Articles tagged Statistical Process Control (SPC)

Control charts help us monitor and stabilize a process. A little graphics along with statistics provides a tool to identify when something has changed. Some changes are abrupt and obvious, other a little more subtle, yet the out of control signals each have approximately the same chance of alerting us to a change.

A little graphics along with statistics provides a tool to identify when something has changed. Some changes are abrupt and obvious, other a little more subtle, yet the out of control signals each have approximately the same chance of alerting us to a change. [Read more…]

Dr. Nelson created a simple experiment to illustrate the effect of meddling with a stable process. (Dr. Deming did something similar)

While the intent of making small changes to a process may be to make improvements, these perturbations generally increase the variation of the results.

To improve a process requires understanding the source of the variation and often controlled experiments to identify process improvements. [Read more…]

Another variation of the X-bar and R chart, in this case measuring and plotting individual readings instead of a sample average. The range value is obtained from the current reading and a fixed number of previous readings.

This type of control chart is suitable for calibration or testing situations where it is not practical to create subgroups of items for samples. [Read more…]

The s chart replaces the R chart and provides an increase in sensitivity to variation of the spread of the data.

The s-chart works better with 10 or more items per sample in order to obtain the s (standard deviation) estimate. The use of a spreadsheet or calculator expedites the calculation of the sample standard deviation.

[Read more…]

Control charts provide an ongoing statistical test to determine if the recent set of readings represents convincing evidence that a process has changed or not from an established stable average.

The test also checks the sample to sample variation to determine if the variation is within the established stable range. A stable process is predictable and a control chart provides the evidence that a process is stable or not.

Some control charts use a sample of items for each measurement. The sample average values tend to be normally distributed allowing straightforward construction and interpretation of the control charts. The center line of a chart is the process average. The control limits are generally set at plus or minus three standard deviations (of the sample means – commonly called the sampling error of the mean) from the grand average.

[Read more…]

Every process should operate stably. Every process may have many measurements available to monitor either various aspects to the final product or the assembly equipment. There may be hundreds of possible items to measure and monitor.

We do not have the resources nor time to apply control chart principles to each possible measurement. Control charts do not directly add value and they have a cost to maintain and interpret. While it may be tempting to add a dozen or so control charts, as the cost increases the value quickly decreases.

[Read more…]

As stated before, variation happens.

The root cause of the variation for a stable process includes material, environmental, equipment, and so on, changes that occur during the process. No saw cuts the same length of material twice – look close enough there is some difference. [Read more…]

An easy method to monitor and control a process average. It is an alternative to the Shewhart control chart.

Pre-control charts work well with stable and slow process drifts or changes. These charts provide a means to monitor a process and act as a guide for process centering.

They are easier to setup, implement, and interpret the Shewhart charts. [Read more…]

For a stable process, nothing much happens. If the stable process is producing acceptable products, we should expect to continue to produce acceptable products.

Unless something changes. [Read more…]

Once you decide to monitor a process and after you determine using an $- \bar{X} -$ & s chart is appropriate, you have to construct the charts.

The $- \bar{X} -$ & R charts use the range as an approximation of the variation in the population. When feasible use the standard deviation, s, rather than the range, R for the improved efficiency in detecting meaningful changes in process variation. [Read more…]