Artificial Neural Network Modeling for Predicting Surface Roughness in End Milling of Al-SiCp Metal Matrix Composites and Its Evaluation
نویسندگان
چکیده
منابع مشابه
Development of Predictive Model for Surface Roughness in End Milling of Al-SiCp Metal Matrix Composites using Fuzzy Logic
Metal matrix composites have been increasingly used as materials for components in automotive and aerospace industries because of their improved properties compared with non-reinforced alloys. During machining the selection of appropriate machining parameters to produce job for desired surface roughness is of great concern considering the economy of manufacturing process. In this study, a surfa...
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Machining processes such as end milling are the main steps of production which have major effect on the quality and cost of products. Surface roughness is one of the considerable factors that production managers tend to implement in their decisions. In this study, an artificial neural network is proposed to minimize the surface roughness by tuning the conditions of machining process such as cut...
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Study on tool wear and surface roughness in end milling of particulate aluminum metal matrix composite: Application of response surface methodology
Metal matrix composites have been widely used in industries, especially aerospace industries, due to their excellent engineering properties. However, it is difficult to machine them because of the hardness and abrasive nature of reinforcement elements like silicon carbide particles (SiCp).In the present study, an attempt has been made to investigate the influence of spindle speed (N), feed rate...
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Surface roughness plays an important role in the performance of a finished part. The roughness is usuallymeasured off-line when the part is already machined, although in recent years the trend seems to have been to focus on online monitoring. Measuring and controlling the machining process is now possible thanks to improvements and advances in the fields of computers and sensors. The aim of thi...
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ژورنال
عنوان ژورنال: Journal of Applied Sciences
سال: 2012
ISSN: 1812-5654
DOI: 10.3923/jas.2012.955.962