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Optimization of cutting parameters to minimize the surface roughness in the end milling process using the Taguchi method

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Detalhes bibliográficos
Resumo:This paper presents a study of the Taguchi design application to optimize surface quality in a CNC end milling operation. The present study includes feed per tooth, cutting speed and radial depth of cut as control factors. An orthogonal array of L9 was used and the ANOVA analyses were carried out to identify the significant factors affecting the surface roughness. The optimal cutting combination was determined by seeking the best surface roughness (response) and signal-to-noise ratio. The study was carried-out by machining a hardened steel block (steel 1.2738) with tungsten carbide coated tools. The results led to the minimum of arithmetic mean surface roughness of 1.662 µm, being the radial depth of cut the most influent parameter, with 64% of contribution for the workpiece surface finishing.
Autores principais:Ribeiro, J.E.
Outros Autores:Lopes, Hernani; Queijo, Luis; Figueiredo, Daniel
Assunto:Milling Cutting parameters Optimization Surface roughness Taguchi method
Ano:2017
País:Portugal
Tipo de documento:artigo
Tipo de acesso:acesso aberto
Instituição associada:Instituto Politécnico de Bragança
Idioma:inglês
Origem:Biblioteca Digital do IPB
Descrição
Resumo:This paper presents a study of the Taguchi design application to optimize surface quality in a CNC end milling operation. The present study includes feed per tooth, cutting speed and radial depth of cut as control factors. An orthogonal array of L9 was used and the ANOVA analyses were carried out to identify the significant factors affecting the surface roughness. The optimal cutting combination was determined by seeking the best surface roughness (response) and signal-to-noise ratio. The study was carried-out by machining a hardened steel block (steel 1.2738) with tungsten carbide coated tools. The results led to the minimum of arithmetic mean surface roughness of 1.662 µm, being the radial depth of cut the most influent parameter, with 64% of contribution for the workpiece surface finishing.