Plastic Manufacturing Convection-Diffusion Simulation Results

Ahmed M. Abed created a 5.5 KB Excel dataset containing numerical simulation results for a convection-diffusion model in plastic manufacturing. The data includes tabular and graphical outcomes from a mathematical poka-yoke simulator, used to analyze defect causes. The dataset was last updated in April 2026.

Use Cases

• Analyze the relationship between convective velocities, diffusion coefficients, and resulting error metrics like absolute error or L2 error.
• Validate numerical schemes like Runge-Kutta 4th order by comparing convergence rates across different simulation parameters.
• Correlate simulation parameters with operational metrics such as Overall Equipment Effectiveness (OEE) improvement from 76.6% to 88.9%.
• Use parametric analysis results to model the effect of time and location on defect generation in the plastic blowing and drying stages.

Strengths

• Dataset is openly licensed under CC-BY-4.0 for reuse.
• Includes specific performance metrics like a product quality improvement to a 5.2 sigma level.

Limitations

• Very small dataset at only 5.5 KB, indicating limited scope.
• No column names or sample data are provided, hindering immediate analysis.
• Temporal and geographic coverage of the underlying process is unspecified.

Provenance

Source

Authored by Ahmed M. Abed and hosted on figshare.

Collection Method

Generated from numerical simulation of a convection-diffusion model using discrete singular convolution and Runge-Kutta schemes.

Freshness

Last updated in April 2026.