz, Mehmet Erdi; Ross, Nimel Sworna; Zimroz, Radoslaw; Krolczyk, Grzegorz M.Surface quality, machining efficiency, and tool life are all significantly impacted by tool wear in metal cutting machining. Research priorities and areas of focus in tool wear are shifting as intelligent machining becomes the norm. Unfortunately, there are currently no acknowledged most effective ways for analyzing tool based on the energy signals specially in the machining of titanium and its alloys. In the present work, the titanium machining was performed under different lubrication conditions such as dry, minimum quantity lubrication (MQL), liquid nitrogen and hybrid, etc. Then, the spectrograms are used to transform the acquired energy data into time-frequency features. Starting with a set of randomly generated hyper parameters (HPs), the long short-term memory (LSTM) model is fine-tuned using sine cosine algorithm (SCA) with loss serving as the fitness function. The confusion matrix provides additional validation of the 98.08% classification accuracy. Additional evaluations of the suggested method's superiority include its specificity, sensitivity, F1-score, and area under the curve (AUC).Öğe Cutting forces and temperature measurements in cryogenic assisted turning of AA2024-T351 alloy: An experimentally validated simulation approach(Elsevier Sci Ltd, 2022) Gupta, Munish Kumar; Korkmaz, Mehmet Erdi; Sarikaya, Murat; Krolczyk, Grzegorz M.; Gunay, Mustafa; Wojciechowski, SzymonAluminium alloys are widely used in modern engineering applications such as automobile, aerospace etc because of its characteristics. The machining of aluminium alloys are also considered as difficult because of its sticky and soft nature, low thermal conductivity, strain hardening effect etc. The cooling conditions employed at cutting zone improved the machining performance but the resources, material consumption, skilled labor etc. are also required for performing the machining experiments. Therefore, the simulation of process parameters with the help of Finite Element Modelling (FEM) during machining is highly researched topic these days. In this work, a new practice from measurement science i.e., FEM simulation was performed with AdvantEdge software and the prediction models were developed for evaluating the cutting forces and cutting temperature while machining AA2024-T351 alloy under dry, liquid nitrogen (LN2) and carbon dioxide (CO2) conditions. Initially, the 3D turning model was developed and the results were compared with experimental findings. The results obtained from simulation model are very close with experimental results with minimum standard value of 0.67 (5.7%) for cutting forces and 4.58 (6.16%) for cutting temperature. Thus, it is worthy to mention that the 3D FE model is efficient and effective to predict and measurement results with minimum error.Öğe Development of lattice structure with selective laser melting process: A state of the art on properties, future trends and challenges(Elsevier Sci Ltd, 2022) Korkmaz, Mehmet Erdi; Gupta, Munish Kumar; Robak, Grzegorz; Moj, Kevin; Krolczyk, Grzegorz M.; Kuntoglu, MustafaLattice structures are vital for biological applications because of its numerous benefits (for example, faster and stronger binding to bone tissue). Consequently, processing of lattice structure is a particularly popular area of study currently. In this study, additive manufacturing technologies utilized in several engineering disciplines were collated and their merits and shortcomings were examined. Numerous sectors and disciplines view lattice structured additive manufacturing as a prototyping technique. In recent years, additive manufacturing tech-nology has also progressed toward the fabrication of useable final goods. The objective of this review is to classify the produced systems under the headings of aviation, automotive, and military technologies within the context of engineering and to compare them by examining the research and technology firms in this sector. In this cate-gorization, lattice-structured additive manufacturing techniques are categorized as an engineering production technology, and examples of this field are investigated. Technologies, which are examples of diverse engineering applications, are categorized under four primary headings: additive manufacturing knowledge, selective laser melting (SLM), lattice structure, and changeable porosity cellular structures.Öğe Effect of nanoparticles as a lubricants in nano-MQL machining of metallic materials: A review(Ieee, 2021) Korkmaz, Mehmet Erdi; Gupta, Munish Kumar; Krolczyk, Grzegorz M.; Maruda, Radoslaw W.; Li, ZhixiongNanofluids with minimal lubrication (MQL) are drawing attention with laws and regulations that improve environmental protection. Researchers have focused on a variety of issues concerning the performance and application of nanofluids in MQL processing. This review effort attempts to evaluate some of these researches in order to understand the influence of nanoparticles, as well as the kind and on the machinability performance of metallic materials. Furthermore, it has been found that the rise of unique types of nanoparticles and/or nanofluids combined with other types of nanoparticles considerably alters MQL processing performance (hybrid nanofluids). It has been observed that graphene oxide, paraffin wax, and soy-based nanofluids, as well as MoS2 nanoparticles and hybrid nanofluids, such as multi-layer aluminum carbon nanotubes and alumina graphene, provide effective lubricating and cooling effects in MQL processing. However, to optimize their application in machining operations, the thermophysical and wettability features of hybrid nanofluids during aging, as well as difficulties associated to nanoparticle clustering at greater concentrations, must be explored. This paper finally lists several types of nanoparticles that can be used for further machining studies to achieve collaborative effects on MQL processing performance.Öğe Erosion characteristics on surface texture of additively manufactured AlSi10Mg alloy in SiO2 quartz added slurry environment(Emerald Group Publishing Ltd, 2022) Demirsoz, Recep; Korkmaz, Mehmet Erdl; Gupta, Munish Kumar; Collado, Alberto Garcia; Krolczyk, Grzegorz M.Purpose The main purpose of this work is to explore the erosion wear characteristics of additively manufactured aluminium alloy. Additive manufacturing (AM), also known as three-dimensional (3D) manufacturing, is the process of manufacturing a part designed in a computer environment using different types of materials such as plastic, ceramic, metal or composite. Similar to other materials, aluminum alloys are also exposed to various wear types during operation. Production efficiency needs to be aware of its reactions to wearing mechanisms. Design/methodology/approach In this study, quartz sands (SiO2) assisted with oxide ceramics were used in the slurry erosion test setup and its abrasiveness on the AlSi10Mg aluminum alloy material produced by the 3D printer as selective laser melting (SLM) technology was investigated. Quartz was sieved with an average particle size of 302.5 mu m, and a slurry environment containing 5, 10 and 15% quartz by weight was prepared. The experiments were carried out at the velocity of 1.88 (250 rpm), 3.76 (500 rpm) and 5.64 m/s (750 rpm) and the impact angles 15, 45 and 75 degrees. Findings With these experimental studies, it has been determined that the abrasiveness of quartz sand prepared in certain particle sizes is directly related to the particle concentration and particle speed, and that the wear increases with the increase of the concentration and rotational speed. Also, the variation of weight loss and surface roughness of the alloy was investigated after different wear conditions. Surface roughness values at 750 rpm speed, 10% concentration and 75 degrees impingement angle are 0.32 and 0.38 mu m for 0 and 90 degrees samples, respectively, with a difference of approximately 18%. Moreover, concerning a sample produced at 0 degrees, the weight loss at 250 rpm at 10% concentration and 45 degrees particle impact angle is 32.8 mg, while the weight loss at 500 rpm 44.4 mg, and weight loss at 750 rpm is 104 mg. Besides, the morphological structures of eroded surfaces were examined using the scanning electron microscope to understand the wear mechanisms. Originality/value The researchers verified that this specific coating condition increases the slurry wear resistance of the mentioned steel. There are many studies about slurry wear tests; however, there is no study in the literature about the quartz sand (SiO2) assisted slurry-erosive wear of AlSi10Mg alloy produced with AM by using SLM technology. This study is needed to fill this gap in the literature and to examine the erosive wear capability of this current material in different environments. The novelty of the study is the use of SiO2 quartz sands assisted by oxide ceramics in different concentrations for the slurry erosion test setup and the investigations on erosive wear resistance of AlSi10Mg alloy manufactured by AM.Öğe In-process detection of cutting forces and cutting temperature signals in cryogenic assisted turning of titanium alloys: An analytical approach and experimental study(Academic Press Ltd- Elsevier Science Ltd, 2022) Gupta, Munish Kumar; Korkmaz, Mehmet Erdi; Sarikaya, Murat; Krolczyk, Grzegorz M.; Guenay, MustafaIn-process detection of cutting forces, temperature, roughness, wear etc. during machining of titanium alloys are very important. The Finite element (FE) analysis plays an important role in monitoring and detection of machining responses. It offers a high accuracy in modeling of dry cutting processes and its performance in modeling of cryogenic machining process is a matter of interest. In this context, current investigation focuses on the dry turning and LN2/CO2 cooling assisted turning process of commonly used Ti6Al4V alloy. It is very useful material in the biomedical sector, and the simulation of cutting forces and cutting temperature via finite element method (FEM) has been performed. In addition, the simulation results are validated with experimental work. The results show that the deviations between FE modeling and experimental results for the cutting temperature are the average of 5.54%, 5.18% and 8.42% for the dry, LN2 and CO2 cooling conditions, respectively. On the other hand, the deviations from FE modeling and cutting force test results were 3.74%, 3.358%, and 3.03% under dry, LN2 and CO2 cooling conditions, respectively.Öğe Indirect monitoring of machining characteristics via advanced sensor systems: a critical review(Springer London Ltd, 2022) Korkmaz, Mehmet Erdi; Gupta, Munish Kumar; Li, Zhixiong; Krolczyk, Grzegorz M.; Kuntoglu, Mustafa; Binali, Rustem; Yasar, NafizOn-line monitoring of the machining processes provides to detect the amount and type of tool wear which is critical for the determination of remaining useful lifetime of cutting tool. According to Industry 4.0 revolution, the machining performance in terms of cutting forces, surface roughness, power consumptions, tool wear, tool life, etc. needs to be automatically monitored because the unfavorable conditions in machining cause chatter vibrations, tool breakage, and dimensional accuracy. Therefore, the usage of advanced sensor systems plays a key role in achieving the improved machining characteristics in terms of less human effort, errors, production time, etc. and fulfills the requirement of Industry 4.0. Hence, this review presents the holistic knowledge of online detection systems including sensors and signal processing software preferred in mechanical machining operations. Initially, this paper is starting with the up-to-date literature introduction section followed by type of sensors used in machining, online detection methods in machining, challenges and suggestions, etc. Eventually, the article concluded the findings and future remarks especially focused on the theme of Industry 4.0. In the end, it is worthy to mention that this review paper is very helpful for researchers and academicians working in the industrial sectors.Öğe Influence of duplex jets MQL and nano-MQL cooling system on machining performance of Nimonic 80A(Elsevier Sci Ltd, 2021) Korkmaz, Mehmet Erdi; Gupta, Munish Kumar; Boy, Mehmet; Yasar, Nafiz; Krolczyk, Grzegorz M.; Gunay, MustafaNickel based super alloys are considered as difficult to machine materials. These days, the sustainable cooling system are applied at the cutting zone for enhancing the machining performance of nickel based super alloys. Therefore, the present work focusses on the machining aspects of Nimonic 80A under different cooling conditions. Moreover, the turning experiments were performed under dry, minimum quantity lubrication (MQL different positions) and nano-MQL (different positions) conditions and the influence of nozzle position during MQL and nano-MQL were investigated. The tool wear, surface roughness, mechanism promoting tool wear, power consumption and chips morphology were investigated under these subjected conditions. The outcomes of this study state that the position of MQL nozzles plays an important role to improve the machining performance of Nimonic-80 alloy. The total tool wear is approximately 60% better for nano-MQL (mixed direction) than dry conditions. The results also stated that abrasion and adhesion are prompting tool wear mechanisms observed under dry conditions.Öğe Measurement and analysis of machining induced tribological characteristics in dual jet minimum quantity lubrication assisted turning of duplex stainless steel(Elsevier Sci Ltd, 2022) Gupta, Munish Kumar; Boy, Mehmet; Korkmaz, Mehmet Erdi; Yasar, Nafiz; Gunay, Mustafa; Krolczyk, Grzegorz M.In this work, the sustainable machining approach is promoted by implementing the dry and minimum quantity lubrication (MQL) cooling conditions in the turning of duplex stainless steel. Initially, the turning experiments were performed under dry as well as MQL conditions and then, the influence of different positions of MQL nozzles on tribological and machining performance of 2205 duplex steel was investigated. The cutting parameters were kept fixed and the performance is evaluated in terms of surface roughness, micro-hardness, energy consumption, tool wear, machined surface microstructure and chips morphology. The results demonstrated that the highest average surface roughness values were obtained under dry conditions, with a value of 2.20 mu m while MQL (flank + rake directions) produces the lowest surface roughness value of 1.55 mu m with an improvement of 30%. Moreover, dual-jet MQL gives the lowest energy consumption (229 kJ) and tool wear (0.15 mm) with 23.67% and 52.38% enhancement, respectively.Öğe A new intelligent approach of surface roughness measurement in sustainable machining of AM-316L stainless steel with deep learning models(Elsevier Sci Ltd, 2024) Ross, Nimel Sworna; Mashinini, Peter Madindwa; Shibi, C. Sherin; Gupta, Munish Kumar; Korkmaz, Mehmet Erdi; Krolczyk, Grzegorz M.; Sharma, Vishal S.Due to the manufacturing sector ' s digitalization and ability to combine quality measurement and production data, machine learning and deep learning for quality assurance hold enormous potential. In this situation, industries may process data to inform data-driven estimates of product quality, thanks to predictive excellence. This research investigates the machinability of Laser Powder Bed Fusion (LPBF) - 316L stainless steel specimens, focusing on the impact of cutting parameters and cooling conditions (Dry, MQL, CO 2 and CO 2 + MQL) on surface roughness. The research employs advanced data augmentation techniques, incorporating TransGAN and multihead attention (MHA) based Alexnet model for surface imperfection classification. The results highlight the effectiveness of the proposed methodology in accurately classifying surface conditions and underscore the superior performance of the MHA-Alexnet algorithm compared to alternative models (Alexnet and AE-Alexnet). Overall, the study contributes valuable insights into optimizing machining parameters and cooling strategies for enhanced surface finish in additively manufactured alloys.Öğe Numerical and experimental investigations of built orientation dependent Johnson-Cook model for selective laser melting manufactured AlSi10Mg(Elsevier, 2021) Akturk, Murat; Boy, Mehmet; Gupta, Munish Kumar; Waqar, Saad; Krolczyk, Grzegorz M.; Korkmaz, Mehmet ErdiPowder bed fusion based additive manufacturing techniques involve melting or sintering of powder particles via laser beams to join them in order to attain desired shapes. This study aims to provide basis for material constitutive parameters of widely used aluminum alloy AlSi10Mg alloy. Initially, tensile samples of AlSi10Mg alloy samples were manufactured by using SLM technology. Afterwards, through quasi-static and high temperature tensile tests, an attempt has been made to determine the Johnson-Cook material model of AlSi10Mg. in order to conduct quasi-static tensile tests, strain rates of 10(-3) s(-1), 10(-2) s(-1) and 5 x 10(-2) s(-1) were considered and tests were conducted at ambient temperature. Whereas, for high temperature tensile tests 24,150, 300 degrees C temperature values were considered at the reference strain rate value of 10(-3) s(-1). The numerically simulated tensile results achieved by using the established Johnson-Cook model were then compared with experimental results. It was observed that the maximum error between the test and simulation results was around of 7.5%. The error percentage is well within the acceptable, thus proving the accuracy of the established material model. (c) 2021 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).Öğe Real-time monitoring and measurement of energy characteristics in sustainable machining of titanium alloys(Elsevier Sci Ltd, 2024) Gupta, Munish Kumar; Korkmaz, Mehmet Erdi; Yilmaz, Hakan; Sirin, Senol; Ross, Nimel Sworna; Jamil, Muhammad; Krolczyk, Grzegorz M.The development of cutting-edge monitoring technologies such as embedded devices and sensors has become necessary to ensure an industrial intelligence in modern manufacturing by recording machine, process, tool, and energy consumption conditions. Similarly, machine learning based real time systems are popular in the context of Industry 4.0 and are generally used for predicting energy needs and improving energy utilization efficiency and performance. In addition, sustainable and energy-efficient machining technologies that can reduce energy consumption and associated negative environmental effects have been the latest topic of much study in recent years. Concerning this regard, the present work firstly deals with the real time monitoring and measurement of energy characteristics while machining titanium alloys under dry, minimum quantity lubrication (MQL), liquid nitrogen (LN2) and hybrid (MQL + LN2) conditions. The energy characteristics at different stages of machine tools were monitored with the help of a high end energy analyser. Then, the energy signals from each stage of machining operation were predicted and classified with the help of different machine learning (ML) models. The experimental results showed that MQL, LN2, and hybrid conditions decreased the total energy consumption by averagely 2.6 %, 17.0 %, and 16.3 %, respectively, compared to dry condition. The ML results demonstrated that the accuracy of the random forest (RF) approach obtained higher efficacy with 96.3 % in all four conditions. In addition, it has been noticed that the hybrid cooling conditions are helpful in reducing the energy consumption values at different stages.Öğe A short review on thermal treatments of Titanium & Nickel based alloys processed by selective laser melting(Elsevier, 2022) Korkmaz, Mehmet Erdi; Gupta, Munish Kumar; Waqar, Saad; Kuntoglu, Mustafa; Krolczyk, Grzegorz M.; Maruda, Radoslaw W.; Pimenov, Danil Yu.Selective laser melting (SLM) has been considered as a well-researched technology used to produce near net shape metallic components with superior mechanical and physiochemical characteristics. Recently SLM has recently been used for the production of components made by high-performance alloys such as Titanium and Nickel. However, the microstructural and physical anisotropy along with the defects have negative impact on the performance and behavior of SLM-produced alloys. Therefore, to improve the material characteristics, extra attention must be paid to the source(s), identification, and removal of these deviations. Thermal heat treatments are often considered as an effective approach to deal with aforementioned issues. stress-relieving, quenching/hardening, annealing/ recrystallization, and thermo-mechanical heat treatments are among prominent procedures adopted for the post processing of SLM fabricated metallic components and hence considered in this article. Since these procedures have substantial impact on the microstructure and mechanical behavior therefore an assessment of their influence and resulting changes is significantly important. Therefore, this short review provides the said knowledge on thermal treatments used to improve the SLM fabricated titanium and nickel based alloys. This review can significantly help in designing and selecting appropriate post processing thermal treatments keeping in mind the expected outcome. (c) 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).Öğe A technical overview of metallic parts in hybrid additive manufacturing industry(Elsevier, 2022) Korkmaz, Mehmet Erdi; Waqar, Saad; Garcia-Collado, A.; Gupta, Munish Kumar; Krolczyk, Grzegorz M.Additive manufacturing technologies have emerged as the promising alternatives of conventional manufacturing techniques. Conventional manufacturing techniques involves cutting and removal of material by mechanical procedures to achieve final product. Whereas, discrete chunks of material in any form are combined point by point and layer by layer for the fabrication of final product in additive manufacturing processes. Numerous advantages and inefficiencies of these manufacturing techniques are reflected in factors such as the design, fabrication, material properties and working condition etc. Therefore, development of a production technology by combining the benefits of both conventional and additive techniques is significantly important. Hybrid Manufacturing jointly apply additive and conventional production methods to attain final products. Hence, this short overview covers the operation aspects of both additive and subtractive manufacturing of metallic materials. (c) 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).Öğe Tribological and surface morphological characteristics of titanium alloys: a review(Springernature, 2022) Gupta, Munish Kumar; El Etri, Hamza; Korkmaz, Mehmet Erdi; Ross, Nimel Sworna; Krolczyk, Grzegorz M.; Gawlik, Jozef; Yasar, NafizBeing easily fabricated, welded, biocompatible, having a high strength-to-weight ratio, withstanding comparatively high temperatures up to 800 degrees C and low modulus of elasticity make grade titanium and its alloys an important choice for automotive, biomedical and aerospace industries. In contempt of the different pleasant assets of Ti-6Al-4V alloy, the operation of this alloy is restricted especially when it comes to tribological and surface morphological characteristics. Enhancing these properties is important, for this purpose, a diversity of attempts and studies have been conducted. This paper mounts a review of morphological and tribological behaviors of titanium alloys including Ti-6Al-4V against different materials counting with carbide tools and other types of materials under dry and lubricated sliding conditions. The surface morphological, wear, and other properties have been discussed in this review article.
