Optimisation of packaging design for different functionalities using genetic algorithm
Dr Gonzalo Martinez-Hermosilla, Massey University
Packaging design involves trading off a wide range of different functionalities, including considerations of strength, volumetric efficiency, product cooling, handling and other factors. This study proposes a methodology for optimisation of packaging design based on hybrid genetic algorithm in order to maximise different functionalities desired for packaging systems. The functionalities covered by this methodology are cooling performance, mechanical performance, pallets stacking, container loads, cardboard usage and geometrical aspects of the packaging. The methodology was tested with two case studies: 1. Optimisation box dimensions to transport beef mince and 2.Optimisation of position and shape of handholes on small box panels. Five models were developed to represent all the functionalities included in this study. The models were solved by Comsol Multiphysics, Ansys APDL, and Cape Pack. A program was developed using Matlab that controls all these software, make interactions between results, and runs the hybrid genetic algorithm for box optimisation. The routine successfully found optimum designs for both case studies. The approach taken is an adaptable methodology so any other product or functionality can be used as the basis for optimisation.
Gonzalo is a Research Officer of the School of Engineering and Advanced Technology, Massey University, Palmerston North. He is an Agricultural Engineer with a PhD in Bioprocess Engineering with interest on mathematical modelling and optimisation of processes. Most of his research activity has been in the packaging, food, and postharvest sectors, where his work embraces both experimental and theoretical approaches. In particular, he has developed tools to design and optimise packaging systems for various high valued food products.