Abstract
A neural network approach is presented for the estimation of shape change during a Hot Isostatic Pressing (HIP) process of nickel-based superalloys for near net-shape manufacture. For the HIP process, shrinkage must be estimated accurately; otherwise, the finished piece will need excessive machining and expensive nickelbased alloy powder will be wasted (if overestimated) or the part will be scrapped (if underestimated). Estimating shape change has been a very difficult task in the powder metallurgy industry and approaches range from rules of thumb to sophisticated finite element models. However, the industry still lacks a reliable and general way to accurately estimate final shape. This paper demonstrates that a neural network approach is promising to estimate post-HIP dimensions from a combination of pre-HIP dimensions, powder characteristics and processing information.
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References
Atkinson HV, Rickinson B A, (1991) Hot Isostatic Processing. Galliard Printers Ltd., Norfolk, UK.
Cherian RP, Smith LN, Midha PS, (2000) A neural network approach for selection of powder metallurgy materials and process parameters. Artificial Intelligence in Engineering, 14 39–44.
Kalpakjian S, (1995) Manufacturing Engineering and Technology. Addison-Wesley Publishing Company, Inc.
Khazami-Zadeh M, Petzoldt F, (1995) Hot isostatic pressing of near net shape parts through finite element simulation, Advances in Powder Metallurgy and Particulate Materials Proceedings of the 1995 International Conference & Exhibition on Powder Metallurgy & Particulate Materials. 2:5/125–5/138.
MPIF, (2001), web site: <http://www.mpif.org>.
NCEMT, (2001), web site: <http://www.ncemt.ctc.com/modsim/hip>.
Nissen A, Jaktlund L-L, Tegman R, Garvare, T, (1989) Rapid computerized modeling of the final shape of HIPed axisymmetric containers. Proceedings of Second International Conference on Hot Isostatic Pressing: Theory and Applications, 55–61.
Smith LN, Midha PS, (1999) A knowledge based system for optimum and concurrent design, and manufacture by powder metallurgy technology. Internationaljournal of Production Research, 37(1): 125–137.
Twomey JM, Smith AE, (1998) Bias and variance of validation methods for function approximation neural networks under conditions of sparse data. IEEE Transactions on Systems, Man, and Cybernetics, Part C, 28:417–430
Udo GJ, (1992) Neural network applications in manufacturing processes. Computers and Industrial Engineering, 23:97–100.
Wilson RK, Flower HL, Hack GAJ, Isobe S, (1996) Nickel-base alloys for severe environments. Advanced Materials & Processes, 3:19–22.
Zhang H-C, Huang SH, (1995) Applications of neural networks in manufacturing: A state-of-the-art survey. International Journal of Production Research, 33:705–728.
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© 2002 Springer-Verlag London
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Dengiz, O., Konak, A., Kulturel-Konak, S., Smith, A.E., Nettleship, I. (2002). Neural Computing Approach to Shape Change Estimation in Hot Isostatic Pressing. In: Parmee, I.C. (eds) Adaptive Computing in Design and Manufacture V. Springer, London. https://doi.org/10.1007/978-0-85729-345-9_15
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DOI: https://doi.org/10.1007/978-0-85729-345-9_15
Publisher Name: Springer, London
Print ISBN: 978-1-85233-605-9
Online ISBN: 978-0-85729-345-9
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