Statistical Process Control in Python
5 hours ago
- #Python
- #Statistical Process Control
- #Quality Control
- Introduction to Statistical Process Control (SPC) in Python, focusing on measuring variation and identifying intervention benchmarks.
- Setup involves installing pandas, plotnine, and scipy packages, and importing custom functions for distributions and process control.
- Case study on Japanese Hot Springs (onsen) quality control, highlighting temperature, pH, and sulfur levels as key metrics.
- Data collection involves 15 months of 20 random samples each, aiming to monitor quality shifts in onsen attributes.
- Descriptive statistics and visualization techniques are introduced to analyze process variation and subgroup statistics.
- Control charts (X-bar and S charts) and moving range charts are demonstrated for monitoring process stability and variation.