Modernizing IIoT Operations with InfluxDB

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Continuing in our series of InfluxDays recaps, we turn our attention to Brian Gilmore’s presentation on Industrial IoT. This is an area that uses time series data extensively and has a lot of room to expand the way it uses this data. Here’s a quick breakdown of where things stand today.

Challenges in modernizing industrial operations

Navigating the divide between the physical and digital realms in the manufacturing space is a challenge. In many areas, a digital divide exists whereby companies are hesitant to adopt newer, digital solutions. Gilmore identified several factors that contribute to this situation.

One is the idea of local awareness. Operators have access to raw data from machines and processes on the factory floor. However, actually using that data still involves manual steps, like spreadsheets. The fallout from this is that manufacturers rarely have advanced analytics that provide insight on that data. This means that they’re missing opportunities for optimization.

Another factor is remote visibility. Remote can refer to distributed systems, like edge devices, or simply being able to see what’s going on with a machine without having to be standing at it. What operators ultimately need to be able to do is to understand what’s going on in remote devices or processes and act on that data in an effective and timely way. While some of the remote visibility issue relates to security, businesses can get around this by providing secure, read-only access to data.

A human element provides another challenge. There is a need to transfer domain expertise from seasoned veterans who know all the systems and processes to the next generation of manufacturing professionals. The incoming generation of workers are primarily digital natives who have a very different skill set and expectations around how to interact with technology. This creates a need to codify and/or automate processes and institutional knowledge in a way that allows tech-savvy workers to step in and be productive from the start.

Industrial process historians

A critical piece of operations technology (OT) in this whole equation is the process historian. These legacy systems have some key advantages, but there are also several drawbacks in the context of modernizing operations.

  • The good – These legacy data historians provide real-time data, and they’re very well integrated into manufacturing processes and the OT tech stack. As a result, they’re very familiar and comfortable for operators.

  • The bad – One of the most frequent complaints about legacy data historians is the cost. These are on-prem solutions with no cloud option. They tend to be very complex software, designed for experts. This makes them inaccessible to many potential users. Critically, these solutions are also siloed, providing very little interoperability with other systems.

  • The ugly – The fact that legacy systems are siloed is certainly an issue, but the impact of siloing is significant. It is challenging to integrate legacy historians with IT systems and, more broadly, cloud and SaaS services. The lack of interoperability also slows innovation because users can’t take advantage of emerging technologies like artificial intelligence or machine learning. This leads to missed opportunities for optimization and limits the ability of plant workers to experiment and innovate.

Embracing the digital factory

Although challenges certainly exist with current IIoT technology stacks, there’s also a ton of untapped upside, too. Embracing technology to implement and improve observability reduces the amount of time that operators spend working on issues because they don’t need to physically chase them down on the plant floor. Digital efficiencies create a proactive environment that saves operators time and encourages innovation.

InfluxDB can replace legacy data historians. Not only does it serve as a data store, the InfluxDB platform facilitates data collection, transformation, and automating actions based on data analysis. Users can build applications and dashboards with the kinds of tools that digital native employees are familiar with and want to use.

IIoT recap-Time Series Application

Furthermore, the InfluxDB platform can function as a vertical stack in IIoT contexts, extending the power of the database to the edge, where data is born. Not only does this expand opportunities for innovation and localized insights at the edge, but it also provides seamless integration and interoperability across the entire system from any point of that system.

Focusing on observability through digitization enables all kinds of use cases. Whether that involves failure detection and forensics, predictive maintenance, optimization, or alerting, IIoT operators can do more in less time, yielding better results. If you need some ideas, see how companies like Herrenknecht AG, Algist Bruggeman, Vleemo, and others are leveraging time series data in the IIoT space.

IIoT recap 2

A new IIoT tech stack

Combining InfluxDB with other open source and/or familiar IT and OT software and processes can unlock significant potential. The makings of a modern manufacturing tech stack already exist. It’s up to businesses and operators to determine what information they want from their industrial operations and the best way to get those answers based on their needs and resources.

IIoT recap - new IIoT tech stack

For more detailed discussion of these topics, check out the full presentation.