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Variability & Statistical Process Control

Variability & Statistical Process Control. Outline. Section 1: Understanding the Impact of Variation Section 2: Process Control Systems Section 3: Measurement Capability Analysis. What is Variation?. Loss Function What is the target for a given process?

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Variability & Statistical Process Control

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  1. Variability & Statistical Process Control

  2. Outline Section 1: Understanding the Impact of Variation Section 2: Process Control Systems Section 3: Measurement Capability Analysis

  3. What is Variation? Loss Function What is the target for a given process? How far away from the target is still OK? ? ? Target

  4. What is Variation? A curve representing loss in quality as a function of a measured value Loss Function Loss in Quality target Measurement

  5. What is Variation? Traditional “Loss Function” Spec limits define acceptable and unacceptable quality Loss in Quality Lower Spec Limit Upper Spec Limit

  6. What is Variation? Modern “Loss Function” Target: Desired Value or Outcome Loss in Quality Increases as Variation from Target Increases Loss in Quality Target

  7. LSL USL What is Variation? How the Loss Function Affects Product Both are within spec Which is more desirable? LSL USL

  8. What is Variation? Loss Function for Defects Loss in Quality Number of Defects Target

  9. What is Variation? Less Variation = Higher Quality

  10. Examining Variation Definition A Stable Processhas the same normal distribution at all times. A stable process is In Control A stable process still has variation

  11. Examining Variation Stable Process Normal distribution at all times Prediction Time

  12. Examining Variation Common Causes The cause of variations in a stable process is called a Common Cause. A common cause is a natural cause of variation in the system.

  13. Examining Variation Common Cause Examples • Machine vibration • Temperature fluctuations • Slight variation in raw materials • Human variation in setting control dials

  14. 200 200 180 180 160 160 140 140 120 120 Thickness 100 100 80 80 60 60 40 40 20 20 0 0 Time Examining Variation Tools for Examining Stability Trend Chart: A plot showing the behavior of a process over time.

  15. Examining Variation 35 Tools for Examining Stability Histogram: A barchart showing the distribution of the process. 30 25 20 Percentage 15 10 5 0 0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200 Thickness

  16. 0 5 10 15 20 25 0 5 10 15 20 25 Sequence Sequence Examining Variation Activity: Comparing stable processes Which process has better quality? 150 150 140 140 130 130 120 120 110 110 Thickness Thickness 100 100 90 90 80 80 70 70 60 60 50 50 B A

  17. 0 5 10 15 20 25 0 5 10 15 20 25 Sequence Sequence Examining Variation Activity: Comparing stable processes (cont’d) Which process has better quality? 150 150 140 140 130 130 120 120 110 110 Thickness Thickness 100 100 90 90 80 80 70 70 60 60 50 50 B A

  18. Examining Variation Unstable Process Any process that is not stable is called an unstable or out-of-control process. ? ? Prediction Time

  19. Examining Variation Kinds of Instability: Excursions 200 200 180 180 160 160 140 140 120 120 Thickness 100 100 80 80 60 60 40 40 20 20 0 0 Time

  20. Examining Variation Kinds of Instability: Shifts 200 200 180 180 160 160 140 140 120 120 Thickness 100 100 80 80 60 60 40 40 20 20 0 0 Time

  21. Examining Variation Kinds of Instability: Drifts 200 200 180 180 160 160 140 140 120 120 Thickness 100 100 80 80 60 60 40 40 20 20 0 0 Time

  22. Examining Variation Kinds of Instability: Cycles 200 200 180 180 160 160 140 140 120 120 Thickness 100 100 80 80 60 60 40 40 20 20 0 0 Time

  23. Examining Variation Kinds of Instability: Chaos 200 200 180 180 160 160 140 140 120 120 Thickness 100 100 80 80 60 60 40 40 20 20 0 0 Time

  24. Examining Variation Special Causes Anything that causes variations that are not part of the stable process is called a special cause, assignable cause, or unnatural cause.

  25. Examining Variation Examples of Special Causes • Batch of defective raw material • Faulty set-up • Human error • Incorrect recipe • Blown gasket • Earthquake

  26. Reducing Variation Improving a Stable Process Two strategies for improving a stable process • Centering at Target • Reducing Common Cause Variation

  27. Reducing Variation Centering at Target 200 200 180 180 160 160 140 140 120 120 Thickness 100 100 80 80 60 60 40 40 20 20 0 0 Time

  28. Reducing Variation Reducing Common Cause Variation 200 200 180 180 160 160 140 140 120 120 Thickness 100 100 80 80 60 60 40 40 20 20 0 0 Time

  29. Reducing Variation Reducing Variation in a Stable Process Make Permanent Changes Changes are based on the scientific approach • Structured problem solving • Planned experiments Examples: new equipment, equipment upgrade, new procedure, new machine settings, better raw material

  30. Reducing Variation Reducing Variation in an Unstable Process • Do not ignore special causes. • Do quickly detect special cause variations. • Do stop production until the process is fixed. (Reactive) • Do identify and permanently eliminate special causes. (Preventive)

  31. Reducing Variation Improving an Unstable Process Four Step Process • Detect the special cause variation. • Identify the special cause. • Fix the process • Remove the special cause, or • Compensate for the special cause. • Prevent the special cause from occurring again

  32. 200 200 180 180 160 160 140 140 120 120 Thickness 100 100 80 80 60 60 40 40 20 20 0 0 Time Reducing Variation Improving an Unstable Process Reactive Not Here Detect Here Detect Here

  33. 200 200 180 180 160 160 140 140 120 120 Thickness 100 100 80 80 60 60 40 40 20 20 0 0 Time Reducing Variation Improving an Unstable Process Preventive Unstable Stable

  34. Detecting Variation How can we decide if variation is the result of common or special cause?

  35. 200 200 180 180 160 160 140 140 120 120 Thickness 100 100 80 80 60 60 40 40 20 20 0 0 Time Detecting Variation Tool: Control Chart Benefit: Prevents tampering or ignoring

  36. Observe Variation Common Cause Detect Special Cause Don’t Tamper Identify Fix Reduce Overall Variation Prevent Detecting Variation Control Chart for Detecting Variation Control Chart

  37. Detecting Variation Control Chart for Detecting Variation Control Chart Trend Chart Center Line Control Limits + + Upper Control Limit Center Line Lower Control Limit

  38. Lower Control Limit Upper Control Limit Detecting Variation Control Limits Control limits tell us where the measurements in a stable process should fall

  39. Detecting Variation -3s +3s Control Limits Calculated statistically, based on: • Historical Data • Characteristics of the stable process Also called 6 sigma limits Highly Unlikely 1.5 out of 1000 Highly Unlikely 1.5 out of 1000

  40. Detecting Variation Creating a Control Chart Turn the distribution on its side Upper Control Limit Center Line Lower Control Limit

  41. Detecting Variation Can we use spec limits as control limits? Can we compute control limits for an unstable process?

  42. Detecting Variation Creating a Control Chart What is the Center Line? Process mean, based on historical data or Process Target

  43. Detecting Variation Creating a Control Chart Selecting the Center Line The center line should be the target, unless we are unable or unwilling to control the process to target. Measurements: Defects: Since the target is zero defects, the center line is the process mean.

  44. Control Limits Based on performance of the process. Tell us when to take action on the process. Spec Limits Based on performance of the product. Tell us when to disposition the product. Detecting Variation Control Limits vs. Spec Limits

  45. Focus On Control Limits Improve Process Quality Spec Limits Improve Product Quality Detecting Variation Control Limits vs. Spec Limits

  46. Detecting Variation Uses of a Control Chart • On-Line: Assess the present stability of a process, as part of a process control system (PCS) • Off-Line: Assess the historical stability of a process

  47. Observe Variation Detect Special Cause Common Cause Identify Don’t Tamper Fix Reduce Overall Variation Prevent What is a PCS? A PCS is a subset of the Reduction in Variation flow Control Chart

  48. What is a PCS? Definition A process control system is an on-line, real-time system for identifying and responding to process/equipment problems

  49. What is a PCS? Elements of a Process Control System • Measurements • Calculations • Control Chart • PCS Rules • Response Flow

  50. Elements of a PCS PCS Rules Set of rules applied to the data plotted on the control chart to determine if the process is stable or unstable.

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