Which type of chart has an upper and lower control limit and is used to ensure quality?

A control chart is a statistical tool used to monitor process variation. A control chart is a graphical representation of data over time. It is used to detect and correct deviations from the desired condition.

What Is a Control Chart?

The Control Chart is one of the Seven Basic Quality Tools. 

A control chart is a graphic display of data that shows how well a process or system performs over time. The control chart displays the performance of a process in terms of its ability to meet specifications.

Control charts help determine if a process is working correctly, identify trends, and take necessary corrective action before it is too late.

What is a Control Chart Used for?

 Control Charts can be used to:

• Determine whether a process is operating within acceptable limits

• You can use control charts to spot unusual patterns in the process

• You can use them to determine whether there is any trend in the data

What Are the Ten Good Features of a Control Chart?

The following ten features make a Control Chart an excellent visualization tool.

1. Visualization

Control Chart is a great way to visualize the process over a period of time. That makes it easy to spot trends and anomalies.

2. Trend Identification

You can see where the process has been trending over time. If the trend line goes up or down, this indicates that something may need to change.

3. Statistical Significance

When a control chart is plotted, you focus on the outliers (the points that fall outside the upper and lower control limits). There is a 99.73% probability that the point will fall within control limits if the process is in control. The likelihood of a point falling outside the control limits is rare (0.27% probability) and needs to be investigated, and appropriate corrective action should be initiated.

4. Process Improvement

When using a control chart to improve a process, you want to look at the upper and lower control limit values. If the upper control limit (UCL) is higher than the upper specification limit (USL), or the lower control limit (LCL) is less than the lower specification limit (LSL), then the process needs improvement.

It shows that the process is not capable of meeting the specification limits.

5. Outliers

If any point is outside the control limits, it indicates that the process should be investigated. These could be due to equipment failure, operator error, or other causes.

Types of Control charts

Depending on the type of data (continuous vs Discrete) and the sub-group size, we have different control charts.

Continuous Data

For continuous data, you could use Xbar-R, Xbar-s or an I-MR type of Control Chart depending upon the subgroup size.

Discrete Data

For discrete data, depending upon whether the data is related to the count of defects or the count of defectives, and also whether the subgroup size is constant or varying, you could use c Chart, u Chart, np Chart or p Chart.

The below diagram shows the appropriate control chart for various scenarios.

Tools for creating a Control Chart

Various tools can be used to create a histogram.

1. Manual: Using a pen and paper: This is how Control Charts were used historically. However, with the availability of computer power, you would hardly see this approach being used.

2. Microsoft Excel: This is one of the common tools used to create a control Chart. However, it has its limitations.

3. Minitab: Minitab is advanced statistical software Six Sigma professionals use. You can draw a control chart using Minitab.

4. Other Commercially Available Tools: Various tools available can help in data collection and process control. For example, Trendable by Argolytics.

Conclusion

Control Charts are a powerful tool for monitoring processes. They provide valuable insights into the performance of a process. As such, they are widely used across industries.

Control charts are a key part of the management reporting process that have long been used in manufacturing, stock trading algorithms, and process improvement methodologies like Six Sigma and Total Quality Management (TQM). The purpose of a control chart is to set upper and lower bounds of acceptable performance given normal variation. In other words, they provide a great way to monitor any sort of process you have in place so you can learn how to improve your poor performance and continue with your successes.

The control chart serves to “sound the alarm” when a process shifts (for instance, a machine suddenly breaking on a factory floor) or if someone has a breakthrough that needs to be documented and standardized across the larger organization. Simply put (without taking anomalies into consideration), you'll know something needs to be fixed if you're below your lower control limit or above your upper control limit. See the control chart example below:

Control Charts At Work In 2 Industries

In industrial settings, control charts are designed for speed: The faster the control charts respond following a process shift, the faster the engineers can identify the broken machine and return the system back to producing high-quality products. At a factory, a lag in testing could mean that thousands of parts are produced incorrectly before anyone notices the machine is broken, which results in wasted time and materials, as well as angry customers.

In nonprofit organizations, a control chart could be used to determine when an online donation system has broken down. If the website goes offline, halting critical donations, the leadership team can quickly alert IT and ensure the page gets back up and running quickly. Alternatively, seeing a major jump in donations likely means something good is happening—be it world events or a successful marketing campaign. Either way, leadership should know as soon as possible when donation activity changes.

Keep emotion (and error) out of your measure evaluations with these step-by-step instructions.

Control Chart Examples: How To Make Them Work In Your Organization

• Budget: You can use your control charts to examine your percentage of spend each month. If you spend over 15% of your budget in one particular spring month, that is extremely helpful to know right away so you can cut back over the rest of the year. Or, if you spend less than 8% of your budget for a couple months in a row, you'll know you may have a little wiggle room in the months to come.

• Retention rate: Some organizations feel like they need a little turnover to keep the organization healthy. If you're retaining your talent at a rate above your normal control limit, you'll know that you may not be evaluating staff very selectively. You'll want to be sure to identify the reasons you may be retaining so many employees to see if this is positive news or if an HR process is broken. But if your retention rate is increasing or it drops below your lower control limit, you'll be able to determine how to move that trend the other direction and dedicate more resources to recruiting for a period of time.

• Employee or citizen surveys: At ClearPoint, we do quarterly customer support feedback surveys to see how our clients feel we’re doing. If we're doing something that is having a positive effect, we want to know what it is and continue to do it well. But if we're falling below our normal control limit, we'll want to note that something needs to change. This could be anything from having better customer service response time to changing a particular feature in our software that is frustrating or difficult to use.

"Can I Create A Control Chart In Excel?”

Because of Excel’s computing power, you can create an  Excel control chart—but in order to do so, you need to know how the upper and lower limits are calculated. There are different statistical analysis tools you can use, which you can read more about here.

Control Charts & The Balanced Scorecard: 5 Rules

Control charts can be used as part of the Balanced Scorecard approach to account for an acceptable range or variation of performance. If you choose to do this, there are five key quality control rules to keep in mind when considering using control charts at your organization:

1. Give it time and update your limits accordingly. You can't expect to see immediate results or instant insights from a new control chart (that is measuring something new to your organization). It takes a number of months—or even years—to understand natural variation and baseline “normal” performance.Don't be afraid to adjust if necessary, and don't rest on your laurels if something you've been tracking has been steadily improving over time. These are good indications that your upper and lower limits may need to be updated.

1. Watch for "big movers."  There is going to be a certain amount of variation as part of normal operations, and small variation is nothing to worry about. Instead, focus your attention on major jumps or falls. These are the places where your organization needs to concentrate its efforts.

1. Results matter and should be visible. Process improvement initiatives should cause a particular metric to rise above the upper control limit, demonstrating that there was a statistically significant shift in the objective’s measure. Control charts give you a clear way to see results and act on them in the appropriate way. Over time, you may need to adjust your control limits due to improved processes.

1. Don’t get bogged down. Take a moment to remember that control charts can be complicated. (They were, after all, developed by engineers!) But your organization can keep your control charts as simple as you need. Extremely complex math is still being developed in the operations research field to better understand process variation and how to account for it via control charts, but the typical leader at an organization does not need to worry about going into that level of detail. Instead, try to identify the acceptable upper and lower limits for each key metric that you want to track, and keep the overall theory of limits in mind when reviewing your control charts.

1. Update your limits according to new data. Remember that controls charts are based on historical data—so as time progresses and new data is collected, these limits need to change. Don't be afraid to adjust if necessary, and don't rest on your laurels if something you've been tracking has been steadily improving over time. These are good indications that your upper and lower limits may need to be updated.

1. Set your RAG evaluations as ranges. On your control bars, within 5% of your target is green. Outside of 5% but within 10% is yellow, and outside of 10% is red. You can adjust the percentages, but the RAG status help show that you are getting more out of control.

In Conclusion

The key with control charts is to recognize when anything is happening outside the norm. Be it good or bad, you will want to develop an action plan for how to respond when the latest measure lands outside the acceptable limits. 

What are the upper and lower control limits in trend analysis?

What is p

What is p

What is upper control limit in control chart?