As a modern manufacturer, you care about quality. But can you prove it to regulators, investors, and—most important—customers? What does your quality assurance scheme achieve? What does it tell you? And is that information what you really need to know?
For many manufacturers, quality management takes the form of pass/fail checks that typically occur between operational stages in the process. Although a simple pass/fail might be sufficient to catch product that is simply not up to snuff, this type of test lacks the level of insight that can make the difference between getting by and making genuine improvements to your product quality and customer satisfaction.
Even the simplest quality assurance schemes will cover input checks and process automation for most steady-state processes. You’ll be adjusting the parameters of some processes based on measurements. Then, between each stage in the process, you’ll be doing simple pass/fail checks.
These checks are vital and tell you whether the process is going wrong—and, if so, allow you to dump that production run before it disappoints your hard-won customers.
However—and this is crucial—pass/fail checks don’t tell you how right things are going; how to not just fix but also prevent issues; where and how you can apply best practices across all your operations; and how to envision opportunities for product and process improvements.
Managing the amount of data required for this type of analysis on paper or spreadsheets is nearly impossible. Fortunately, if you’re looking for a better option for making the most of your quality data, modern quality intelligence software, driven by statistical process control (SPC), can help.
Let’s take a look at four ways in which quality intelligence software can help you get a fresh look at the information that can move the needle for your organization.
#1: Learn to Anticipate
Many businesses that use data for continuous improvement, Lean, or Six Sigma efforts look for out-of-spec variations that indicate unacceptable quality—similar to the knowledge you gain from a pass/fail check. But the information found within spec limits can transform your business.
With a quality intelligence solution, you can turn test measurements into a histogram distribution of those data at each stage.
This type of visualization can tell you how frequent each value is and where the majority of values lie. Now, you can spot outliers that indicate emerging issues (e.g., machine malfunction, shift differences). By catching these issues early, you can reduce costly waste, overfill, and defective product.
#2: Continuously Improve
When you collect the level of detail that enables detailed variation analysis, you can start to look at process capability at each check and each stage. A visual display allows you to answer what should be a key question for any manufacturer: “How capable is my production process of producing the right result?”
You can measure capability separately for each stage; you can even assign a numeric score to capability. In essence, it’s a score of how easily your histogram fits within your specification limits. Comparing scores enables you to quickly prioritize areas that need attention or that could provide quick and valuable quality wins.
Through this process, you can pinpoint and prioritize improvements that will make your operations more efficient and your product more consistently excellent.
#3: Build on Success
Can you look at statistically significant trends within your data? Not with pass/fail checks. But more granular analyses can highlight emerging problems so that you can intervene early. For example, if one of your metrics is within acceptable limits but steadily rising over time, it might be time to check the ingredients, materials, or parts you are buying; perform equipment maintenance; or spot-check your process.
Likewise, you can run these sorts of analyses to identify successes. Which shift, batch, or process is running right on the money? What is happening there that’s different from less-outstanding areas? And can you replicate that success across other areas of your operations? This type of evaluation can lead to enterprise-wide improvements and better implementation of best practices—important steps when your business is booming.
#4: Think Strategically
Finally, a more robust quality intelligence solution supports comparison of quality parameters between different lines or plants. Is there a problem with process capability for line A while it’s fine for line B? If so—why?
Here, again, your quality data can lead you in the right direction for important product improvements, saving valuable time and resources.
A Better Option
Pass/fail checks have their place. But pass/fail data don’t show you how close to the limit you are. They don’t show trends. Those limited data don’t indicate opportunities for improvements in output, procedures—and profits. They don’t show you how likely you are to be able to manufacture a consistent quality product again in the future.
You gain these benefits only by recording actual values over multiple runs, over time—and then really analyzing those data. Once you start doing this, you can gain some key insights.
For nearly 30 years, InfinityQS has been a leader in providing quality management solutions to manufacturers. To see how our solutions can help your continuous process improvement efforts, please contact us for a personalized demo.