Thesis Type: Postgraduate
Institution Of The Thesis: Bursa Uludağ University, Fen Bilimleri Enstitüsü, Fen Bilimleri Enstitüsü, Turkey
Approval Date: 2012
Thesis Language: Turkish
Student: Doğan ŞENKAL
Supervisor: Mustafa Cemal ÇakırAbstract:
In this work, correlations between the surface roughness - tool life and cutting parameters (Vc, f, ap) are modeled and analyzed using Response Surface Methodology (RSM) in hard material turning operations of cold work mold steel hardened to 62 HRC up to its core. Ceramic inserts (KY4400 - KY1615) are used in the operations. Consequently, cutting parameters that have influence on surface roughness are determined and optimum surface roughness values, as well as the parameter values that give these optimum values are observed.The general manufacturing can be described as the achievement of a predefined product quality with given equipment, cost and time constraints. Unfortunately, for some quality characteristics of a product such as surface roughness cost of tools it is hard to ensure that these requirements will be met. Goals of this paper point out the various methodologies and practices that are being employed for the prediction of surface roughness, wear on cutting tools. The outcome benefits would allow for the machinability process to become more productive and at the same time to reduce any re-processing of the machined work piece so as to satisfy the technical specifications (Benardos and Vosniakos, 2007).This paper presents a study of the analysis of surface roughness and wear on cutting tools when turning the hardened steel up to 62 HRC with an advanced alumina/TIC ceramic grade (KY1615) and coated aluminum oxide and titanium carbonitride ceramic (Al2O3/TiCN) cutting tools (KY4400). Through this study all of machining parameter and results of these trials can be seen. Accordingly the best parameter can be chosen. The evaluated results indicated that the feed rate affected the surface roughness the most, other parameters remained slightly (Ra). It decreased with decreasing the feed rate while it increased with the decreasing the nose radius. The cutting speed and the depth of cut had a slight effect on the surface roughness values of Ra. Surface Roughness decreased due to increasing the Cutting Speed. A statistical unit which is expert on statistical evaluation was used in this experimental plan. First of all, this experimental plan was based on RSM method. This method examines the optimization of cutting parameters for surface roughness in turning. Secondly, wear of cutting tool was also analyzed in this paper. Thirdly, it was tried to find a relation between chip examples and wear pictures. It is necessary to determine the best machining condition in order to get better surface roughness. In this paper after all best machining condition was analyzed thanks to RSM method and wear-chip pictures. According to RSM, the best results of the surface roughness can be obtained with the highest cutting speed and the lowest feed rate values.