Statistical Process Control Workshop: Implementing Quality Control Techniques in Python
By
lifeisstillgood
Toasted golden, schmeared with insight. Top of the rack.
Summary
This is an educational workshop tutorial that teaches statistical process control (SPC) techniques using Python, specifically focusing on quality control applications. The content demonstrates how to use statistical tools and plotnine visualizations to measure variation in product quality over time and identify when intervention is needed. The workshop uses a case study of Japanese hot springs (onsen) economy to illustrate practical applications of SPC in quality control contexts.
Key quotes
· 4 pulledStatistical Process Control refers to using statistics to (1) measure variation in product quality over time and (2) identify benchmarks to know when intervention is needed.
In this workshop, we will learn how to perform statistical process control in Python, using statistical tools and plotnine visualizations!
For today's workshop, we're going to think about why quality control matters in a local economy, by examining the case of the Japanese Hot Springs bath economy!
Your online textbook for learning reliability and six sigma techniques in R and Python! Made for Cornell University Course SYSEN 5300.
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