Machining Modeling: A Comparative Study | Comparison of Predictive Cutting Models Using RSM and RNA Approaches

Lakhdar Bouzid (u. a.)

ISBN 10: 6630113667 / ISBN 13: 9786630113662

Published by Our Knowledge Publishing, 2026

About this Item

Machining Modeling: A Comparative Study | Comparison of Predictive Cutting Models Using RSM and RNA Approaches | Lakhdar Bouzid (u. a.) | Taschenbuch | Englisch | 2026 | Our Knowledge Publishing | EAN 9786630113662 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.

Seller Inventory # 135723487

Bibliographic Details

• Title: Machining Modeling: A Comparative Study | Comparison of Predictive Cutting Models Using RSM and RNA Approaches
• Publisher: Our Knowledge Publishing
• Publication Date: 2026
• Language: English
• ISBN 10: 6630113667
• ISBN 13: 9786630113662
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 5D millimeters 220 millimeters width by 150 millimeters height by 5 millimeters depth
• Weight: 119 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

During machining, the conditions for success are determined in the cutting zone. In this context, the relationship between cutting conditions (cutting speed, feed rate, depth of cut, and tool type) and surface roughness (Ra and Rt) represents a major industrial objective. This work focuses on an experimental study examining the effects of cutting parameters on surface roughness, obtained during the machining of 42Cd4 steel (AISI 4140) hardened to 60 HRC, machined via dry hard turning using ceramic and metal carbide tools. The study is divided into two parts: the first focuses on proposing mathematical models to predict surface roughness, based on two modeling methods: the response surface methodology (RSM) and artificial neural networks (ANNs). The second part involves comparing the results of the two modeling methods-RSM and ANNs-in order to select the most effective one. Based on the comparative study, the ANN models proved to be better at predicting surface roughness within the range of the experiments conducted than the SRM models.