عنوان	Neuro-fuzzy based predictive model for cutting force in CNC turning process of Al–Si–Cu cast alloy using modifier elements
نوع پژوهش	مقاله‌ی منتشر شده در نشریه
کلیدواژه‌ها	ANFIS · Turning · Cutting force · Aluminum alloys · Refinement elements
چکیده	This study investigated the predicted cutting force model of a turning operation for Al–Si–Cu cast alloy modified with modifiers based on adaptive neuro-fuzzy inference system (ANFIS) approach. Feed rate, cutting speed and Silicon spacing were considered as the input parameters. A series of turning experiments were conducted at various feed rates and cutting speeds. The prediction result showed that the ANFIS model successfully predicted the cutting force value in terms of cutting speed, feed rate and Si spacing. A mathematical model was proposed to describe the cutting force changes during the machining of Al–Si–Cu cast alloy. Moreover, the addition of Bismuth into the base alloy decreased the cutting force compared to other refinement elements
پژوهشگران	سعید فراهانی (نفر سوم)، محسن مارانی (نفر اول)، محمدجواد زینلی (نفر دوم)، کریس مچفسکه (نفر چهارم)