Physics-Based 3D Simulation for Synthetic Data Generation and Failure Analysis in Packaging Stability Assessment

TL;DR

This paper introduces a physics-based 3D simulation system for generating synthetic data and analyzing pallet stability, reducing physical testing needs and supporting safety assessments in logistics.

Contribution

It presents a controllable simulation environment combined with neural network evaluation for improved safety analysis of pallet configurations.

Findings

Accurately simulates pallet dynamics with variable configurations.

Reduces costs and environmental impact of physical testing.

Uses neural networks to predict failure from simulated videos.

Abstract

The design and analysis of pallet setups are essential for ensuring safety of packages transportation. With rising demands in the logistics sector, the development of automated systems utilizing advanced technologies has become increasingly crucial. Moreover, the widespread use of plastic wrapping has motivated researchers to investigate eco-friendly alternatives that still adhere to safety standards. We present a fully controllable and accurate physical simulation system capable of replicating the behavior of moving pallets. It features a 3D graphics-based virtual environment that supports a wide range of configurations, including variable package layouts, different wrapping materials, and diverse dynamic conditions. This innovative approach reduces the need for physical testing, cutting costs and environmental impact while improving measurement accuracy for analyzing pallet dynamics. Additionally, we train a deep neural network to evaluate the rendered videos generated by our simulator, as a crash-test predictor for pallet configurations, further enhancing the system's utility in safety analysis.