Statistical Process Control CBE / MET 433 20 April 2012 Statistical Process Control

World Class Quality (Shewhart..1960) “On-Target with Minimum Variance.” Operating “On-Target” requires a different way of thinking about our processes. Operating with “Minimum Variance” is achieved only when a process displays a reasonable degree of statistical control. “Good Parts” vs “Bad Parts”

World Class Quality (Shewhart..1960) “On-Target with Minimum Variance.” Operating “On-Target” requires a different way of thinking about our processes. Operating with “Minimum Variance” is achieved only when a process displays a reasonable degree of statistical control. “Good Parts” vs “Bad Parts”

World Class Quality (Shewhart..with an in-control process) MAKE  PACK  SHIP

World Class Quality (Shewhart..w/in-control process) MAKE  PACK  SHIP Challenges: Examples from industry: Polymer gum in fiberpac Corn sweetener “Crystal Clear”

Shewhart: “While every process displays variation, some processes display controlled variation while others display uncontrolled variation.” Controlled Variation: Stable, consistent pattern of variation over time. “Chance” causes.

Shewhart: “While every process displays variation, some processes display controlled variation while others display uncontrolled variation.” Controlled Variation: Stable, consistent pattern of variation over time. “Chance” causes. Uncontrolled Variation: Pattern of variation that changes over time. “Assignable” causes.

Shewhart: “While every process displays variation, some processes display controlled variation while others display uncontrolled variation.” Controlled Variation: Stable, consistent pattern of variation over time. “Chance” causes. Uncontrolled Variation: Pattern of variation that changes over time. “Assignable” causes. Shewhart: “A phenomenon will be said to be controlled when, through the use of past experience, we can predict, at least within limits, how the phenomenon may be expected to vary in the future.”

Statistical Control Predictability Use statistics to highlight uncontrolled variations Eliminate uncontrolled variations Next: Control Charts as a way to see uncontrolled variations.

Statistical Measures Location: What can we use? Dispersion: What can we use?

Look at example (Camshaft Bearings) Statistical Measures Location: What can we use? Dispersion: What can we use? Look at example (Camshaft Bearings)

= 1.375146 = 1.374978 = 1.374820 R = 0.00080 = 0.000750 = 0.00120 S = 0.0001697 = 0.0001697 = 0.0003576

Controlled Variation Subgroups used (4-5) Reason: use of mean tends to normalize information (distribution of the subgroup average) Shewhart: pick subgroups to organize the data into a rational manner.

Uncontrolled Variation Gather 20 – 30 subgroups before calculating the control limits

Questions?

Questions?

Questions?