In hybrid and discrete manufacturing processes, pneumatics control the dynamic movements on the machines used in the process. Internet of Things (IoT) devices can help these machines operate more safely, reliably and efficiently.
In a MachineDesign article, IoT for Pneumatic Systems, Emerson’s Enrico De Carolis describes how these devices, such as a pneumatic valve manifold, gather and perform analytics on this data to develop actionable information to improve overall performance.
Enrico opens by explaining that improved performance happens when you:
…seamlessly gather data, analyze it on the fly and turn that information into actionable results that increase uptime, efficiency and productivity.
Some of the applications in hybrid and discrete manufacturing include:
Medical device assembly, automotive production, food processing and numerous packaging applications…
Enrico shares an example:
Imagine a smart pneumatic device, for example, that could report a clogged or dirty filter before it gets bad enough to slow or halt a packaging process. The goal is to make the shift from a merely diagnostic capability and mentality to one that is truly prognostic and forward-looking.
IoT devices gathering data right at the source:
…can be used to drive improvements in machine reliability in terms of availability (maximum run time), performance (ideal cycle time), and quality (good part count with minimal scrap).
Given the sheer amounts of data these devices can collect:
…edge and cloud-based computing strategies need infrastructure capable of handling the new realities of big data, and these systems are still taking shape.
With different ways to move this information to PLCs and control systems, embedding intelligence at the device level helps improve interoperability.
For example, consider a pneumatic fieldbus valve manifold such as the ASCO Numatics G3 platform, which extends intelligence to perform a variety of IIoT data analytics locally—at the device level.
This data can be collected independent of the communications architecture above and does not require changes at the control system level to do the prognostic and diagnostic analysis.
Read the article for Enrico’s guidance on how device-level analytics simplify control system logic and ongoing maintenance, and examples of where Industrial Internet of Things devices can be applied such as valve cylinder monitoring and pressure variance monitoring.
Visit the Numatics G3 Fieldbus Electronics page for more on these device-level analytics. You can also connect and interact in the Fluid Control & Pneumatics group in the Emerson Exchange 365 community.