Dataset for "Study of thickness distribution on a robotic rotational moulding system by experiment and simulation"

For 50 years, robotic systems have automated injection moulding. While rotational moulding is less advanced, recent innovations like ROBOMOULD® have improved its process control. This technology uses a 6-axis robot arm to manipulate the mould, enabling precise control over thickness distribution.

This dataset is the measurement results from a full factorial study to study the three control parameters (rocking angle, rotations per rock, and robot feed rate or speed) of this robotic rotational moulding system. The moulded parts were produced using an industrial sized fuel tank mould on the robotic moulding system. This study compares experimental and simulated thickness distributions in robotic rotational moulding. A MATLAB-based finite element model predicts thickness distribution based on powder contact time. Results show that robot feeding rate and the interaction between rocking angle and rotations per movement significantly influence thickness distribution. The simplified simulation model accurately predicts trends at higher feeding rates.

These measurement results can be used to inform future experiments, calibrate simulation models, or validate existing simulations.
The most up-to-date version of this dataset can be found in Queen's University Belfast Open Research Repository (ORR) at https://doi.org/10.17034/30230857.v1
This is the updated version of the dataset, which is available via CC BY 4.0. It relates to the connected research article.

An earlier less complete version of the dataset can be found at DOI: 10.17034/2942d476-c73b-4238-8b9b-7800ccbba979