Paul Singh

Evaluation of the Stress-Energy Methodology to Predict Transmitted Shock through Expanded Foam Cushions

Mechanical stresses experienced by packages in the distribution environment include shock and vibration amongst several others. The destructive effects of these hazards can typically be restricted by using cushioning materials to help protect fragile goods during distribution. ASTM D1596 is the conventional standard used to determine shock absorbing performance of a cushioning material for a given combination of static loading, thickness, and drop height. This industry-accepted standard, however, requires significant amounts of transmitted shock data and can be expensive with respect to costs associated with testing and materials amongst others. Alternate stress-energy-based methodologies, developed in the past decade, recommending a considerable reduction in the number of drop tests while providing the ability to predict transmitted shock for any drop height, static loading as well as cushion thickness, are evaluated in this study for their stated accuracy. Based upon an in-depth evaluation of dynamic cushion curves for closed cell moldable foams generated using ASTM D1596, this research evaluates the accuracy of the proposed methodology in relation to the prediction of transmitted shock. Results show that the stress-energy methods while saving time in predicting transmitted shock, produce higher degrees of error than the ±5 % previously stated. In addition, they cannot predict behavior of cushions, and transmitted shock at high drop heights and static loadings with thin cushions, where only the measured values are accurate.

Evaluation of the gavarti associates-comprehensive abrasion tester

The GA-CAT (Gavarti Associates-Comprehensive Abrasion Tester) was put through sensitivity and repeatability studies to determine the variability associated with the machine. This was done to evaluate its ability to detect differences in quality within a batch of production run labels. The results showed that repeatability was poor so that quality variations in labels could not be assessed. The focus of the study therefore shifted to evaluating the causes of machine variability.