In the manufacturing world, quality data drive operations. They enable us to measure everything from process capability to actual process performance. Data help us optimize production speed while improving quality. And data make it possible to tune our processes to precise specifications.
If collecting quality data is a good thing, then collecting a lot of data must be even better, right? Well, like anything involving human endeavors, it’s easy to overdo it when you try too hard.
Getting Overwhelmed by Quality Data
The next time it rains, take a few seconds and try to focus on a single drop. It’s nearly impossible. And if you were to see a single drop and track it as it hits an object, it would be hidden by other drops within a few seconds and you would lose focus on it.
That overwhelm can happen in our quality management efforts, too. For example, consider the control charts we use every day. Their purpose is to enable study of our manufacturing processes over time. They provide a visual representation of a process so you can quickly and easily spot trends and variances—and take action to correct the process when you need to.
Implementing statistical process control (SPC) and collecting data too frequently can create a deluge of data points that renders the resulting control chart unusable. And then you’ve defeated your purpose for collecting the data in the first place.
Data Collection Overload
Collecting data too frequently is one of the main mistakes we make when implementing SPC control charts. The following chart was created from data collected at the rate of one sample per minute. Note how tight the process behavior limits are. With this level of sensitivity, most of the samples are registering as out of control.
*Click on the image for a larger version
There are many reasons that collecting data too frequently will cause problems. One key issue is that it creates process behavior limits that are too sensitive and generate false alarms. When we have false alarms at this rate, we’re telling the operator that the system doesn’t really work and therefore alarms don’t matter. This can’t happen. Operators need to trust the process and trust the control charts.
By adjusting the sampling frequency to once per hour we can see a true representation of the process’s behavior.
*Click on the image for a larger version
Ensuring that the sampling frequency is correct presents process behavior limits that give the user true signals and allow for true process control and improvement. This makes all the difference in the world to an operator. This is a process that the operator can trust. This is a system that the operator can trust.
Ensuring Sampling Frequency Is Correct
Sampling frequency is based on how fast the process is changing. Samples must be taken often enough to catch any expected changes but far enough apart to display the variation.
The key to setting a rational sampling frequency is to understand the process. Every process has normal variation, and understanding this behavior enables us to more accurately sample the process.
Here are a few tips to help you set an effective sampling frequency:
- Conduct a process study to understand normal patterns of the process.
- Collect data as frequently as possible during the process study to ensure the common behavior of the process is understood. Don’t worry yet; frequent data is preferred for a process study, since the data will not be used for a control chart.
- Evaluate the process study data trend to determine the amount of time or number of products produced between process shifts.
- Set an SPC sampling frequency to collect two subgroups between the process shifts—for example, a process that shifts every three hours should be sampled every hour.
Next time you are tasked with creating a sampling strategy, take a moment to think about ultimate goal, and ensure you’re sampling the process flow at a rational rate!
Take advantage of the technology at your fingertips today. Contact an InfinityQS account manager by calling 1.800.772.7978 or through our website.