Browsing by Author "Kilic, S. Engin"
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Article Citation Count: 1Combined use of ultrasonic-assisted drilling and minimum quantity lubrication for drilling of NiTi shape memory alloy(Taylor & Francis inc, 2023) Namlu, Ramazan Hakkı; Lotfi, Bahram; Lotfi, Bahram; Yılmaz, Okan Deniz; Akar, Samet; Kılıç, Sadık Engin; Mechanical Engineering; Department of Mechanical Engineering; Manufacturing EngineeringThe 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 Count: 6Cutting force prediction in ultrasonic-assisted milling of Ti-6Al-4V with different machining conditions using artificial neural network(Cambridge Univ Press, 2021) Namlu, Ramazan Hakkı; Turhan, Cihan; Turhan, Cihan; Kilic, S. Engin; Lotfısadıgh, Bahram; Kılıç, Sadık Engin; Energy Systems Engineering; Mechanical Engineering; Manufacturing EngineeringTi-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.Article Citation Count: 0EFFECT OF THE MQL TECHNIQUE ON CUTTING FORCE AND SURFACE QUALITY DURING THE SLOT MILLING OF TITANIUM ALLOY(inst Za Kovinske Materiale I in Tehnologie, 2022) Kılıç, Sadık Engin; Yilmaz, Volkan; Unver, Hakki Ozgur; Seker, Ulvi; Kilic, S. Engin; Manufacturing EngineeringIn this study, the effects of four control parameters, i.e., the cutting speed (v(c)), feed per tooth (f), depth of cut (a(p)), and flow rate of the cutting fluid (Q), on the surface roughness (R-a) and cutting force (F-c) were investigated in the slot milling of titanium alloys (Ti-6A1-4V). The effects of the control parameters were determined by a statistical analysis. In addition, RSM models for R-a and F-c during machining under three cooling/lubrication conditions, i.e., dry, flood, and minimum quantity lubrication (MQL), were obtained. The results revealed that both R-a and F-c are sensitive to changes in f, a(p) and Q. It was found that the MQL condition generates lower values of R-a where the surface roughness value is 0.227 mu m. By contrast. F-c values under the MQL condition were close to those of the flood condition and at times even better. The machining performance at a cutting-fluid flow rate of 36 mL/h under the MQL condition was found to be the best under certain machining conditions. MQL was found to be an effective alternative technique for conventional conditions when machining Ti-6Al-4V.Article Citation Count: 1Enhancing machining efficiency of Ti-6Al-4V through multi-axial ultrasonic vibration-assisted machining and hybrid nanofluid minimum quantity lubrication(Elsevier Sci Ltd, 2024) Namlu, Ramazan Hakkı; Lotfi, Bahram; Lotfi, Bahram; Kılıç, Sadık Engin; Mechanical Engineering; Department of Mechanical Engineering; Manufacturing EngineeringTi-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 Citation Count: 2An experimental study on ultrasonic-assisted drilling of Inconel 718 under different cooling/lubrication conditions(Springer London Ltd, 2024) Namlu, Ramazan Hakkı; Tekaut, Hasan; Lotfi, Bahram; Ucak, Necati; Kılıç, Sadık Engin; Lotfi, Bahram; Kilic, S. Engin; Mechanical Engineering; Department of Mechanical Engineering; Manufacturing EngineeringUltrasonic-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 Count: 76An intelligent process planning system for prismatic parts using STEP features(Springer London Ltd, 2007) Kılıç, Sadık Engin; Kilic, S. Engin; Manufacturing EngineeringThis 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 Count: 0Investigation of the Combined Effects of Ultrasonic Vibration-Assisted Machining and Minimum Quantity Lubrication on Al7075-T6(Hindawi Ltd, 2024) Namlu, Ramazan Hakkı; Cetin, Baris; Lotfi, Bahram; Kilic, S. Engin; Kılıç, Sadık Engin; Mechanical Engineering; Department of Mechanical Engineering; Manufacturing EngineeringThe aluminum alloy Al7075-T6 finds extensive application in the aviation and automotive industries, where machining plays a pivotal role. Emerging techniques such as Ultrasonic Vibration-Assisted Machining (UVAM) and Minimum Quantity Lubrication (MQL) hold promise for enhancing machining efficiency. In this study, the combined use of UVAM and MQL for slot milling of Al7075-T6 was investigated. The results demonstrate that UVAM reduced cutting forces by an average of 10.87% in MQL and 8.31% in Conventional Cutting Fluid (CCF) conditions when compared to Conventional Machining (CM). In addition, UVAM yielded significantly improved surface finishes, characterized by an average reduction in surface roughness of 41.86% in MQL and 32.11% in CCF conditions relative to CM. Furthermore, surfaces subjected to UVAM exhibited fewer instances of burn marks and tool-induced markings, reduced chip splashing, and more uniform surface integrity compared to those manufactured with CM. Lastly, chips generated through UVAM exhibited distinct characteristics, notably shorter length, curvier shape, and a distinctive half-turn morphology when compared with the irregular chips produced through CM. In conclusion, our findings underscore the potential of UVAM in synergy with MQL to augment the machining of Al7075-T6 alloy, thereby yielding superior-quality machined components with enhanced operational efficiency.Article Citation Count: 2Machining performance and sustainability analysis of Al2O3-CuO hybrid nanofluid MQL application for milling of Ti-6Al-4V(Taylor & Francis inc, 2024) Namlu, Ramazan Hakkı; Namlu, Ramazan Hakki; Lotfi, Bahram; Kılıç, Sadık Engin; Mechanical Engineering; Department of Mechanical Engineering; Manufacturing EngineeringMachining of Ti-6Al-4V presents challenges due to its low thermal conductivity, and conventional cutting fluids (CCF) are inadequate in providing a productive and sustainable solution. This study aims to achieve more sustainable and productive machining of Ti-6Al-4V by utilizing Al2O3 and CuO-added Nanofluid Minimum Quantity Lubrication (NMQL) individually and in hybrid form with different concentrations. A comparison is made with pure-MQL, CCF and dry conditions. The study consists of three stages. In the first stage, the physical properties of the coolants, like contact angle and surface tension, are investigated. The second stage involves slot milling operations, and various outputs including cutting forces, surface roughness, surface topography, surface finish, and subsurface microhardness are analyzed. In the last stage, a sustainability analysis is conducted based on the Pugh Matrix Approach. The results indicate that Al2O3-NMQL exhibits lower contact angles and surface tensions compared to other conditions. Furthermore, HNMQL applications result in lower cutting forces (up to 46.5%), surface roughness (up to 61.2%), and microhardness (up to 6.6%), while yielding better surface finish and topography compared to CCF. The sustainability analysis demonstrates that HNMQL application is the most suitable option for achieving sustainable machining of Ti-6Al-4V.Article Citation Count: 11A neural network model for the assessment of partners' performance in virtual enterprises(Springer London Ltd, 2007) Kılıç, Sadık Engin; Amaitik, Saleh; Kilic, S. Engin; Manufacturing EngineeringIn response to increasing international competition, enterprises have been investigating new ways of cooperating with each other to cope with today's unpredictable market behaviour. Advanced developments in information & communication technology (ICT) enabled reliable and fast cooperation to support real-time alliances. In this context, the virtual enterprise (VE) represents an appropriate cooperation alternative and competitive advantage for the enterprises. VE is a temporary network of independent companies or enterprises that can quickly bring together a set of core competencies to take advantage of market opportunity. In this emerging business model of VE, the key to enhancing the quality of decision making in the partner companies' performance evaluation function is to take advantage of the powerful computer-related concepts, tools and technique that have become available in the last few years. This paper attempts to introduce a neural network model, which is able to contribute to the extrapolation of the probable outcomes based on available pattern of events in a virtual enterprise. Quality, delivery and progress were selected as determinant factors effecting the performance assessment. Considering the features of partner performance assessment and neural network models, a back-propagation neural network that includes a two hidden layers was used to evaluate the partner performance.Article Citation Count: 8An ontology-based multi-agent virtual enterprise system (OMAVE): part 1: domain modelling and rule management(Taylor & Francis Ltd, 2017) Lotfısadıgh, Bahram; Unver, Hakki Ozgur; Kılıç, Sadık Engin; Dogdu, Erdogan; Ozbayoglu, A. Murat; Kilic, S. Engin; Manufacturing EngineeringNew advancements in computers and information technologies have yielded novel ideas to create more effective virtual collaboration platforms for multiple enterprises. Virtual enterprise (VE) is a collaboration model between multiple independent business partners in a value chain and is particularly suited to small and medium-sized enterprises (SMEs). The most challenging problem in implementing VE systems is ineffcient and inFLexible data storage and management techniques for VE systems. In this research, an ontology-based multi-agent virtual enterprise (OMAVE) system is proposed to help SMEs shift from the classical trend of manufacturing part pieces to producing high-value-added, high-tech, innovative products. OMAVE targets improvement in the FLexibility of VE business processes in order to enhance integration with available enterprise resource planning (ERP) systems. The architecture of OMAVE supports the requisite FLexibility and enhances the reusability of the data and knowledge created in a VE system. In this article, a detailed description of system features along with the rule-based reasoning and decision support capabilities of OMAVE system are presented. To test and verify the functionality and operation of this system, a sample product was manufactured using OMAVE applications and tools with the contribution of three SMEs.Article Citation Count: 8An ontology-based multi-agent virtual enterprise system (OMAVE): part 2: partner selection(Taylor & Francis Ltd, 2017) Lotfısadıgh, Bahram; Nikghadam, Shahrzad; Kılıç, Sadık Engin; Unver, Hakki Ozgur; Dogdu, Erdogan; Kilic, S. Engin; Manufacturing EngineeringA 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.