How can you use statistical process control to detect drift?

1 What is drift and why does it matter?

Drift is a type of process variation that occurs when the process output shifts away from the target or specification over time. Drift can be caused by various factors, such as wear and tear of equipment, changes in raw materials, environmental conditions, operator skills, or measurement errors. Drift can affect the quality and consistency of the product or service, and increase the risk of nonconformity or failure. Therefore, it is important to identify and eliminate drift as soon as possible to maintain process stability and customer satisfaction.

2 How to measure drift using control charts?

Control charts are one of the most common and effective tools for SPC. They are graphical displays of the process performance over time, with upper and lower control limits that indicate the expected range of variation. Control charts can help you detect drift by showing if the process output is within or outside the control limits, or if there is a pattern or trend in the data. For example, if the process output is consistently above or below the center line, or if there is a steady increase or decrease in the data points, it may indicate that the process is drifting.

3 How to analyze drift using control charts?

Once you have plotted the process data on a control chart, you can use some simple rules to analyze the drift and determine its significance and cause. For example, if one point falls outside the control limits, this indicates a special cause of variation that is not inherent to the process and requires immediate investigation and correction. Additionally, if two out of three consecutive points are near the control limits, this could indicate a potential shift in the process mean, and further analysis and action are needed. Similarly, if seven consecutive points are on one side of the center line or six or more consecutive points are increasing or decreasing, this indicates a trend in the process output that requires identification and elimination of the source of drift.

4 How to correct drift using control charts?

After you have identified and analyzed the drift using control charts, you need to take appropriate actions to correct it and restore the process stability. Isolating and removing any special causes of variation that caused an outlier, ensuring the accuracy and consistency of data collection and recording, inspecting and maintaining equipment, standardizing process procedures, training and supervising operators, modifying and optimizing process parameters, and updating control limits and the center line are all possible actions. Doing so will help you achieve the desired output.

5 How to prevent drift using control charts?

To prevent drift, it's important to use control charts as part of a continuous improvement cycle, where the process is monitored, measured, analyzed, and improved on a regular basis. To do this, you must establish and document the process objectives, specifications, and requirements and communicate them clearly to stakeholders. Select and use the appropriate type and size of control chart for the process based on the type and frequency of data, as well as the process characteristics and capabilities. Collect and plot the process data on the control chart at regular intervals to check for any signs of drift or other types of variation. Analyze and interpret the control chart data using rules and methods to identify sources and causes of drift or variation. Implement and evaluate corrective and preventive actions to monitor their effectiveness on process performance and quality. Finally, review and update the control chart data and limits, document, and share results from SPC activities. SPC is a powerful technique for detecting and correcting drift in any process. It can help reduce defects, waste, costs, and risks while increasing efficiency, productivity, and profitability.