The realities of the new digital economy have taken hold, and as a result most manufacturers have embraced a wide array of pilot programs – finding realistic opportunities to embrace IIoT, and looking to interesting ways to capitalize on data analytic investments.
Unfortunately, the undergoing the pilot is often easy part of digital transformation, HighByte co-founder and CMO Torey Penrod-Cambra tells IndustryWeek. “The hard part is scaling up and maintaining the often complex data and system architecture that IIoT creates,” she says. “If manufacturers don’t have a logical way of managing and standardizing their data models, they are building their IIoT infrastructure on a house of cards.”
Unfortunately, the ongoing IT/OT convergence is creating an environment where it’s difficult to address broken integrations. Why? Far too often organizations lack a point person or department with full responsible for managing the growing number of integrations, and the data infrastructure is too fragile to support a dynamic factory environment.
Simply put, OT lacks a tool to efficiently and securely facilitate the flow of information throughout the organization, explains Penrod-Cambra. “If manufacturers are going to successfully roll out IIoT, they need someone dedicated to data operations or DataOps.”
According to Penrod-Cambra, the key to closing the gap rests with the creation of a new discipline focused on DataOps. “Many manufacturers currently don’t have this discipline ramped up—some haven’t even considered it. This role needs to be responsible for data governance, data models, and the semantic layer—specifically as these pertain to industrial automation data,” she says. “We think this role will probably be most successful if it’s born out of the OT organization, which already has the inherent knowledge of what this data is. The final component is providing this function will a tool they can use to securely manage and model industrial data in real time at the Edge.”
Filling the Gap
HighByte’s newly released Intelligence Hub enables operations to securely connect, model, and flow valuable industrial data to the users and systems that require this valuable information throughout the extended enterprise. The platform-agnostic software solution runs on-premises at the Edge, securely connects devices and applications via OPC UA and MQTT, is built for scale, and offers a codeless user interface. HighByte has positioned the software solution as the missing data infrastructure link to achieving the vision of Smart Manufacturing and Industry 4.0.
“As the number of applications that need to turn raw data into usable information increases, the customer is faced with having to recreate models in every application or develop their own solutions that integrate with the various APIs. Either choice slows down the initial deployment of Industrial 4.0 initiatives, inhibits the ability to scale, and places a huge maintainability problem on the customer,” said HighByte CEO Tony Paine. “With HighByte Intelligence Hub, customers can standardize and maintain their data models in a single location, securely streamline information flows, and accelerate time to value for their Industry 4.0 investments."
Early adopters in factories around the world recognize the untapped value of industrial data coming from machines and process controllers on the plant floor. More users and systems want access to this data in real-time to convert it into useful information they can act on—like predicting machine failure, preventing downtime, and improving product quality. Unfortunately, raw operations data lacks context, standards, and correlation, impairing its ability to be used by business functions outside of Operations. This has created the need for DataOps solutions to enter the industrial market.
Bottom line, as organizations look to move past the pilots, it’s time to embrace the tools that enable manufacturing environments to scale. This means collaboratively and cross-functionally thinking about the organization’s long-term vision to create a workable strategy, explains Penrod-Cambra. “It’s important to think about scale from the start. Manufacturers should be thinking about their end architecture before even running a pilot,” she says. “It’s just not that helpful to run a pilot with an architecture that’s not extendable.”
