Many manufacturers face the costly problem of a lagging leak test cycle time. With constant pressures on production, line managers have no choice but to run parallel test stations to maintain production quotas. More often than not, the answer is simple—use your leak test data. Here’s how one customer did it.
Machine vision images and data are a valuable part of the Manufacturing 4.0 equation. The problem is that machine vision images and data are often trapped in silos across the plant floor, with images stored in formats that make them difficult to access and analyze. With the right data management strategy, you can make this data accessible to your team so it can drive value.
Learn about the successes we’ve helped our customers achieve—and how we can help you achieve the same success on your production lines!
We talk about how Sciemetric’s new partnership with Cincinnati Test Systems (CTS) gives manufacturers worldwide access to the combined products and expertise of three world-leading masters of leak and other in-process test solutions.
Machine vision images and related data can be used for much more than basic pass/fail determination during the process cycle. We get into how this data can be collected, correlated and analyzed will all other production data as part of a comprehensive IIoT strategy.
So, your plant collects data—but how are you using that data to take quick, decisive action on the plant floor and inform timely decision-making in the corner office? We dive into five ways smart manufacturers are using their data to raise the bar on quality and competitiveness.
When a product comes back with a warranty claim, the next step is to determine root cause. Robert Ouellette discusses how digital process signature analysis is the key to trace root cause, address the problem fast, contain the scope of a recall and ensure it never happens again.
Out of all the testing stations on a production line, leak testing is the station most prone to causing bottlenecks. CEO Nathan Sheaff summarizes how manufacturers can take advantage of digital technology and advanced data analytics for more efficient, productive operations.
We recap our five blog posts that captured the most attention in 2017, from getting your leak test right and containing warranty costs with data to how the repair bay can contribute to a more effective defect data management strategy.
Aaron Alberts explores how, when it comes to collecting process data to raise the bar on quality and productivity, you can never have too much. The key is to break down the data silos across the plant floor and get all that data into one centralized database for analysis.