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Autor
Singh Ankita, Datta Saurav, Mahapatra Siba Sankar
Tytuł
Application of a Fuzzy Inference System for the Optimization of Material Removal Rate and Multiple Surface Roughness Characteristics in the Machining of GFRP Polyester Composites
Źródło
Decision Making in Manufacturing and Services, 2013, vol. 7, nr 1/2, s. 19-42, tab., rys., bibliogr. 36 poz.
Słowa kluczowe
Systemy rozmyte, Polimery, Materiałoznawstwo, Wyniki badań
Fuzzy systems, Polymers, Materials science, Research results
Uwagi
summ.
Abstrakt
This paper presents a multi-objective extended optimization methodology applied in the machining of a randomly oriented GFRP rod. Design of Experiment (DOE) has been selected based on a L9 orthogonal array design with varying process control parameters like: spindle speed, feed rate and depth of cut. Multiple surface roughness parameters of the machined FRP product along with the Material Removal Rate (MRR) of the machining process have been optimized simultaneously. The Fuzzy Inference System (FIS) has been proposed for providing feasible means for the meaningful aggregation of multiple objective functions into an equivalent single performance index (MPCI). This Multi-Performance Characteristic Index (MPCI) has been optimized using the Taguchi method. The approach adapted here is capable of overcoming limitations/ assumptions of existing optimization methodologies available in the literature. (original abstract)
Pełny tekst
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Bibliografia
Pokaż
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Cytowane przez
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ISSN
2300-7087
Język
eng
URI / DOI
http://dx.doi.org/10.7494/dmms.2013.7.1.19
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