PREDICTION OF CUTTING PARAMETERS BY MILLING FUNCTIONALLY GRADED MATERIAL USING NEURAL NETWORK

Journal Title: Proceedings in Manufacturing Systems - Year 2014, Vol 9, Issue 2

Abstract

Paper shows the general characteristics of graded materials, their previous industrial use and potential use of graded materials in the future. In any case, today the use of graded materials is increasing and moving from the laboratory environment into everyday use. However, the subsequent processing of the graded material remains the big unknown, and represents a major challenge for researchers and industry around the world. It could be said that the study of machinability of these materials is in its infancy and in this area are many unanswered questions. Machinability problem of graded materials was undertaken at the Faculty of Mechanical Engineering in Maribor. After a radical study of the literature and potential machining processes of graded materials, we started with the implementation of cutting processes on the workpiece. This professional paper presents the first results of the analysis, which will be used for further research and machinability study of graded materials. Also prediction of cutting forces with neural network by milling functionally graded material was made. In paper first predicted cutting forces by milling graded material are presented.

Authors and Affiliations

T. Irgolic, U. Zuperl, F. Cus

Keywords

Related Articles

Creep testing of epoxy resin-flax fiber composites

The present study proposes an experimental approach into determining the viscoelastic characteristics of a composite made out of an epoxy-resin matrix with long flax fiber reinforcement. In a first instance, the fabricat...

Methodology for efficiency improvement in warehouses: a case study from the winter sports equipment industry

The paper considers a methodology for efficiency improvement in warehouses. The methodology is developed for the needs of the winter sports equipment division of Amer Sports Corporation. Key aspects of the methodology ar...

Manufacturing performance improvement of complex products based on coding and parameterisation: a case study

This work presents a case study referring to the way in which a complex product design is linked to the manufacturing processes which are necessary to make it. The product is a mobile cement pump consisting of 8 sub-asse...

The implementation of a modular open architecture PC-based CNC system used as a research and education equipment

Open-architecture CNC technological equipment are used nowadays both for industrial and educational purposes. Using a modular structure and a PC-based CNC controller, these devices allow the users to develop and test new...

Remote control of hydrostatic drive mechanisms for hoisting machinery and logistics centers

The analysis of the crane or loader travel mechanism construction with hydrostatic drive and low-moment hydraulic motor has been performed. It has been proposed that the electric circuit of pump performance remote contro...

Download PDF file
  • EP ID EP121923
  • DOI -
  • Views 102
  • Downloads 0

How To Cite

T. Irgolic, U. Zuperl, F. Cus (2014). PREDICTION OF CUTTING PARAMETERS BY MILLING FUNCTIONALLY GRADED MATERIAL USING NEURAL NETWORK. Proceedings in Manufacturing Systems, 9(2), 75-80. https://europub.co.uk./articles/-A-121923