Filters

20212
Reset filters

Settings

Access Right: info:eu-repo/semantics/closedAccessSubject: minimum quantity lubrication

Search Results

Now showing 1 - 2 of 2
  • Thumbnail Image
    Article
    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.
  • Thumbnail Image
    Article
    Citation - WoS: 28
    Citation - Scopus: 33
    An 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 Engin
    Ti-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.