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.
Back-propagation neural network (BPN), life-cycle design, transport packaging
Copyright 2005, Surendra M. Gupta
Gupta M. Surendra
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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