Why should you as a machine builder/integrator care about incorporating data collection and analysis capability into your production process? Sciemetric's Senior VP and Account Manager, Aaron Alberts explore this topic in this article for Machine Design.
The idea of big data and Industry 4.0 can overwhelm manufacturers—but it doesn't have to. The first step towards Industry 4.0 doesn't have to be a giant leap. At it's core, it's just about using your data in a productive way. Jeff McBee, Regional Sales Manager at Cincinnati Test Systems, offers 7 questions to self-diagnose your need for data-driven analytics in the latest issue of Manufacturing AUTOMATION.
We often talk about “silos” in manufacturing, referring to process and test data trapped on the production line that could otherwise be used to drive improvements in quality and yield. But as we all grapple with this thing called Industry 4.0, the silos that often cause the most problems are the ones that exist between people, not machines. Read this article by Jeff McBee, Regional Sales Manager at Cincinnati Test Systems, to help identify who best to appoint as champion of digital transformation initiatives in your plant and which questions you should be asking yourselves as you devise your approach to Industry 4.0.
A key principle of any digital journey for a manufacturer, whether or not they are in the automotive supply chain, comes down to making effective use of production data. Learn how to ready your production line for Industry 4.0 with data-driven insights in this article, contributed by Sciemetric's Manufacturing IT Manager, Patrick Chabot.
The ASSEMBLY Show 2018 announces the inaugural Product of the Year winner, QualityWorX DataHub from Cincinnati Test Systems and Sciemetric. The DataHub is a simple, cost-effective tool for analyzing leak test data and performing test-to-test comparisons. The product aggregates data from multiple leak test instruments into an analytics database for real-time usage. Learn more in this article.
Sciemetric's Manufacturing IT Manager, Patrick Chabot shares insights on how manufacturers can make better use of their machine vision data in this article by IMV (Imaging and Machine Vision) Europe.
Cross-process analysis of images, image data and other process data improves quality, process control, and enables continuous process improvements. Learn more in this article in Vision Systems Design, by Sciemetric's Manufacturing IT Manager, Patrick Chabot.
Cincinnati Test Systems and Sciemetric have brought the data management and analytics of Manufacturing 4.0 to leak and flow testing with their first collaboration as part of the TASI Group. Learn more about the QualityWorX CTS DataHub.
There are some instances where an acceptable leak rate is so small as to be practically zero. Few air leak test methods, such as pressure decay, have the necessary detection range. These situations call for a trace gas-based test method. Learn more in this article in Quality Magazine, written by Cincinnati Test Systems' Systems Engineer, Peter Bonyhati.
Even on a modern manufacturing line equipped to collect and analyze process data, something can always slip through the cracks to derail quality and efficiency. This is only to be expected. But what if a key assembly process still rests entirely with a human being manually completing a task? There is no obvious data trail, no process monitoring in real-time. What then? In this article, Sciemetric's Manufacturing IT Manager, Patrick Chabot discusses the importance of having a strategy for continuous improvement on the line.