{"id":2629,"date":"2024-10-09T10:10:36","date_gmt":"2024-10-09T08:10:36","guid":{"rendered":"https:\/\/ellistat.com\/?post_type=guide-dutilisateur&p=2629"},"modified":"2024-10-21T15:24:50","modified_gmt":"2024-10-21T13:24:50","slug":"01-fact-2-taguchi","status":"publish","type":"guide-dutilisateur","link":"https:\/\/ellistat.com\/en\/guide-dutilisateur\/01-fact-2-taguchi\/","title":{"rendered":"Taguchi Designs - Orthogonal Arrays (Fact 2)"},"content":{"rendered":"

Visit Taguchi method<\/strong> is a statistical approach to Design of Experiments (DOE) that aims to optimize processes while reducing product variability. This method is particularly useful in industrial environments, where it is crucial to improve product quality and performance while minimizing costs and resource utilization.<\/p>\n\n\n\n

Taguchi uses a two-level experimental design, which means that each factor under study is tested at two distinct levels, generally referred to as low and high level. This approach is ideal for studies seeking to understand the main effects of factors and their interactions, while keeping the experimental framework simple and efficient.<\/p>\n\n\n\n

Ellistat offers a range of experimental designs based on the Taguchi method, adapted to the number of factors to be studied. The table below summarizes the different experimental designs available.<\/p>\n\n\n

\n
\"\"<\/figure>\n<\/div>","protected":false},"featured_media":0,"template":"","meta":{"_acf_changed":false},"menu-guide-dutilisateur":[24],"class_list":["post-2629","guide-dutilisateur","type-guide-dutilisateur","status-publish","hentry","menu-guide-dutilisateur-6-doe-plans-dexperiences"],"acf":[],"yoast_head":"\nPlan d'experience Taguchi (Fact 2) - Ellistat<\/title>\n<meta name=\"description\" content=\"Comment r\u00e9aliser un plan d'experience de Taguchi (Fact 2) avec Ellistat ? 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