Gaining The Manufacturing 4.0 Advantage With Data-Driven In-Process Testing
Manufacturing is changing thanks to the increasingly sophisticated and intelligent use of data to make a production line smarter and more efficient. For off-highway and specialty vehicle manufacturers, the 4.0 revolution offers great opportunity to achieve significant cost reductions and grow revenue. In this article, Sciemetric's Product Manager, Dave Mannila, discusses the benefits of data-driven in-process testing.
Ottawa’s Sciemetric Instruments acquired by Ohio-based TASI Group
The Ottawa Business Journal discusses Sciemetric’s acquisition by Ohio-based TASI Group with CEO Nathan Sheaff and how this is expected to accelerate Sciemetric’s growth.
You need to go deeper than MES
Mathew Daniel, Sciemetric’s VP of Operations, is featured in Manufacturing Technology Insights Magazine where he discusses how manufacturers must go deeper than conventional manufacturing execution systems (MES) to achieve the quality and efficiency benchmarks demanded by Industry 4.0. This is about taking data collection and analysis to a new level with what Frost and Sullivan calls Manufacturing Performance and Quality Management (MP&QM).
How not to fear the Gage R of your leak test
In this feature with Quality Magazine, Rob Plumridge, Sciemetric leak application engineer, discusses how to tackle the first “R” of Gage R&R for leak testing – repeatability. By focusing on repeatability first (before the other “R” – reproducibility), manufacturers can be certain they have addressed all the controllable variables that can impact the leak test, regardless of the equipment.
Data management principles for machine vision
Mathew Daniel, Sciemetric’s VP of Operations, shares with InTech Magazine how manufacturers can make the most effective use of their machine vision data to achieve higher standards of quality and efficiency and troubleshoot problems faster when warranty claims come through the door.
Bridging the machine vision data gap for Manufacturing 4.0
In this feature published by Imaging and Machine Vision Europe, Mathew Daniel, Sciemetric’s VP of Operations, discusses how vendors of machine vision systems and manufacturers must take a holistic approach to make more effective use of machine vision data as a tool to help raise production quality. He explores the value of integrating vision data into the serialized birth history record for each part in production.
Data holds the key to refining processes
In the pages of Industrial Technology Magazine, Sciemetric CEO Nathan Sheaff highlights five things manufacturers can easily do with their process data right now to take the guesswork out of limit setting, optimize test cycle times, trace the root cause of defects, predict maintenance requirements, and launch machines and lines faster.
What production data is necessary to drive your Industry 4.0 agenda?
What production data is necessary to drive your Industry 4.0 agenda? “Industry 4.0”, “big data” and “data analytics” are not futuristic “hope to achieve some day” concepts. In this feature with Automation.com. Mathew Daniel, Sciemetric’s VP of Operations, discusses how they are redefining the competitive landscape of global manufacturing today, and the kind of digital architecture manufacturers must adopt to collect, manage and analyze their data to achieve the actionable insight they need.
Waveform versus scalar data
Sciemetric product launch manager Robert Ouellette shares with Manufacturing Automation Magazine how digital process signature analysis takes take quality control on the production line to a new level. While SPC and scalar data continue to serve a useful role to monitor and track the health of a production line, it is signature analysis that offers the most effective means to quickly find and address root cause when problems arise.
3675 Turnkey Leak Test Station
The editors of Design Engineering profile Sciemetric’s Model 3675, a turnkey station to boost the speed and accuracy of leak testing. The 3675 can combine up to three of Sciemetric’s 3520 Series Leak Test units in one stand, controlled by a single sigPOD controller.