Kurumun Atıf Alan Makalesi
Atıf Alan Yayın
Experimental study and analysis of machinability characteristics of metal matrix composites during drilling
Scopus
Toplam 130 atıf DOI
In this study, the metal matrix composite materials were produced by hot press with various production parameters. The drilling experiments were performed on computer numerical control vertical machining centre without cutting fluid. Analysis of variance (ANOVA) was carried out in order to determine the effects of the production parameters on thrust force and surface roughness of metal matrix composites drilled with different feed rate. The effect of production parameters such as temperature, pressure and reinforcement ratio were investigated, and their effects were presented. The optimal level for each production parameters was determined by ‘Maximize the S/N ratio approach with a Taguchi design’. The test results revealed that the reinforcement ratio was the main factor affecting the surface roughness of the metal matrix composites for both feed rate. However, same singularity was not matter on thrust force due to close contribution rates of production parameters and high error rates of analysis. In literature, an increase on the thrust force and the surface roughness values was reported as the feed rate increased during machining. Nevertheless, in our MMCs system, the thrust force and the surface roughness values were in tendency of declination as the feed rate increased which makes this study more novel research.
Atıf Kaynağı
Atıf Yapan Yayın
Optimization and analysis of surface roughness, flank wear and 5 different sensorial data via tool condition monitoring system in turning of aisi 5140
Scopus
Havuzumuzda Open Access 108 atıf almış
Optimization of tool life is required to tune the machining parameters and achieve the desired surface roughness of the machined components in a wide range of engineering applications. There are many machining input variables which can influence surface roughness and tool life during any machining process, such as cutting speed, feed rate and depth of cut. These parameters can be optimized to reduce surface roughness and increase tool life. The present study investigates the optimization of five different sensorial criteria, additional to tool wear (VB) and surface roughness (Ra), via the Tool Condition Monitoring System (TCMS) for the first time in the open literature. Based on the Taguchi L9 orthogonal design principle, the basic machining parameters cutting speed (vc), feed rate (f) and depth of cut (ap) were adopted for the turning of AISI 5140 steel. For this purpose, an optimization approach was used implementing five different sensors, namely dynamometer, vibration, AE (Acoustic Emission), temperature and motor current sensors, to a lathe. In this context, VB, Ra and sensorial data were evaluated to observe the effects of machining parameters. After that, an RSM (Response Surface Methodology)‐based optimization approach was applied to the measured variables. Cutting force (97.8%) represented the most reliable sensor data, followed by the AE (95.7%), temperature (92.9%), vibration (81.3%) and current (74.6%) sensors, respectively. RSM provided the optimum cutting conditions (at vc = 150 m/min, f = 0.09 mm/rev, ap = 1 mm) to obtain the best results for VB, Ra and the sensorial data, with a high success rate (82.5%).
Atıf Yapan Makale Bilgileri
Kurumlar (4)
Bydgoszcz University of Science and Technology
Bydgoszcz, Poland
Selçuk Üniversitesi
Selçuklu, Turkey
South Ural State University
Chelyabinsk, Russian Federation
University of Portsmouth
Portsmouth, United Kingdom