An Introduction to Statistical Process Control Charts (SPC) Steve Harrison

An Introduction to Statistical Process Control Charts (SPC) Steve Harrison

Topics Variation A Quick Recap An introduction to SPC Charts Interpretation Quiz Application in Improvement work

Variation

Common Cause Variation Typically due to a large number of small sources of variation Example: Variation in work commute due to traffic lights, pedestrian traffic, parking issues Usually requires a deep understanding of the process to minimise the variation Multiple factors 5

Special Cause Variation Are not part of the normal process. Arises from special circumstances Example: Variation in work commute impacted by flat tyre, road closure, ice and snow. Usually best uncovered when monitoring data in real time (or close to that) Assignable cause 6

Special Cause - My trip to work 120 Min. 100 80 60 40 20 0 Upper process limit Mean Lower process limit Consecutive trips

Two Types of Variation Common Cause: chance cause noise Special Cause: assignable cause signal Statistically significant (not good or bad) 8

9 SPC Charts

SPC, Statistical Process Control or The Control Chart Elements 1. Chart/graph showing data, running record, time order sequence 2. A line showing the mean 3. 2 lines showing the upper and lower process control limits Its best if you have 25 data points to set up a control chart, but 50 are better if available. Be careful of too many points

The Anatomy of an SPC or Control Chart 80 70 60 50 40 30 20 10 0 F M A M J J A S O N D J F M A M J J A S O N D Upper process control limit Mean Lower process control limit

Measures of Central Tendency Mean = Average SPC Chart Median = Central or Middle Value Run Chart Mode = Most frequently occurring value 12

Standard Deviation or σ In statistics, standard deviation shows how much variation exists from the mean. A low standard deviation indicates that the data points tend to be very close to the mean; high standard deviation indicates that the data points are spread out over a large range of values.

Standard Deviation and a normal distribution

PRACTICAL INTERPRETATION OF THE STANDARD DEVIATION 99.7% will be within 3 s Mean - 3s Mean Mean + 3s

3s AND THE CONTROL CHART 3s 3s UCL Mean LCL 6s

4-Apr 6-Apr 8-Apr 12-Apr 14-Apr 18-Apr 20-Apr 22-Apr 3-May 5-May 9-May 11-May 13-May 15-May % Daily TTOs Completed by Noon Run Charts vs. SPC Charts Run Chart Simple Easy to create in Excel or on paper Less Sensitive Only need 12-15 data points Ward x % of total TTOs completed by 12 noon 80 April 4 - May 15, 2012 SPC More Powerful Control lines show the degree of variation Need software Better with 25+ data points 70 60 50 40 30 20 10 0 17

Special cause variation 90 80 70 60 50 40 30 20 10 0 F M A M J J A S O N D J F M A M J J A S O N D

SPECIAL CAUSES - RULE 1 UCL Point above Upper Control Limit (UCL) MEAN LCL

SPECIAL CAUSES - RULE 1 UCL MEAN LCL Or point below Lower Control Limit (LCL)

SPECIAL CAUSES - RULE 2 UCL MEAN LCL Eight points above centre line

SPECIAL CAUSES - RULE 2 UCL Or eight points below centre line MEAN LCL

SPECIAL CAUSES - RULE 3 UCL Six points in a downward direction MEAN LCL

SPECIAL CAUSES - RULE 3 UCL Or six points in an upward direction MEAN LCL

Quiz Does the chart show A. Special Cause Variation? B. Common Cause Variation? C. Both of the above D. No Variation 67% 33% 0% 0% Special Cause Variation? Common Cause Variation? Both of the above No Variation

How many special cause signals are present on this chart? A. 0 B. 1 C. 2 D. 3 E. 16 33% 67% 0% 0% 0% 0 1 2 3 16

How many special cause signals are present on this chart? A. 0 B. 1 C. 2 D. 3 E. 16 100% 0% 0% 0% 0% 0 1 2 3 16

How many special cause signals are present on this chart? A. 0 B. 1 C. 2 D. 3 E. 16 100% 0% 0% 0% 0% 0 1 2 3 16

What use is this? Evaluate and improve underlying process Is the process stable? Use data to make predictions and help planning Recognise variation Prove/disprove assumptions and (mis)conceptions Help drive improvement identify statistically significant change

Example

Annotated SPC Charts One of the most powerful tools for improvement Describe a process captured over time (as opposed to being a single sample) Reveal any trends a process might be experiencing When combined with careful annotation they track the impact of change

Annotated SPC Charts

Application Responding to Variation 33

Process with special cause variation Identify the cause: if positive then can it be replicated or standardized. If negative then cause needs to be eliminated Process with common cause variation Reduce variation: make the process even more reliable Not satisfied with result: redesign process to get a better result 34

PRACTICAL

Length Of Stay for Bowel Surgery Patients

Quality Composite Ratio

Outpatient attendances (Part 1)

Outpatient attendances (Part 2)

% discharged by noon

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