How to Create a Statistical Process Control for Local Government
A procedure for using statistical methods to monitor and control processes, ensuring they operate within defined control limits and produce consistent outputs.
Purpose
To detect process variation early, distinguish between common cause and special cause variation, and maintain process stability for consistent service and service quality.
Scope
Applies to production, manufacturing, and service delivery processes where key quality characteristics can be measured and monitored statistically.
Prerequisites
- Identified critical quality characteristics for monitoring
- Defined measurement methods and data collection procedures
- Statistical process control software or control chart tools
- Trained operators and quality staff in SPC concepts and chart interpretation
Supports Local Government Act compliance, freedom of information requirements, and public accountability standards.
Step-by-Step Procedure
Select Process and Quality Characteristic
Identify the process and the critical quality characteristic to be monitored using statistical process control.
- 1.1Review process risk assessments and quality data to prioritise characteristics
- 1.2Select the quality characteristic that has the most impact on community member satisfaction or process performance
- 1.3Define the measurement method and measurement system requirements
Establish Control Limits
Calculate the control limits for the selected characteristic based on initial process data collected under stable conditions.
- 2.1Collect initial data from the process under normal operating conditions
- 2.2Calculate the process mean and standard deviation
- 2.3Calculate the upper control limit and lower control limit
- Use at least 20 to 25 subgroups of data to establish reliable control limits
Set Up Control Charts
Create the appropriate type of control chart for the quality characteristic and populate it with the calculated control limits.
- 3.1Select the appropriate chart type such as X-bar and R chart, or individuals chart
- 3.2Configure the chart with the calculated centre line and control limits
- 3.3Set up the chart display in the SPC system or at the workstation
Monitor the Process
Collect ongoing data and plot it on the control chart at defined intervals to monitor process stability.
- 4.1Collect measurement data at the specified sampling frequency
- 4.2Plot the data on the control chart
- 4.3Check for out-of-control signals after each data point
Respond to Out-of-Control Signals
When an out-of-control signal is detected, investigate the cause and take appropriate action to bring the process back into control.
- 5.1Identify the type of out-of-control signal on the chart
- 5.2Investigate the potential special cause using process knowledge and data
- 5.3Take corrective action to eliminate the special cause
- 5.4Document the investigation and action taken
- Do not adjust a stable process in response to common cause variation
Review and Update Control Limits
Periodically review the control limits and update them when the process has changed or improved.
- 6.1Review control chart performance at scheduled intervals
- 6.2Recalculate control limits when a significant and intentional process change has been implemented
- 6.3Document the rationale for any control limit changes
Quality Checkpoints
Common Mistakes to Avoid
Expected Outcomes
Percentage of time the process operates in statistical control, indicating consistency.
Average time from detecting an out-of-control signal to identifying and resolving the special cause.
Frequently Asked Questions
What are the common out-of-control signals?
Common signals include a point beyond the control limits, seven consecutive points above or below the centre line, seven consecutive points trending up or down, and other patterns defined by the Western Electric or Nelson rules.
How often should data be plotted on the control chart?
Sampling frequency depends on the process speed, cost of sampling, and risk. High-speed processes may require frequent sampling, while slow processes may be sampled less often. The key is to detect changes before a significant number of non-conforming units are produced.
What is the difference between control limits and specification limits?
Control limits are calculated from process data and reflect the natural variation of the process. Specification limits are set by the community member or designer and define the acceptable range for the output. A process can be in control but not capable if its natural variation exceeds the specification limits.
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