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.
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Atıf Yapan Yayın
A state-of-the-art review on sensors and signal processing systems in mechanical machining processes
Scopus
Havuzumuzda 119 atıf almış
Sensors are the main equipment of the data-based enterprises for diagnosis of the health of system. Offering time- or frequency-dependent systemic information provides prognosis with the help of early-warning system using intelligent signal processing systems. Therefore, a chain of data-based information improves the efficiency especially focusing on the determination of remaining useful life of a machine or tool. A broad utilization of sensors in machining processes and artificial intelligence–supported data analysis and signal processing systems are prominent technological tools in the way of Industry 4.0. Therefore, this paper outlines the state of the art of the mentioned systems encountered in the open literature. As a result, existing studies using sensor systems including signal processing facilities in machining processes provide important contribution for error minimization and productivity maximization. However, there is a need for improved adaptive control systems for faster convergence and physical intervention in case of possible problems and failures. On the other hand, sensor fusion is an innovative new technology that makes decisions using multi-sensor information to determine tool status and predict system stability. It is currently not a fully accepted and practiced method. In a nutshell, despite their numerous advantages in terms of efficiency, time saving, and cost, the current situation of sensors used in the industry is not a sufficient level due to the investment cost and its increase with additional signal acquisition hardware and software equipment. Therefore, more studies that can contribute to the literature are needed.
Atıf Yapan Makale Bilgileri
Kurumlar (5)
Opole University of Technology
Opole, Poland
Selçuk Üniversitesi
Selçuklu, Turkey
Shandong University
Jinan, China
Sinop Üniversitesi
Sinop, Turkey
South Ural State University
Chelyabinsk, Russian Federation