Advanced Technologies and Materials

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Vol. 26 No. 1 (2001): Journal for Technology of Plasticity
Original articles

Parametric/geometrical modelling of forged part families via a cad interface towards on-line internet based manufacturing and cost parameter prediction of designed products

J. Naude
Department of Mechanical and Manufacturing Engineering, Rand Afrikaans University, Johannesburg, South Africa
Z. Hoffman
Bay Zoltan Institute for Logistics and Production Systems, Miskolc, Hungary
L. Cser
Bay Zoltan Institute for Logistics and Production Systems, Miskolc, Hungary
P. Tamas
Bay Zoltan Institute for Logistics and Production Systems, Miskolc, Hungary

Published 2001-06-29

abstract views: 7 // Full text article (PDF): 6


Keywords

  • Parametric modelling,
  • Geometrical modelling,
  • E-commerce,
  • Neural Networks

How to Cite

Naude, J., Hoffman, Z., Cser, L., & Tamas, P. (2001). Parametric/geometrical modelling of forged part families via a cad interface towards on-line internet based manufacturing and cost parameter prediction of designed products. Advanced Technologies and Materials, 26(1), 1–9. Retrieved from https://jged.uns.ac.rs/index.php/atm/article/view/jtp.2001.27.1.1

Abstract

The co-ordination of work has a critical impact on organisational and business performance. In an era of ever-shorter product life cycles and lead times, it becomes a crucial necessity for companies to manage their internal and external transactions in an efficient, cost-effective way. Information technology has become the major enabler for speeding up communication and improving technical information exchange between the economic actors (customers and suppliers). In this paper we will describe the potential of information technologies for improving the technical information flow in order to reduce the transaction costs of a company. The ability to analyse and predict parameters related to the forging process will greatly improve the designing and manufacturing of forged parts as well as accurately predict the manufacturing costs involved. The research1 presented in this paper deals with the generation of parametric/geometric forge part family models. The information within these models is used to train backpropagation neural networks for economic and technical parameter prediction. Software were developed, tested and prove the concept viable. The implementation on the Internet as an e-commerce application is suggested.

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