Industrial IoT – What You Need to Know to Pilot a Successful Program

I’ve often likened my job to the popular TV show, “How It’s Made”. Each month, I’m involved with dozens of client conversations. While the breadth of industrial applications and industries is wide, the issues these companies face are remarkably similar.

One of the most prevalent is a desire to get accurate and timely information into the hands of more plant people. Even for companies that have been continuously investing to modernize and automate their processes, they rarely have all the data they would like and have trouble justifying the incremental cost to expand legacy systems. For companies that have predominantly older, non-connected equipment, the price-tag to upgrade their infrastructure using traditional data access approaches is simply prohibitive.

In both these situations, the latest “breakthrough technology”, the Industrial Internet of Things (IIoT), is showing significant and rapid return by dramatically reducing the connection cost required to see their plant or enterprise in action. Here’s a look the overall architecture and building blocks in the current generation IoT playbook.

• Sensors & Inputs – At the very edge of the solution architecture are the sensors and inputs required to convert real world measurements into digital information.  There are two schools of thought in this area.   The first involves embedding sensors with a communication layer that can relay digital signal data to a device communication engine. The other approach is to use existing sensors and tie their native analog signals, including current or DC voltage, back to a gateway device that transforms it to a digital value and then relays to the communication engine.  There are a growing list of players addressing this space, but from personal experience, solutions like the Advantech B+B Wizard Gen 2, can accommodate both approaches
• EDGE device is an embedded computer & software that acts as the digital data collection hub. It’s two primary functions are to poll sensors (and other data sources) via the Device Communication Engine and then forward this information securely to a final data repository.    Early EDGE devices focused on simply polling sensors, via a single communication protocol, moving the data to the cloud.  Next gen solutions are addressing the need to offer greater flexibility, connectivity and scalability at lower costs.  For example, our new InSource Edge device uses core components from the Wonderware technology stack, known for its universal connectivity, to offer communication with protocols such as MQTT (a newer IoT protocol), OPC-DA (a main staple of existing PLCs and other smart controllers) and even REST (Representational State Transfer) used to connect to web services and other 3rd party software applications). The flexibility to acquire data from multiple sources often gives the data better context.

In addition to collection, the EDGE device will ultimately pass the digital data on to the cloud platform, where it will be stored, analyzed and presented.  Newer solutions offer features like data store and forward that prevent loss of data in the event of communication failure along with vendor certified security.

• Analytics and Presentation Layer – the last piece is the final data repository platform that includes, long term data storage, analytics and visualization.   This space too is evolving rapidly, with specific, pre-engineered solutions emerging – like Energy, Building management, Filling line downtime & OEE – already offered and more to surely follow.

Again, there are two approaches we see gaining traction.  The first includes newer, cloud- based products from heavy hitters like Amazon AWS and Microsoft Azure.  As they have done in other IT applications, these platforms have the potential to be disruptive, offering companies large “data lake” repositories and pre-built analytics.   We have worked with a few early adopters to help them launch pilot projects, mainly to help channel data from their existing platforms, including Wonderware, to the cloud.  While the long-term potential shows great promise, early adopters share their concerns about the lack of  tools for plant-floor connectivity as well as difficulty attracting the experienced talent necessary to deploy and tailor these solutions. As a result, AWS & Azure initiatives can be pushed out of traditional automation and control engineering teams into much leaner IT departments, which can delay implementation.

This has spawned interest, in pre-built solutions like Wonderware Online, with pre-engineered applications that can enable customers to “see” their live data in hours.   Evolving AI tools, like predictive analytics, and pre-built solutions like downtime & OEE dashboards, deliver actionable results quickly with no in-house expertise required.  These cloud solutions are often delivered as subscriptions, allowing companies to scale up or down to suit their needs, operationalize their costs and achieve much quicker returns on a lower investment.  As a result, we see, more companies, piloting initiatives with pre-built solutions, developing in-house expertise as they go.  Then, as they gain knowledge, they are building more comprehensive 3-5 year plans that may include an incremental step-change to larger platforms like Amazon AWS and Microsoft Azure.

If you’d like to talk more about how we can help you implement IoT solutions in your company, please call us at 804-378-8981 or request a consultation online at:  www.insource.solutions.