Plastic Injection Process Simulation Results and Error Metrics

5.5 KB of tabular data presents numerical simulation results for a convection-diffusion model used in plastic manufacturing. The dataset, created by Ahmed M. Abed, contains error metrics and outcomes from a mathematical poka-yoke simulator designed to reduce defects. It was last updated in April 2026.

Use Cases

• Analyze the rate of convergence, absolute error, L2 error, and L∞ error to validate the Mat-PYS simulation accuracy.
• Conduct parametric analysis using tabulated data on convective velocities and diffusion coefficients to understand their impact on results.
• Use the tabular outcomes to correlate simulation parameters with improvements in Overall Equipment Effectiveness (OEE) from 76.6% to 88.9%.
• Reference the error metrics and results at different time and location points to program the JRNS (Jidoka recruit's network system) for process control.

Strengths

• Data is openly licensed under CC-BY-4.0 for reuse.
• Includes specific performance metrics like L2 error and convergence rates for model validation.
• Simulation outcomes are linked to a concrete process improvement, raising OEE to 88.9%.

Limitations

• The dataset is very small at 5.5 KB, indicating limited scope and likely a small number of data points.
• No column names or sample data are provided, making the data structure and specific variables unclear.
• The description is highly technical and focused on methodology, with less detail on the raw data composition.

Provenance

Source

Ahmed M. Abed via figshare.

Collection Method

Generated from numerical simulations (Runge-Kutta 4th order, SSP-RK54 schemes) of a convection-diffusion model.

Freshness

Last updated in April 2026, indicating it is a forward-dated or planned update.