Process Control Charts Ensure Manufacturing Excellence

Summary

Process control charts are an important application of statistical process control (SPC) that are used in the management of processes in various industries with the aim of maintaining consistency, reducing variation and improving quality of products and services. These charts are particularly important in Six Sigma and manufacturing organizations to achieve process stability and excellence.

Six Sigma is a data-driven approach to defect reduction and process improvement. Control charts are an important part of Six Sigma projects as they give real-time feedback on process capability, help with decision making based on data and thus help in identifying where there is room for improvement. In manufacturing, these charts are useful in achieving product quality, minimizing waste and increasing production yield.
 

What control charts are

Control charts are statistical tools used to study the behavior of a process over time (Figure 1). They are useful in distinguishing between the random or normal process fluctuations, also referred to as common cause variations and special cause variation, which are the atypical events that require correction.

How control charts work

Control charts monitor processes continually and alert staff to conditions that are not typical of the process. They assist in the recognition of trends, shifts or patterns that are indicative of a point of change—be it a good one or a bad one. This approach is preventive in nature and is directed toward avoiding defects before they occur so that the process becomes stable and predictable.

Constructing a control chart involves selecting and understanding the process to be monitored along with its characteristics. Then, data must be collected—include enough data to establish a baseline. Next, calculate statistical parameters by finding the mean, standard deviation and the control limits.

Now, it’s time to plot the data. Present the values in a time series and draw the control limits. Next, analyze trends. Look for patterns, signals and variations that could indicate a change in the process. If there are anomalies, take corrective action. If needed, find the route cause (or causes) and implement the solution(s).

Interpret the control charts by observing the representation of the data and understanding how it relates to the process. If the process is stable, data points remain within control limits without patterns or trends. An out-of-control process has data points outside the control limits, which indicate potential issues. Be aware of non-random patterns: trends, cycles or repeated patterns that could indicate an underlying cause that needs investigation. In addition, look for sudden shifts. A drastic shift in the process mean suggests there may be an external influence or a fundamental change in the system.
 

Control chart pros and cons

Benefits of using control charts include

• Early detection of issues
• Process Stability Improvement
• Enhanced decision-making
• Cost reduction
• Continuous improvement support.

Although control charts are beneficial in many cases, there are some disadvantages associated with using control charts:

• Initial setup complexity
• Misinterpretation risks
• Limited to historical data
• They are not a standalone solution; they should be combined with other quality management tools for optimal results.

Wrapping up

Control charts are useful tools in the control and improvement of process performance in most industries. They are useful in monitoring the stability of the process, which is crucial in any organization desiring to achieve quality, reduce costs and increase production efficiency. As there are some difficulties in the implementation and interpretation of the controls, the advantages clearly outweigh the disadvantages, and the charts are therefore a significant part of the quality management system based on data.

_{This feature originally appeared in the August/September issue of Automation.com Monthly.}