A process control chart, also known as a Shewhart chart or process-behavior chart, is one of the tools used in quality control management. Process control charts allow you to see any abnormalities in a given process over a specified time period.
This type of chart is widely used in manufacturing wherein there are many automation jobs. For example, control charts can be used to evaluate if the different automated ice cream cone making systems are performing as they should. The chart allows the engineers of a manufacturing facility to evaluate the current process automation. Based on the results, a plan is put into place to address any undesired variations or issues.
There are different types of control charts including p- control charts, u- control charts, fuzzy control charts and regression control charts. Collected data is plotted versus time. Every process control chart has the following:
- Points - data sample at different times
- Central line - average or mean
- Lower line - lower control or threshold limit
- Upper line - upper control or threshold limit
These lines will determine if there are suspicious variations in your data from a historical point of view. You will know whether the process is either in control (consistent) or out of control (unpredictable). If the points are all within the upper and lower control limits, then the process is going on smoothly. However, if there are points above and below the limits, this means there is a variation in the process. These variations are called special-cause variations. Something is different or has changed, and this warrants immediate investigation. Any deviations or variations, especially when looking at process automation, may mean increase in quality costs.
To prepare a process control chart:
1. Identify the process that needs to be evaluated.
2. Identify the sampling method. Random sampling method should be employed to get a good range of data.
- Determine how many samples need to be obtained.
- Determine the frequency of sampling (days, week, months, etc.)
3. Collect the data. Make sure accurate and timely data collection is performed.
4. Plot the data on the graph. Create the horizontal or x-axis, which is usually the time element. Decide on the scale for the vertical or y-axis, which will depend on the measurement of the type of data you are plotting.
5. Calculate the upper, average and lower control limits.
6. Interpret the graph. Look for any significant points falling into the outer limits. If one or more points are found in the outer limits, the process is deemed out of control. This would mean that you need to find out what caused this situation and correct the problem.
Process control itself is used in various applications. A process control block, for example, can be found in the computer's operating system. Most of the processes nowadays are highly automated. Control mechanisms employ the use of a PID control algorithm to make their manufacturing processes run smoothly. Ladder logic is one of the programming languages used to develop software for industrial process automation.
A process control chart is a useful tool in determining whether there are breakdowns in a process. It can be applied not only to an automated manufacturing system but to human processes as well. Knowing any unwanted deviations in processes allows the company to act on the problem so as not to incur further costs whether monetary in nature or otherwise.