Predicting creep lifetime performance in edgewise compression of containerboards and for stacked corrugated board boxes

Abstract

Predicting how long time a corrugated board box can be stored with a constant load stacked on top of it without failing is an everyday challenge for a box designer. This is a basic step in corrugated board box material design which is usually resolved by utilizing so-called stacking factors. A stacking factor is the ratio between the compression strength of the box and the stacking load. Higher stacking factors are used to accommodate for longer storing times or high relative humidity conditions. Utilizing stacking factors in the way commonly done today can be a good first approximation. However, this method often neglects or overcompensates for the inherent nonnormal distribution statistical behaviour associated with corrugated board box lifetimes. A higher precision in predicting box lifetimes enables material optimization and, thus, a more efficient use of resources. This work presents a convenient way of predicting lifetimes of both containerboards and corrugated board boxes. The approach additionally introduces the concept of reliability into lifetime prediction.The prediction is made directly from material or structural parameters and the applied load. This is accomplished by relating two different parameter sets for the Weibull distribution. It is shown that lifetime is indeed dependent not only on a stacking factor but also on durability and the variations associated with the material or box.

Radar cross section statistical characteristics of stealth aircraft using the Weibull‐generalized gamma mixture model

“…Figure 1E,F illustrates the Weibull plots of RCS data given in Figure 1C,D. The axes are $$Y=\mathrm{ln}(-\mathrm{ln}(1-F(\sigma )))$$ vs. $$X=\mathrm{ln}(\sigma )$$, where $$F(\sigma )$$ is the empirical distribution function of RCS data $$\sigma $$ 15,16 . The best regression lines of the Weibull plots are also illustrated respectively.…”

“…vs. X σ = ln( ) , where F σ ( ) is the empirical distribution function of RCS data σ. 15,16 The best regression lines of the Weibull plots are also illustrated respectively. If RCS data follows the Weibull distribution, the Weibull plot follows a straight line.…”

Creep behaviour of day‐old chicken corrugated paperboard packaging under different uniaxial compression loads—An experimental study

“…29 Several researchers have investigated the so-called creep deformation of corrugated board and its components under constant load. [30][31][32][33][34][35][36][37][38][39][40][41] The studies concluded that cyclical changes in humidity generally cause higher creep rates than holding humidity constant. Other studies showed that the creep deformation has three stages: primary, secondary and tertiary (see Figure 2).…”

“…Several researchers have investigated the so‐called creep deformation of corrugated board and its components under constant load 30–41 . The studies concluded that cyclical changes in humidity generally cause higher creep rates than holding humidity constant.…”