Abstract
We develop a back-propagation neural network (BPN) to predict the life-cycle design performance for transport packaging. The BPN is constructed and trained on the packaging design attributes to detect hidden relationships among historical or pre-existing life-cycle design data to predict a new concept design through supervised learning, by minimizing the squared difference between the actual and the predicted life-cycle design performance. To this end, the designer could use the predicted life-cycle design in a trade-off analysis and concept selection for a potential packaging design. A case example is used to illustrate the methodology.
Keywords
Back-propagation neural network (BPN), life-cycle design, transport packaging
Subject Categories
Production engineering
Disciplines
Engineering
Publisher
Omnipress
Publication Date
2005
Rights Information
Copyright 2005, Surendra M. Gupta
Rights Holder
Gupta M. Surendra
Permanent URL
Recommended Citation
Gupta, Surendra M.; Jarupan, Lerpong; and Kamarthi, Sagar V., "Prediction of packaging life-cycle design performance" (2005). . Paper 93. http://hdl.handle.net/2047/d10013520
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Notes
Originally published in the Proceedings of the 2005 Northeast Decision Sciences Institute Conference, Philadelphia, Pennsylvania, March 30-April 1, 2005 (CD-ROM)