Kılıç, Sadık Engin
Loading...
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
ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
Scholarly Output
22
Articles
16
Citation Count
191
Supervised Theses
3
22 results
Scholarly Output Search Results
Now showing 1 - 10 of 22
Conference Object Citation Count: 0Partner selection in formation of virtual enterprises using fuzzy logic(SciTePress, 2015) Kılıç, Sadık Engin; Sadigh,B.L.; Ozbayoglu,A.M.; Unver,H.O.; Kilic,S.E.; Manufacturing EngineeringVirtual Enterprise (VE) is a temporary cooperation among independent enterprises to build up a dynamic collaboration framework for manufacturing. One of the most important steps to construct a successful VE is to select the most qualified partners to take role in the project. This paper is a survey of ranking the volunteer companies with respect to four evaluation criteria, proposed unit price, delivery time, quality and enterprises' past performance. Fuzzy logic method is proposed to deal with these four conflicting criteria, considered as input variables of the model. As each criterion is different in nature with the other criterion, various membership functions are used to fuzzify the input values. The next step is to construct the logical fuzzy rules combining the inputs to conclude the output. Mamdani's approach is adopted to evaluate the output in this Fuzzy Inference System. The result of the model is the partnership chance of each partner to participate in VE. A partner with highest partnership chance will be the winner of the negotiation. Implementation of this model to the illustrative example of a partner selection problem in virtual enterprise and comparing it with fuzzy-TOPSIS approach verifies the feasibility of the proposed approach and the computational results are satisfactory. Copyright © 2015 SCITEPRESS - Science and Technology Publications All rights reserve.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: 16A framework for energy reduction in manufacturing process chains (E-MPC) and a case study from the Turkish household appliance industry(Elsevier Sci Ltd, 2016) Kılıç, Sadık Engin; Unver, Hakki Ozgur; Gok, Gozde; Fescioglu-Unver, Nilgun; Kilic, Sadik Engin; Manufacturing EngineeringEnergy 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 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.Doctoral Thesis İşlenmesi zor malzemelerin minimum miktarda yağlama yöntemi kullanılarak sürdürülebilir talaşlı imalatı(2019) Kılıç, Sadık Engin; Kılıç, Sadık Engin; Ünver, Hakkı Özgür; Manufacturing EngineeringKüresel sanayi eğilimleri talaşlı işlemlerin doğa dostu ve sürdürülebilir imalat açısından kabul edilebilir nitelikte olması yönündedir. Bu bakımdan kesme sıvısı tüketiminin azaltılması statejileri fazlaca ilgi çekici ve zorlu bir araştırma konusu olarak literatürde geniş bir şekilde tartışılagelmektedir. Kesme sıvısı kullanımına alternatif olmak üzere çok sayıda etkin strateji önerilmiştir. En az miktarda yağlama yöntemi çevre dostu ve ekonomik oluşuyla bu yöntemlerden bıri olarak öne çıkmaktadır. Talaşlı işlemlerde en az miktarda yağlama yöntemi uygulamalarındaki yüksek beklentilere karşın, bu yöntemin özellikle Ti alaşımları (Ti 6Al 4V) gibi. işlenmesi zor malzemelerde kullanımında hala çok sayıda kısıtlayıcı bulunmaktadır. En az miktarda yağlama yönteminin bu türlü zor işlem koşullarındaki yetersizliği en kesme sıvılarının az miktarda yağlama uygulamasındaki özelliklerinin iyileştirilmesine odaklanan çeşitli yöntemler üzerinde çalışmalara yol açmıştır. Son yıllarda bu yöndeki çalışmaların çoğunun en az miktarda yağlamada nanoteknoloji kullanımıyla iyileştirme sağlamak üzerine olduğu görülmektedir. Bu çalışmada Ti 6Al 4V malzemenin kanal frezelenmesinde enaz miktarda yağlayıcı sisteminde hegzagonal boron nitrür (hBN) nano parçacıklı kesme sıvısı kullanan doğa dostu yağlama/soğutma stratejisi için özgün bir yaklaşım önerilmektedir. Bu çalışmadaki özgünlük nano akışkan kullanımıyla kesme sıvısının yağlama/soğutma etkinliğini ve enaz miktar yağlayıcı yöntemindeki ısıl iletkenliği artırarak Ti 6Al 4V'nin işlenebilirliğini iyileştirmek yönündedir. Bu amaç doğrultusunda, araştırma özellikle kesme sıvısı içine dağılmış hBN parçacıklarının etkisi üzerine odaklanmaktadır. hBN nano parçacıklı enaz miktar yağlayıcı uygulamasının Ti 6Al 4V malzemenin kanal ferezelenme işlemi üzerindeki etkisinin kapsamlı şekilde anlaşılabilmesi için çok sayıda deney planlanlanarak gerçekleştirilmiş ve hBN parçacıklı enaz miktarda yağlayıcı kullanılarak elde edilen sonuçlar, kesme sıvısı kullanmadan, yüksek debili kesme sıvısı kullanarak ve enaz miktarda yağlayıcı kullanarak elde edilen sonuçlarla karşılaştırılmıştır. Kesme kuvveti (Fc) ve yüzey pürüzlüğü (Ra) ölçüm değerlerinin her biri beş seviyedeen oluşan 5 faktörle: kesme hızı (v), diş başına ilerleme (fn), eksenel kesme derinliği (ap), kesme sıvısı akış hızı (Q) and hBN nano parçacık konsentrasyonu ile değişimini belirlemek üzere Cevap Yüzeyi Metodolojisine dayalı Merkezi Karma Tasarımı kullanılarak deney tasarımı oluşturulmuştur. Cevap Yüzey Metodolojisi kullanılarak deney sonuçlarından oluşturulan ortalama yüzey pürüzlülüğü Ra ve Özgül kesme enerjisi (SEC) için oluşturulan modeller kullanılarak Çok Amaçlı Parçacık Sürü Optimizasyonu (PSO) çalışması yapıldı. Çalışma sonuçları tüm çıktıların diş başı ilerleme, eksenelkesme derinliği ve kesme sıvısı akış hızına duyarlı olduğunu göstermiştir. Ancak bu çıktılar kesme hızına duyarlı değildir. Ayrıca, enaz kesme sıvısı (MQL) hBN nano parçacıklarla birlikte uygulandığında kesme kuvveti Fc ve yüzey pürüzlülüğü Ra değerleri azalmıştır. Sonuç olarak, Ti 6Al 4V malzemenin işlenmesinde hBN nano parçacıklarla birlikte enaz kesme sıvısı (MQL) uygulamasının geleneksel akıtma kesme sıvısı uygulamasına etkin bir alternative olduğu belirlenmiştir.Article Citation Count: 10An 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-4V(Taylor & Francis inc, 2021) Namlu, Ramazan Hakkı; Kılıç, Sadık Engin; Kilic, Sadik Engin; Lotfısadıgh, Bahram; Mechanical Engineering; Manufacturing EngineeringTi-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.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.Article Citation Count: 28Slot milling of titanium alloy with hexagonal boron nitride and minimum quantity lubrication and multi-objective process optimization for energy efficiency(Elsevier Sci Ltd, 2020) Kılıç, Sadık Engin; Yilmaz, Volkan; Unver, Hakki Ozgur; Seker, Ulvi; Kilic, Sadik Engin; Manufacturing EngineeringThe implementation of sustainable manufacturing techniques to make machining processes more eco-friendly is a challenging topic that has attracted significant attention from the industrial sector for many years. As one of the dominant manufacturing processes, machining can have a considerable impact in terms of ecology, society, and economics. In certain areas, this impact is a result of using certain cutting fluids, especially during the machining of difficult-to-cut alloys such as titanium, where a large amount of cutting fluid is wasted to ease the cutting process. In such scenarios, identifying suitable machining conditions to supply cutting fluids using eco-friendly techniques is currently a major focus of academic and industrial sector research. In this study, effects of minimum quantity lubrication with different concentrations of hexagonal boron nitride nanoparticles on the surface roughness and cutting force of slot-milled titanium alloy is investigated using analysis of variance and response surface methodology. The results reveal that all responses are sensitive to changes in the feed per tooth, cutting depth, and cutting fluid flow rate. The regression functions generated were combined with particle swarm optimization in order to improve energy-efficiency, as well. Possible sectorial scenarios were generated for wider industrial adoption. With this study, it was proven that utilizing minimum quantity lubrication with hexagonal boron nitride nanoparticles can reduce both cutting force and surface roughness, which makes it to be a promising alternative as a nanoparticle augmented minimum quantity lubrication method for machining titanium alloys. (C) 2020 Elsevier Ltd. All rights reserved.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.Conference Object Citation Count: 3Design of a Customer's Type Based Algorithm for Partner Selection Problem of Virtual Enterprise(Elsevier Science Bv, 2016) Kılıç, Sadık Engin; Ozbayoglu, Ahmet Murat; Unver, Hakki Ozgur; Kilic, Sadik Engin; Manufacturing EngineeringVirtual Enterprise (VE) is a temporary platform for individual enterprises to collaborate with each other, sharing their core competencies to fulfill a customer demand. In order to improve the customer satisfaction, the most successful VEs select their consortium's members based on customer's preferences. There is quite extensive literature in the field of partner selection in VE, each proposing a new approach to evaluate and select the most appropriate partners among pool of enterprises. However, none of the studies in literature recommend which partner selection methodology should be used in each project with a particular customer attitude. In this study an algorithm is proposed which classifies the customers into three categories; passive, standard and assertive. Three different approaches; Fuzzy Logic-FAHP TOPSIS and Goal programming are used for each customer type respectively. This classification is beneficial since the problem's characteristics; such as vagueness of data, change as the customer's attitude varies. The results certify that, adopting this algorithm not only helps the VE to select the most appropriate partners based on customer preferences, but also the model adapts itself to each customer's attitude. As a result, the overall system flexibility is significantly improved. (C) 2016 The Authors. Published by Elsevier B.V.
- «
- 1 (current)
- 2
- 3
- »