Ian
Ian
Ian
Ian
Ian

Wireless meets batch modularity

Jan. 5, 2022

Back in 2014-15, batch operations were being promoted as one of the “killer apps” for wireless sensor networks. But the bandwidth limitations of these IEEE 802.15.4 protocols—as well as the increasing capabilities and adoption of Wi-Fi—have made the latter better suited to use in these and related industries where reconfiguration of the process/equipment occurs periodically.

Batch processes and factory automation rely heavily on skid packages with self contained controllers. NAMUR has documented a more modular approach to manufacturing with their Module Type Packages (MTP) that are used to assemble ever larger processes. These modules can be wirelessly connected from access points on the edge of each package or module to the main control or alternate data collection system.

Jim Montague’s recent article “Modular process automation: more than the sum of parts” (Oct. '21, p. 58) gives a good overview of how MTP will play a role in the increased use of modular concepts across industries, including batch operations, discrete manufacturing and the continued modularization of continuous processes through all phases of their lifecycle from concept to decommissioning.

With a wireless infrastructure in place, temporary wireless sensors such as clamp-on gauges can be easily added to monitor process conditions such as temperatures, pressures and flows that aren't normally instrumented. These wireless “data traps” are well suited to gathering data to determine correlations between process variables and product quality, aid in energy audits, and troubleshoot equipment, such as pump and steam trap performance. These temporary installations are another form of modular connection, albeit temporary ones.

One of the sureties of every industrial facility of the future is an increase in networked machines and devices that will reduce and/or eliminate the need for human execution of many routine, repetitive tasks. Full-time wireless sensors and associated applications for health and diagnostics will also reduce the risks—and errors—associated with human data collection out in the plant. The automated data being collected by intelligent edge devices may also be initially analyzed with the use of artificial intelligence (AI), with the resulting summary being shared over a dedicated, non-control but still operations technology (OT)-based wireless network.

Due to the nature of its processes, batch manufacturing relies on frequent human interaction for tasks as simple as confirming the next step in a batch, changing the recipe, or perhaps triggering the automatic reconfiguration of the equipment itself. Having a secure wireless infrastructure allows operations and maintenance personnel to access meaningful messages and other information wherever they may be located. This not only saves time but also reduces the likelihood of errors creeping into the system. The net result is the ability to deliver products to market faster—simply through manufacturing cycle-time improvements.

As I've stated in previous columns, the wireless network is just one part of the connection infrastructure that enables communications between two devices and among devices and the remainder of the system. NAMUR is also developing guidance documents to expand MTP and its associated parts on condition-based process control, diagnostics and maintenance, user interface, alarm management and technology evaluation, so these critical components can be considered and integrated into a whole.

Wireless has changed the way we work in the office and home environment, so it should be no surprise that is has the potential to do the same in industrial settings. Indeed, wireless has already made inroads through wireless sensor network implementations as well as for data backhaul. Future technologies such as 5G and WiFi-6 will bring additional capabilities suited to the real-time operations environment, such as reduced latency, greater distances (5G), and the ability to handle many more data points.

About the author: Ian Verhappen