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Statistical Process Control (SPC) is all about the data you collect. In SPC, the rules say that if your process varies outside your specifications—creating an exception—then you need to pay attention. Control charts provide operators with a visual representation of trends and abnormal patterns. But what if your operators could stop watching their control charts to try to catch those trends—and instead, your software simply notified them of the exceptions they needed to address?

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Control charts are incredibly useful tools that have been around for decades—and for good reason. They are "action charts" that help an operator answer the critical question, “Should I adjust my process, or should I leave it?" Operators and engineers use these versatile charts to better understand their processes and know when it is time to adjust them.

But as long as appropriate statistical rules are in place and those rules are being monitored by an ever-vigilant computer, do operators really need to see control charts at all times?

Probably not. If operators are alerted to exceptions, then they can stop constantly watching charts—and stay focused on their myriad other responsibilities.

Control Charts and SPC

From the early days of SPC, control charts were designed to be easy to plot on paper. You take your measurements, calculate a mean and standard deviation, and then plot those two statistics as points on charts.

QM 1022 InfinityQS IC Topic 1 Control Chart

As you add data to the charts, patterns emerge, and you can ask questions such as:

  • “Did the plot points in question fall too far away from the expected mean?"
    • If yes, then something definitely happened, and you should take some sort of action on the process.
  • “Did two out of three of the last points fall between two and three standard deviations from the expected mean?"
    • If yes, again, you need to take action.

Modernizing Charts Brings Fresh Challenges

If you are the person responsible for making an adjustment to a machine when something goes bad—when something in the process is out of control—then you need that control chart.

But total reliance on control charts comes with issues—especially as the pace of manufacturing production increases. When you require users to continually read and analyze control charts, you create some important risks:

  • Too much information. Once you can create control charts with software, it’s easy to create too many of them. And for operators, having too many charts is frustrating and a crazy waste of time. What happens if you don’t pick up that trend? You might skip over a control chart that needs attention simply because you’re trying to slog your way through a slew of them.
  • Tampering increases process variation. Say you’ve set an SPC rule that says six data points ascending or descending in a row indicates an issue that requires intervention. When you start your shift, you spot five ascending dots in a row. You want to fix it. But that’s tampering with the process. And it can make an issue worse instead of better.
  • Creating a burden for operators. As an operator, is it your job to be an SPC chart interpretation expert? Or is your job running the equipment and making product?

No one is suggesting you abandon control charts; we don’t want to lose the benefits of that time-honored tool. Instead, we’re saying, "You don't need to worry about control charts…until you need to worry about them."

InfinityQS can offer you a different way to get the information you need.

Elevating Quality Control and Empowering Operators

Imagine you’re creating control charts by hand. And you’ve been tasked with making 100 of them.

  • Now, imagine you’ve got a new “helper" who says they will tell you each time one of those charts has a violation.
  • AND they’ll divide those 100 control charts into two piles: one for charts with violations and one for charts without violations.
  • AND the violations pile is sorted so the charts with most violations are at the top of the stack.
  • AND they will instantly reshuffle and reorganize all the charts based on whatever criteria you specify.

Would you welcome that kind of help?

InfinityQS software does just that. It converts raw data into actionable information. Using our software, you can review any quality data and uncover information about every step in your manufacturing operations.

Our Enact® quality platform can help you in many ways:

  • Alert you when a statistical rule is violated
  • Link directly to the control chart you need so you can quickly determine what action to take
  • Prioritize your control charts so you can give attention first to those with violations
  • Find the right control chart to help you analyze specific violations
  • Enable you to proactively look for improvement opportunities—instead of simply waiting for statistical violations

And all of that information is accessible anytime. For example, an intuitive Stream Summary dashboard tile gives you all the power of control chart analysis—without forcing you to constantly sift through chart after chart.

QM 1022 InfinityQS IC Topic 1 Stream Summary Filtered Updated

Charting a Course

Charts aren’t the only way to see the stories that are hidden in your quality and process data. Because Enact is in the cloud, we have access to all the data that’s feeding those control charts. And we can use some highly intuitive tools to create visual summaries of that information.

Process Event Pareto charts summarize events to allow users to see where problems are happening and “slice and dice" the data by site, feature, part, shift, and more. Now, you can quickly see answers to questions like, “Which production line is having the most specification limit violations for net weight?"

QM 1022 InfinityQS IC Topic 1 Pareto

Box-and-Whisker plots enables direct data comparisons that a control chart just can’t. Trying to line up and compare many control charts at once is not feasible; but Box-and-Whisker plots are designed to do this kind of analysis.

QM 1022 InfinityQS IC Topic 1 Box and Whisker

Stream Grading is a unique way to easily look at process performance. You can easily zoom from a site level view to an individual data stream view—and quickly understand where process improvements can have the most impact on product yield. Control charts are great for immediate decisions; and in Enact, that same data is valuable for making decisions that affect the greater organization.


None of these visualizations is designed to replace a control chart. But by using the right tool for the right circumstance, you can gain even more insight into your operations. You can now look beyond the individual data streams that you see on a control chart and start looking at the bigger patterns and trends of your manufacturing processes.

Take a Step Back from Control Charts

Manufacturing organizations cling to control charts because they tell a story about your process: where you’ve been, where things are trending, where things might be going.

While we have embraced the technology that automatically generates control charts, we have also latched on to the habit of constantly looking at control charts. That made sense when software was installed on local computers and used a file-based system that wasn’t shared across the site.

But what about now? Modern, cloud-based quality management solutions allow us to share control charts not just across a local site but across all our sites. Should I be printing out control charts anymore? Do I really need to look at that monitor?

Consider the question from this perspective: There was a time when printing emails was convenient, but now that I can look at my email on my computer, tablet, and smartphone, do I need to print it out? It’s much easier to look at my email whenever I like, wherever I am. The same is true for your control charts.

The quality and process data your operators collect every day is your best source of information about your most important operational metrics. Discover how to simplify and streamline the way you capture that information—and make it actionable in real time—with Enact by InfinityQS, an Advantive company.