Democratizing Data at the OT Edge

Claudio Fayad, Vice president of technology, Emerson

Claudio Fayad, Vice president of technology, Emerson

Claudio Fayad serves as vice president of technology of Emerson’s Process Systems and Solutions business.

Prior to this role, Claudio held a variety of positions within Emerson from sales and marketing director to vice president of software. He joined Emerson as director of Process Systems and Solutions in May of 2006 based in Brazil. Before Emerson, he started his career with Smar in 1995 as systems engineer and progressed through various roles of sales. Claudio served as the global engineering sales director in his last role with Smar.

Claudio holds a bachelor’s degree in engineering from the Universidade Estadual de Campinas and a master’s degree in business administration from Northwestern University.

As companies engage in digitalization of their process manufacturing operations, they are focusing more on the edge—the compute power closest to operations. But as these groups move to the next phase of digitalization, the role of the edge is expanding beyond control, interlocks, and digitization to include securely democratizing data.As edge technologies aggregate, centralize, contextualize, and normalize data, they empower cross-functional teams to not only solve the plant’s most difficult problems, but also enablenon-siloed innovation to drive the process improvements necessary to win the future of manufacturing.

Islands of data slow innovation

We have known for decades that collecting data around the plant on paper records and handing them off to process engineers for optimization is no longer enough to maintain competitive advantage. Not only are paper processes inefficient, but the expert personnel required to make use of that data are becoming scarce as retirements increase. Digitization is critical; however, even the traditional methods of digitizing data offer many opportunities for improvement.

When individual business areas digitalize their processes independently, they can create incremental improvement. Aspecific business unit optimizing its operations will almost certainly run more efficiently and effectively. However, if digitalization doesn’t focus on breaking down silos between groups, it creates islands of data, stagnating improvement. When someone else in the organization needs that group’s data, they often find it exists in a different format within an entirely different database.

Not only do they need to convert the data to make it useful, but as soon as they access it, the data is old, and if they want new data the process must begin again.

Consider a team that discovers it consumed more energy than expected on a given day and wants to know why. After collecting their energy consumption data, the team needs to identify energy consumption per individual equipment, which may be historized in another system and owned by a different group. If the team can get permission to access the data, it might even need to be queried in a different way. The team cannot immediately cross reference that data or feed it into artificial intelligence or machine learning applications. To use the data, they must convert it into a different format or create a replica database—both time-consuming activities requiring specialized expertise.

Democratizing data for holistic performance improvement

Today’s digital manufacturing platforms empower cross-functional teams to access any data they need on demand. Armed with this valuable, contextualized data, manufacturers can improve productivity by 5-10 percent or more by finding new ways to debottleneck—not by optimizing single units, but by optimizing interaction between those units.

True data democratization means making the right information continuously available to the right people, hassle-free. Such a solution requires an integrated operational technology (OT) platform allowing any team in the plant with the right credentials to easily access data and generate insight that will foster innovation. With this shared, easy access, agile, cross-functional teams can quickly tackle problems, identify root causes, and develop insights that will determine the best solution.

Unlocking data’s value with edge technologies

As companies begin their journey toward data democratization, they run the risk of accumulating too much data in data lakes, rendering it useless.If a data lake contains nothing but asset values and tags, it can quickly become a data swamp, filled with data that is only usable by a select few experts.

The expanding OT edge is democratizing data and empowering innovation

Effective cross-functional teams will need rich data that contains not only the tags but all the essential metadata for contextualization, making it discoverable and searchable. To provide such rich data, teams leverage modern technologies to create compute nodes at the edge that contain application programming interfaces (API), new protocols, and more to collect all necessary metadata and standardize data for easy sharing across the organization.

Edge nodes can be secured by separating them from the control system via data diodes or zero-trust architecture, providing access to rich data while preventing direct access to the control system. When properly architected, these systems can securely combine data from multiple systems and sources to provide sandboxes where teams across the organization can run machine learning/artificial intelligence algorithms, scripts, smart reports, and more.

Driven by data

The expanding OT edge is democratizing data and empowering innovation. Driven by modern connectivity technologies and protocols, OT edge technologies are improving companies’ digital maturity by collecting contextualized data into databases and providing the necessary APIs to ensure operations data is not just for expert OT personnel. Instead, it can be accessed by anyone across the organization without any risk to the control system or the operations of the plant.