What is Control Chart and its types?
The control chart is an online graph used to study how a process changes over time. The control chart was invented by Walter A. Shewhart.
Guidelines for Control Chart:
A control chart always has a central line for the average, an upper line for the upper control limit and a lower line for the lower control limit. These lines are determined from historical data.
By comparing current data to these lines, you can draw conclusions about whether the process variation is in control or out of control.
When to Use a Control Chart :
- When controlling ongoing processes by finding and correcting problems as they occur.
- When predicting the expected range of outcomes from a process.
- When determining whether a process is stable.
- When analyzing patterns of process variation from special causes or common causes (within the process).
- When determining whether your quality improvement project should aim to prevent specific problems or to make fundamental changes to the process.
Types of Control Charts:
There are two categories in the control chart. One is the variable control chart and the second is the attribute control chart.
Further in the Variable control chart, there are:
- Average and Range chart (X – R)
- Individual and Moving Range Chart ( X – MR / I – MR)
In the Attribute category, there are,
- Number of defectives chart ( p / np chart)
- Number of defects ( c / u chart)
Control Chart Basic Procedure :-
- Choose the appropriate control chart for your data.
- Determine the appropriate time period for collecting and plotting data.
- Collect data, construct your chart and analyze the data.
- Look for “out-of-control signals” on the control chart. When one is identified, mark it on the chart and investigate the cause. Document how you investigated, what you learned, the cause and how it was corrected.
- Continue to plot data as they are generated. As each new data point is plotted, check for new out of control signals.
How to interpret the control chart?
- Any point out of control limit ( Out of Zone A)
- Seven points in a row on one side of center line.
- Six points in a row continuesly increaing or decreasing order.
- Fourteen points in a row alternating up and down.
- Two points out of three points in a row in the same zone A.
- Four points out of five points in arow in the same zone B.
- Fifteen points in a row in zone C above or below center line.
- Eight points in arow on both side of center line but none in zone C.
Guidelines for eliminating Special cause variation:
- Get timely data so that you see the effect of the assignable cause soon after it occurs.
- As soon as you see something indicates that an assignable cause of variation has happened, search for the cause.
- Change tools to compensate for the assignable cause.
Guidelines for reducing Common cause variation:
- Reducing common-cause variation usually requires making fundamental changes in your process
- Addressing the common cause variation will improve the process performance.
Benefits of Control Charts:
- Predict process out of control and out of specification limits.
- Distinguish between specific, identifiable causes of variation.
- Can be used for statistical process control.
- Control charts allow operators to detect manufacturing problems before they occur, this greatly reduces the need for product rework or COPQ.
- Control charts provide as the early warning detection system, to make a changes in the running process.
- After analyzing a control chart, operators need to determine whether to “do something” (adjust in the process) or “do nothing,” (let the process run as is).