Browsing by Author "Kiliç,S.E."

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Citation - Scopus: 4
2d Fe Modelling of Machining: a Comparison of Different Approaches With Experiments
(2005) Bil,H.; Tekkaya,A.E.; Kiliç,S.E.
[No abstract available]
Citation - WoS: 13
Citation - Scopus: 17
Cutting 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.
Citation - Scopus: 5
Micro-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.
Citation - Scopus: 1
Ontology Based Virtual Enterprise System Domain Modeling
(DEStech Publications Inc., 2014) Lotfi Sadigh,B.; Ünver,H.Ö.; Dogdu,E.; Kiliç,S.E.
A virtual enterprise (VE) is a product oriented temporary consortium which forms a collaboration platform to fulfil a specific common purpose (typically to create a product) by benefiting from various capabilities of multiple VE partner enterprises. VE lifecycle consists of 3 distinct phases including VE Formation, Operation and Dissolution. VE partner enterprises are selected from virtual breeding environment (VBE) based on specific criteria considering the new VE project specifications. In order to select the most appropriate partners for the forthcoming VE project, it is required to have comprehensive information regarding the VBE members, their current conditions, capabilities, capacities and their past performances. This database continuously changes and it is dynamic. Ontologies and the corresponding knowledge bases provide the best tools for modelling such complex domain knowledge and highly dynamic data requirements. Ontologies not only help model and capture complex domain knowledge, but also improve the sharing and reusability of data and knowledge providing a suitable environment for software agents and human communications. The VE system must be able to demonstrate what types of resources exist, where they are located, and how much resource capacity is available to be used by the consortium. In this paper a pilot Virtual Enterprise system model developed for OSTIM organized industrial park in Ankara will be presented in detail. The objective of this system model is to enable SMEs in the region to collaborate effectively in order to produce eco-friendly high value added products. © Copyright 2014 by DEStech Publications, Inc. All rights reserved.