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Computational Techniques in Statistical Analysis and Exploitation of CNC Machining Experimental Data
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Author(s): N. A. Fountas (School of Pedagogical & Technological Education (ASPETE), Greece), A. A. Krimpenis (School of Pedagogical & Technological Education (ASPETE), Greece)and N. M. Vaxevanidis (School of Pedagogical & Technological Education (ASPETE), Greece)
Copyright: 2012
Pages: 33
Source title:
Computational Methods for Optimizing Manufacturing Technology: Models and Techniques
Source Author(s)/Editor(s): J. Paulo Davim (University of Aveiro, Portugal)
DOI: 10.4018/978-1-4666-0128-4.ch005
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Abstract
Extracting CNC machining data on- or off-line demands thorough and careful planning. Exploitation of this data can be carried out by statistical methods, in order to obtain the most influential parameters along with their respective level of significance. However, significance of machining parameters varies according to the posed Quality Characteristics at each machining phase. In actual experiments, measuring devices and assemblies are used, and data is recorded in computer archives. To shorten the production time and cost, machining processes are planned on CAM software, especially when complex part geometries, such as sculptured surfaces, are involved. Hence, planning machining experiments using CAM software modules is an efficient approach for experimentation on the actual CNC machine tools. Data extraction and statistical analysis methodologies are presented along with respective machining experimental examples.
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