Kılıç, Sadık Engin
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Name Variants
K.,Sadik Engin
Sadık Engin, Kılıç
Kılıç S.
S. E. Kılıç
Kılıç, Sadık Engin
S.E.Kılıç
Kiliç S.
S.,Kılıç
Kilic S.
K.,Sadık Engin
K., Sadik Engin
Kilic,S.E.
S. E. Kilic
K., Sadık Engin
Kılıç,S.E.
Sadik Engin, Kilic
Sadık Engin Kılıç
S., Kilic
Kilic, Sadik Engin
Kilic,Sadik Engin
S.E.Kilic
Kilic, S. Engin
Sadık Engin, Kılıç
Kılıç S.
S. E. Kılıç
Kılıç, Sadık Engin
S.E.Kılıç
Kiliç S.
S.,Kılıç
Kilic S.
K.,Sadık Engin
K., Sadik Engin
Kilic,S.E.
S. E. Kilic
K., Sadık Engin
Kılıç,S.E.
Sadik Engin, Kilic
Sadık Engin Kılıç
S., Kilic
Kilic, Sadik Engin
Kilic,Sadik Engin
S.E.Kilic
Kilic, S. Engin
Job Title
Profesör Doktor
Email Address
engin.kilic@atilim.edu.tr
Main Affiliation
Manufacturing Engineering
Status
ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
Sustainable Development Goals
1NO POVERTY
0
Research Products
2ZERO HUNGER
0
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3GOOD HEALTH AND WELL-BEING
1
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4QUALITY EDUCATION
0
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5GENDER EQUALITY
0
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6CLEAN WATER AND SANITATION
0
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7AFFORDABLE AND CLEAN ENERGY
2
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8DECENT WORK AND ECONOMIC GROWTH
0
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9INDUSTRY, INNOVATION AND INFRASTRUCTURE
12
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10REDUCED INEQUALITIES
0
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11SUSTAINABLE CITIES AND COMMUNITIES
0
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12RESPONSIBLE CONSUMPTION AND PRODUCTION
5
Research Products
13CLIMATE ACTION
1
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14LIFE BELOW WATER
0
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15LIFE ON LAND
1
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16PEACE, JUSTICE AND STRONG INSTITUTIONS
0
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17PARTNERSHIPS FOR THE GOALS
0
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Documents
40
Citations
1080
h-index
18

Documents
29
Citations
616

Scholarly Output
34
Articles
19
Views / Downloads
77/101
Supervised MSc Theses
4
Supervised PhD Theses
2
WoS Citation Count
387
Scopus Citation Count
494
Patents
0
Projects
0
WoS Citations per Publication
11.38
Scopus Citations per Publication
14.53
Open Access Source
10
Supervised Theses
6
| Journal | Count |
|---|---|
| The International Journal of Advanced Manufacturing Technology | 4 |
| Machining Science and Technology | 3 |
| Procedia CIRP | 3 |
| Journal of Cleaner Production | 2 |
| International Journal of Computer Integrated Manufacturing | 2 |
Current Page: 1 / 4
Scopus Quartile Distribution
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19 results
Scholarly Output Search Results
Now showing 1 - 10 of 19
Article Citation - WoS: 7Citation - Scopus: 10Combined Use of Ultrasonic-Assisted Drilling and Minimum Quantity Lubrication for Drilling of Niti Shape Memory Alloy(Taylor & Francis inc, 2023) Namlu, Ramazan Hakki; Lotfi, Bahram; Kilic, S. Engin; Yilmaz, Okan Deniz; Akar, SametThe drilling of shape-memory alloys based on nickel-titanium (Nitinol) is challenging due to their unique properties, such as high strength, high hardness and strong work hardening, which results in excessive tool wear and damage to the material. In this study, an attempt has been made to characterize the drillability of Nitinol by investigating the process/cooling interaction. Four different combinations of process/cooling have been studied as conventional drilling with flood cooling (CD-Wet) and with minimum quantity lubrication (CD-MQL), ultrasonic-assisted drilling with flood cooling (UAD-Wet) and with MQL (UAD-MQL). The drill bit wear, drilling forces, chip morphology and drilled hole quality are used as the performance measures. The results show that UAD conditions result in lower feed forces than CD conditions, with a 31.2% reduction in wet and a 15.3% reduction in MQL on average. The lowest feed forces are observed in UAD-Wet conditions due to better coolant penetration in the cutting zone. The UAD-Wet yielded the lowest tool wear, while CD-MQL exhibited the most severe. UAD demonstrated a & SIM;50% lower tool wear in the wet condition than CD and a 38.7% in the MQL condition. UAD is shown to outperform the CD process in terms of drilled-hole accuracy.Article Citation - WoS: 15Citation - Scopus: 17An Experimental Study on Ultrasonic-Assisted Drilling of Inconel 718 Under Different Cooling/Lubrication Conditions(Springer London Ltd, 2024) Erturun, Omer Faruk; Tekaut, Hasan; Cicek, Adem; Ucak, Necati; Namlu, Ramazan Hakki; Lotfi, Bahram; Kilic, S. EnginUltrasonic-assisted drilling (UAD) is one of the efficient and innovative methods to improve the drillability of difficult-to-cut materials. In the present study, the UAD of Inconel 718 was investigated under different cooling and/or lubrication conditions. The drilling tests were carried out at a constant cutting speed (15 m/min) and a feed (0.045 mm/rev) using uncoated and TiAlN-coated solid carbide drills under dry, conventional cutting fluid (CCF), and minimum quantity lubrication (MQL) conditions. The applicability of UAD to drilling Inconel 718 was evaluated in terms of thrust force, surface roughness, roundness error, burr formation, subsurface microstructure and microhardness, tool wear, and chip morphology. The test results showed that, when compared to conventional drilling (CD), UAD reduced the thrust force and improved the hole quality, tool life, and surface integrity under all conditions. Good surface finish, lower roundness error, and minimum burr heights were achieved under CCF conditions. MQL drilling provided lower thrust forces, better tool performance, and good subsurface quality characteristics. In addition, the simultaneous application of CCF-UAD and MQD-UAD showed significantly better performance, especially when using the coated tool.Article Citation - Scopus: 5Micro-Wedm of Ni55.8ti Shape Memory Superalloy: Experimental Investigation and Optimisation(Inderscience Publishers, 2021) Meshri,H.A.M.; Akar,S.; Seyedzavvar,M.; Kiliç,S.E.Nickel-titanium superalloy has gained significant acceptance for engineering applications as orthotropic implants, orthodontic devices, automatic actuators, etc. Considering the unique properties of these alloys, such as high hardness, toughness, strain hardening, and development of straininduced martensite, micro-wire electro-discharge machining (μ-WEDM) process has been accepted as one of the main options for cutting intricate shapes of these alloys in micro-scale. This paper presents the results of a comprehensive study to address the material removal rate (MRR) and surface integrity of Ni55.8Ti shape memory superalloy (SMA) in the μ-WEDM process. The effects of discharge current, pulse on-time, pulse off-time, and servo voltage on the performance of this process, including MRR, white layer thickness, surface roughness, and micro-hardness of the machined surface, were investigated by multi-regression analysis using response surface methodology (RSM). The optimisation of input parameters based on the gradient and the swarm optimisation algorithms were also conducted to maximise the MRR and minimise the white layer thickness, surface roughness, and micro-hardness of the machined samples. © 2021 Inderscience Enterprises Ltd.. All rights reserved.Article Citation - WoS: 42Citation - Scopus: 45Enhancing Machining Efficiency of Ti-6al Through Multi-Axial Ultrasonic Vibration-Assisted Machining and Hybrid Nanofluid Minimum Quantity Lubrication(Elsevier Sci Ltd, 2024) Namlu, Ramazan Hakki; Lotfi, Bahram; Kilic, S. EnginTi-6Al-4V offers a balance of good strength with lightweight properties. Yet, Ti-6Al-4V poses machining challenges, including low thermal conductivity, chemical adhesion to cutting tools, and chip removal difficulties. To improve machining efficiency, Ultrasonic Vibration-Assisted Machining (UVAM) has emerged as a promising approach. UVAM has demonstrated reduced tool wear, cutting forces, and improved surface quality compared to Conventional Machining (CM). Additionally, Minimum Quantity Lubrication (MQL) methods offer sustainable coolant alternatives, with recent research focusing on Nanofluid-MQL (NMQL) and Hybrid Nanofluid-MQL (HNMQL) for enhanced performance. Although there exists a body of literature showcasing the promising effects of UVAM and MQL methods individually, comprehensive investigations into the synergistic effects of these methodologies remain limited. This study addresses these critical research gaps by conducting a systematic examination of combined application of multi-axial UVAM and HNMQL. Specifically, it delves into the comparison of different vibration directions within UVAM, evaluates the effectiveness of UVAM when combined with cutting fluids incorporating Al2O3 and CuO nanoparticles in NMQLs and HNMQLs, and contrasts these novel approaches with conventional machining methods. The study unfolds in three distinct stages. The first stage examines the ultrasonic cutting mechanism and its combined application with the MQL technique. In the second stage, the study investigates the physical properties of the cutting fluids, including contact angle and surface tension. The final stage encompasses slot milling operations, where an array of parameters such as cutting forces, surface roughness, surface topography, surface texture, and the occurrence of burr formations are rigorously analyzed. The results demonstrate that the combination of multi-axial UVAM with HNMQL yields substantial advantages over traditional machining methods. Notably, it leads to a remarkable reduction in cutting forces (up to 37.6 %) and surface roughness (up to 37.4 %). Additionally, this combination engenders the production of highly homogeneous and uniform surface textures, characterized by minimal surface defects and a significantly diminished occurrence of burr formations. These findings underscore the potential of multi-axial UVAM combined with HNMQL as a promising approach in enhancing the machining of Ti-6Al-4V, thus offering a pathway to enhance the efficiency and precision of aerospace component manufacturing processes.Article An Experimental Study of the Effects of Ultrasonic Cavitation-Assisted Machining on Ti-6al(Inderscience Publishers, 2024) Koçak,B.; Canbaz,H.İ.; Zengin,N.N.; Mumcuoğlu,A.B.; Aydın,M.B.; Namlu,R.H.; Kılıç,S.E.Ti-6Al-4V has extensive applications in high-tech industries like aviation, defence and biomedical. However, the cutting of Ti-6Al-4V is challenging due to its poor machinability. Recently, ultrasonic cavitation-assisted machining (UCAM) has emerged as a cutting process that utilises high-frequency and low-amplitude vibrations to induce the formation of cavitation bubbles, thereby improving cutting performance. Despite the benefits of UCAM, there is lack of research investigating its application in Ti-6Al-4V. This study aims to investigate the efficacy of UCAM in improving the cutting performance of Ti-6Al-4V and compare it with conventional methods. Specifically, the study compares UCAM with conventional machining (CM) under conventional cutting fluid. The study reveals that UCAM can reduce cutting forces by up to 49.5% and surface roughness by up to 51.9%. Additionally, UCAM yields more uniform, homogeneous surfaces with reduced surface damage compared to CM. These results demonstrate the potential of UCAM for enhancing cutting performance of Ti-6Al-4V. Copyright © 2024 Inderscience Enterprises Ltd.Article Citation - WoS: 77Citation - Scopus: 101An Intelligent Process Planning System for Prismatic Parts Using Step Features(Springer London Ltd, 2007) Amaitik, Saleh M.; Kilic, S. EnginThis paper presents an intelligent process planning system using STEP features (ST-FeatCAPP) for prismatic parts. The system maps a STEP AP224 XML data file, without using a complex feature recognition process, and produces the corresponding machining operations to generate the process plan and corresponding STEP-NC in XML format. It carries out several stages of process planning such as operations selection, tool selection, machining parameters determination, machine tools selection and setup planning. A hybrid approach of most recent techniques ( neural networks, fuzzy logic and rule-based) of artificial intelligence is used as the inference engine of the developed system. An object-oriented approach is used in the definition and implementation of the system. An example part is tested and the corresponding process plan is presented to demonstrate and verify the proposed CAPP system. The paper thus suggests a new feature-based intelligent CAPP system for avoiding complex feature recognition and knowledge acquisition problems.Article Citation - WoS: 14Citation - Scopus: 19Cutting Force Prediction in Ultrasonic-Assisted Milling of Ti-6al With Different Machining Conditions Using Artificial Neural Network(Cambridge University Press, 2021) Namlu,R.H.; Turhan,C.; Sadigh,B.L.; Kiliç,S.E.Ti-6Al-4V alloy has superior material properties such as high strength-to-weight ratio, good corrosion resistance, and excellent fracture toughness. Therefore, it is widely used in aerospace, medical, and automotive industries where machining is an essential process for these industries. However, machining of Ti-6Al-4V is a material with extremely low machinability characteristics; thus, conventional machining methods are not appropriate to machine such materials. Ultrasonic-assisted machining (UAM) is a novel hybrid machining method which has numerous advantages over conventional machining processes. In addition, minimum quantity lubrication (MQL) is an alternative type of metal cutting fluid application that is being used instead of conventional lubrication in machining. One of the parameters which could be used to measure the performance of the machining process is the amount of cutting force. Nevertheless, there is a number of limited studies to compare the changes in cutting forces by using UAM and MQL together which are time-consuming and not cost-effective. Artificial neural network (ANN) is an alternative method that may eliminate the limitations mentioned above by estimating the outputs with the limited number of data. In this study, a model was developed and coded in Python programming environment in order to predict cutting forces using ANN. The results showed that experimental cutting forces were estimated with a successful prediction rate of 0.99 with mean absolute percentage error and mean squared error of 1.85% and 13.1, respectively. Moreover, considering too limited experimental data, ANN provided acceptable results in a cost-and time-effective way. Copyright © The Author(s), 2020. Published by Cambridge University Press.Article Citation - WoS: 19Citation - Scopus: 20A Framework for Energy Reduction in Manufacturing Process Chains (e-Mpc) and a Case Study From the Turkish Household Appliance Industry(Elsevier Sci Ltd, 2016) Uluer, Muhtar Ural; Unver, Hakki Ozgur; Gok, Gozde; Fescioglu-Unver, Nilgun; Kilic, Sadik EnginEnergy is a major input in the manufacturing sector. Its security and efficiency are of supreme importance to a nation's industrial activities. Energy consumption also has serious environmental impacts in terms of Greenhouse Gas (GHG) emissions. In order to use energy more efficiently, simply designing parts and planning manufacturing processes with an energy-aware mindset is insufficient; it is also necessary to model and assess the energy efficiency of a process chain from a holistic point of view. In this work, we propose an integrated energy reduction framework and the internal methods to implement it. Our framework builds on three pillars. Creating an energy profile of a process chain is the first step in characterizing a manufacturing system in terms of energy demand. Energy-aware part designs and process plans are based on ISO/STEP 10303 AP224 standards in order to estimate the embodied energy of a mechanical part. Finally, using discrete event simulation methods, the energy consumption of a process chain is assessed and reduction scenarios are generated based on design or operational alternatives. A data collection and analytics system visualizing measures and key performance indicators (KPIs) also must be implemented in order to measure real consumption values and track improvement results over time. The energy reduction in manufacturing process chains (E-MPC) framework is unique in that it provides a structured method which enables the embodied energy of a part to be estimated during early design stages and further enables the evaluation of design impacts on process chains, thereby recognizing the dynamic nature of systems. A pilot case study of the framework was implemented at the largest household appliance manufacturer in Turkey, Arcelik A.S. In order to evaluate its usefulness and validity, we performed a detailed implementation on a fully automated crankshaft manufacturing line in Arcelilc's refrigerator compressor plant. The results reveal that design improvements estimated gains would reach 2%, whereas operational improvements yield up to 10% energy savings per produced part. (C) 2015 Elsevier Ltd. All rights reserved.Article Citation - WoS: 8Citation - Scopus: 13An Ontology-Based Multi-Agent Virtual Enterprise System (omave): Part 2: Partner Selection(Taylor & Francis Ltd, 2017) Sadigh, Bahram Lotfi; Nikghadam, Shahrzad; Ozbayoglu, A. Murat; Unver, Hakki Ozgur; Dogdu, Erdogan; Kilic, S. EnginA virtual enterprise (VE) is a collaboration model between multiple business partners in a value chain. The VE model is particularly feasible and appropriate for small- and medium-sized enterprises (SMEs) and industrial parks containing multiple SMEs that have different vertical competencies. The VE consortium's success highly depends on its members. Therefore, it is crucial to select the most appropriate enterprises when forming a VE consortium. In this study, a new multi-agent hybrid partner selection algorithm is developed for application in the development of an ontology-based multi-agent virtual enterprise (OMAVE) system. In this platform, the agent's interactions are supported by agent ontology, which provides concepts, properties and all message formats for the agents. Different types of agents collaborate and compete with each other so that unqualified or inefficient enterprises are eliminated from the enterprise pool. Only the remaining enterprises would be allowed to enter the negotiation process and propose in the bidding. The agent-based auctioning platform is coupled with a fuzzy-AHP-TOPSIS algorithm to evaluate partners based on their proposals and background. Accordingly, the winning enterprise for each task is identified and the whole project can be accomplished by assigning tasks to the responsible partners. To test and verify the functionality of the developed OMAVE system, a sample module using OMAVE applications and tools was manufactured. The last section of this paper presents the results of this case study, which validate the applicability of the proposed technique.Article Citation - WoS: 28Citation - Scopus: 33An Experimental Investigation on the Effects of Combined Application of Ultrasonic Assisted Milling (uam) and Minimum Quantity Lubrication (mql) on Cutting Forces and Surface Roughness of Ti-6al(Taylor & Francis inc, 2021) Namlu, Ramazan Hakki; Sadigh, Bahram Lotfi; Kilic, Sadik EnginTi-6Al-4V is widely used in aerospace, medical and defense industries where materials with superior characteristics are needed. However, Ti-6Al-4V is categorized as a difficult-to-cut material, and machining of this alloy is highly challenging. Ultrasonic Assisted Milling (UAM) is a quite recent method to facilitate the machining of difficult-to-cut materials. This method has numerous advantages over the Conventional Milling (CM) method, such as reduced cutting forces and increased surface quality. Besides, Minimum Quantity Lubrication (MQL) is an alternative cooling method to enhance the process efficiency with respect to conventional cooling methods. Cutting force and surface roughness are essential measures to evaluate the cutting performance of a machining process. However, the simultaneous effects of implementing MQL and ultrasonic vibrations in milling operations are not much researched yet. In this study, the combined effects of UAM and MQL on cutting forces and surface roughness during the machining of Ti-6AL-4V are investigated. Results show that the combination of MQL and UAM enhances the cutting forces in rough cutting operations and the surface roughness in both finish and rough cutting operations significantly compared to conventional processes. Consequently, it is concluded that simultaneous implementation of UAM and MQL enhances overall cutting performance in end-milling operation of Ti-6Al-4V.

