Prediction of Vibrations & Cutting force of single point cutting tool in turning by using Artificial Neural Network

Inhaltsverzeichnis (Table of Contents)

• Nomenclature
• Introduction
  • Introduction to Machine Vibration
  • Neural Network
  • Artificial Neural Network
  • Mathematical model of Artificial Neural Network
  • Objectives of the Present Work
  • Methodology
  • Organization of the Report
  • Summary
• Literature Review
  • Introduction
  • Artificial Neural Network
  • Cutting tool vibrations
  • Cutting force
  • Summary
• Analysis of vibrations & forces in turning
  • Introduction
  • Vibrations on single point cutting tool in cutting
    • Types of vibrations
    • Vibration measurement using FFT Analyzer
  • Forces on single point cutting tool in cutting
  • Summary
• Experimentations
  • Introduction
  • Cutting Material
  • Cutting tool Material
    • Carbides
  • Adjustable Cutting Parameters in Turning as Input
    • Cutting speed
    • Feed
    • Depth of cut
  • Output parameters in Turning
    • Tool vibrations
    • Cutting Forces acting on single point cutting tool
  • Instrumentations
    • Lathe machine

Zielsetzung und Themenschwerpunkte (Objectives and Key Themes)

This dissertation aims to develop a model that simulates the vibrational effects of rotating machine parts on a single point cutting tool during the turning process. The study focuses on the relationship between machining parameters, such as spindle speed, feed, and depth of cut, and the resulting tool vibrations and cutting forces.

• Modeling of tool vibrations and cutting forces in turning
• Application of Artificial Neural Networks (ANN) to predict tool behavior
• Influence of machining parameters on tool vibration and cutting force
• Development of a predictive model for tool failure prevention
• Contribution to a deeper understanding of the turning process dynamics

Zusammenfassung der Kapitel (Chapter Summaries)

The dissertation begins with an introduction to machine vibration and neural networks, laying the foundation for the study's methodology. The literature review examines existing research on Artificial Neural Networks (ANN) and their applications in predicting cutting tool vibrations and forces. Chapter 3 delves into the analysis of vibrations and forces during turning, focusing on the types of vibrations and the measurement techniques used. Chapter 4 details the experimental setup, including the cutting materials, tool materials, adjustable parameters, and output parameters measured. The dissertation concludes with a summary of the findings and recommendations for future research.

Schlüsselwörter (Keywords)

This dissertation focuses on the prediction of vibration and cutting force in turning operations using Artificial Neural Networks. Key concepts include: vibration, cutting force, orthogonal cutting, Artificial Neural Network, machining parameters, tool failure prevention, turning process dynamics.