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Many manufacturers continue to focus on data collection rather than data utilization. They don't yet have the modern data analytics tools in place that will allow them to squeeze from their part data the actionable insight that is crucial to meeting Industry 4.0 benchmarks they are seeking for quality, yield and traceability. Learn why digital process signatures are your first step to meet Industry 4.0 objectives.

Ron Pawulski cites a Sciemetric use case to explore how digital process signature analysis can save medical device makers from the cumbersome and costly process of end-of-line destructive testing for quality assurance.

Many manufacturers are tempted to create their own process monitoring solutions in an attempt to avoid spending their budget on an out-of-the-box vendor solution. However, these DIY solutions almost always end up spending manufacturers more money in the long run. Here's why.

End-of-line tests remain popular with many manufacturers—however due to their high level of complexity, these tests can result in false passes that can cause serious problems in the field. Read this blog post to learn why relying on end-of-line is bad for your bottom line.

The fix for a quality assurance system that just isn’t making the grade doesn't necessarily require a costly rip-and-replace. Sciemetric explores how an existing system can instead be retrofitted to gain some smarts with tools for digital process signature analysis.

There is a tendency to think about the line in terms of individual process, with separate solutions for force-distance monitoring, leak testing, torque testing, etc., rather than as a whole—but it doesn't have to be this way. With one common solution, like the sigPOD, one platform can do it all. Learn how commonality on the production line helps manufacturers save time and money.

Finding the right limits for your in-process tests is crucial to achieve the highest production yields and minimize the risks of defective parts slipping through. We explore how waveforms, or digital process signatures, can be used to achieve this, quickly and reliably.

A chief goal when it comes to optimizing any leak test is to ensure if the cycle time of the test can keep up with the pace of production. One factor in optimizing the test so that it can cycle as many parts as quickly as possible with an acceptable range of repeatability and reliability is test pressure. Consider the following factors when identifying proper test pressure for your leak test. 

The information generated by machine vision systems puts a whole new spin on the term “big data.” The raw image files output from vision systems are huge, and manufacturers can generate terabytes of image data in a month—even in a week! So, what do you do with all this data? Read more to find out!

Performing a leak test on big parts poses big challenges. But, as is the case with any leak test scenario, if you know and control your variables, you can control the test. Here are 4 tips to help you achieve a reliable and repeatable leak test.