Dr. Joan Burtner Certified Quality Engineer

Associate Professor of Industrial Engineering and Industrial Management

The Certified Quality Engineer Handbook The Certified Quality Engineer Handbook Examples from Ch. 37: Statistical Process Examples from Ch. 37: Statistical Process

Control (SPC)Control (SPC)

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Quality as a System Characteristic

Goal: A stable Quality Management System (QMS) with well-defined policies and procedures and a culture of compliance with those procedures.

System Characteristics:

System Out of Control One or more processes exhibit special causes.

System in Control There is no evidence of special causes within the system.

Improved System in Control Stable processes are continuously being improved.Source : Dean (2013) Lean Healthcare Deployment and Sustainability

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Borror: Chapter 37 Review of Charts Construction of Control Charts

Control Charts for Attributes Control Charts for Variables

Interpretation of Control Charts “Manual” Application of Tests Statistical Software Application of Tests

Other Process Charts

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Control Limits, Random and Nonrandom Sample Observations

UpperControlLimit(UCL)

LowerControlLimit(LCL)

ProcessMean

Sample number

1 3 4 5 6 7 8 92 10 11 12

Non-random

99.7

%

+3σ

-3σ

Source: Ozcan Figure 12.4 (Modified for Three Sigma Limits)

Non-random

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Statistical Control Chart Types

Attributes

Mean Charts (X-bar Charts)

c-chart p-chart

Variables(Subgroups)

Variation Charts

σ Method

Range Method

u-chart

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Variables Control Charts (Continuous Data)

When process characteristics can be measured, variables control charts are the appropriate way to display the process monitoring.

The Xbar-chart and the Range chart are displayed and interpreted together. When the Range chart exhibits out-of-control status, the rules for evaluating the Xbar-chart should not be used.

The Xbar chart is appropriately evaluated after the Range chart indicates that the process is in control. Use caution in interpretation when using statistical software that evaluates both charts simultaneously.See examples on pages 496-499.

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Variables Control Chart for n = 1

Variables (Individuals)

Mean Charts (X-bar Charts)

Individual observation

Variables(Subgroups)

Variation Charts

σ Method

Range Method

Moving Range

Note that the tests that apply to the subgroup charts do not apply to the Individuals Charts.

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Attribute Control Charts (Discrete Data)

When process characteristics can be counted, attribute-based control charts are the appropriate way to display the process monitoring.

The p-chart is the appropriate control chart for a process with only two outcomes (defective or not defective) when the proportion defective is calculated. The c-chart is the appropriate tool to display monitoring if the number of occurrences per sampling period is recorded.

The u-chart is the appropriate control chart if the number of occurrences and the number of items per sampling period is recorded. The average number of occurrences per sample is calculated.

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Attribute Control Charts (Discrete Data)

See text for examples of p-chart.

See text for examples of c-chart.

We will discuss the u-chart example in class.

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Borror: Example 37.4

A random sample of 1000 account activities is collected weekly for 12 weeks. The institution would like to monitor the proportion of errors.

Week Activities in Error Week Activities in Error

1 6 7 9

2 11 8 8

3 4 9 12

4 10 10 7

5 5 11 12

6 30 12 11

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37.4 Chart Construction and Analysis

Are the data discrete or continuous?

Discrete

Do the data fit the requirements of a p , c, or u chart?

p chart

What tests for special causes apply to this type of chart?

Extreme point, trend, shift in mean, oscillation

Zone rules (A,B,C) do not apply to p charts

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37.4 Chart Analysis

Original control chart produced using Minitab 15

Evidence of special cause (extreme point)

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37.4 Process Improvement

Assignable cause is identified for the out of control point. Sample point 6 is eliminated and a new control chart is produced using Minitab 15.

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Other Charts

Cumulative Sum Charts

EWMA Charts

Moving Average Charts

*******Pre-control Charts *******

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References / Contact Information

Contact Information:Dr. Joan Burtner Burtner_J@Mercer.edu

Borror, C, Ed. (2009). The Certified Quality Engineer Handbook 3rd edition, Milwaukee, WI: ASQ Quality Press. Dean, M.L. (2013). Lean Healthcare Deployment and Sustainability. New York, NY: McGraw Hill.

Ozcan, Y. (2009). Quantitative Methods in Health Care Management 2nd ed, San Francisco, CA: Jossey-Bass.