Page 19 - eBook_Proceedings of the International Conference on Digital Manufacturing V2

Collaborative Study on Weight Optimisation of Lubricant Bottles under
Stacking Condition using Finite Element Analysis and Machine Learning

Moreover, the bottles at the lowest layer are often collapsed
when subjected to the external top load being applied during
stacking condition (Suvanjumrat & Chaichanasiri, 2014).
Therefore, to avoid collapsing and increase their recyclability, a
comprehensive solution is needed to improve the bottles’ design
while confirming that the original strength and stiffness is not
compromised.

Figure 1: Representation of major challenges linked with the
structural design of HDPE bottles under stacking condition

Many manufacturing companies also intend to achieve the
optimal weight of containers that help them to minimise their
production cost. Therefore, there are several studies that attempted
to conduct the structural analysis of HDPE and PET-based bottles
through three different modelling: finite element technique,
experimental technique, and machine learning. Suvanjumrat &
Chaichanasiri (2014) subjected the creep behaviour of HDPE
lubricant oil bottles under constant load over the course of a
month. The finding identified the weak points on bottles and
showed that the deformation of bottle models increased with
increasing stacking load and time. Huang, Chen, Lu, Lin & Chen
(2018) studied the effect of bottle thickness through elastic-plastic
dynamic behaviour of 2800 ml HDPE milk bottle and proposed an
optimise design, having a possible weight reduction of 21.4%

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