期刊
JOURNAL OF INTELLIGENT MANUFACTURING
卷 27, 期 3, 页码 689-700出版社
SPRINGER
DOI: 10.1007/s10845-014-0907-6
关键词
Intelligent neural-fuzzy model; In-process surface roughness monitoring; End milling operations; Neural networks; Fuzzy logic
In this research, a new intelligent neural-fuzzy in-process surface roughness monitoring (INF-SRM) system for an end milling operation was developed. The success of the INF-SRM system depends on an accurate decision-making algorithm, which can analyze the input factors and then generate an accurate output. A new neural-fuzzy model was proposed and implemented as decision-making algorithm for the INF-SRM system. The objective of the new model is to achieve higher accuracy for surface roughness prediction and solve the disadvantages of both neural networks and fuzzy logic. The neural-assisted method was implemented to generate the fuzzy IF-THEN rules for the model. To evaluate the performance of the new neural-fuzzy model, a neural networks model was applied to develop another surface roughness monitoring system for comparison. A statistical method was finally employed to analyze the accuracy between these systems.
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