Modeling of the fundamental mechanical interactions of unit load components during warehouse racking storage

The global supply chain has been built on the material handling capabilities provided by the use of pallets and corrugated boxes. Current pallet design methodologies frequently underestimate the load carrying capacity of pallets by assuming they will only carry uniformly distributed, flexible payloads. But, by considering the effect of various payload characteristics and their interactions during the pallet design process, the structure of pallets can be optimized. This, in turn, will reduce the material consumption required to support the pallet industry.

In order to understand the mechanical interactions between stacked boxes and pallet decks, and how these interactions affect the bending moment of pallets, a finite element model was developed and validated. The model developed was two-dimensional, nonlinear and implicitly dynamic. It allowed for evaluations of the effects of different payload configurations on the pallet bending response. The model accurately predicted the deflection of the pallet segment and the movement of the packages for each scenario simulated.

The second phase of the study characterized the effects, significant factors, and interactions influencing load bridging on unit loads. It provided a clear understanding of the load bridging effect and how it can be successfully included during the unit load design process. It was concluded that pallet yield strength could be increased by over 60% when accounting for the load bridging effect. To provide a more efficient and cost-effective solution, a surrogate model was developed using a Gaussian Process regression. A detailed analysis of the payloads' effects on pallet deflection was conducted. Four factors were identified as generating significant influence: the number of columns in the unit load, the height of the payload, the friction coefficient of the payload's contact with the pallet deck, and the contact friction between the packages. Additionally, it was identified that complex interactions exist between these significant factors, so they must always be considered.