Open Your Data's Potential Value

By Steve Mulder, Regional OEM Director, North America, and Dan Seger, Sr. Principal Engineer and Principal Architect, Rockwell Automation

Manufacturers across all industries are facing challenges to become more efficient and dynamic than ever before. In response, about 95% of manufacturers are using or evaluating smart manufacturing technology, according to the Rockwell Automation 9th Annual State of Smart Manufacturing report.

There’s no argument that data is key to meeting these demands. However, staying competitive as dynamics change will require more than just gathering the data; it also requires transforming a vast quantity of available data into actionable insights that drive results.

That means manufacturers need machines that can organize, contextualize and share data to help manufacturers unlock untapped value in their facilities and deliver new levels of intelligence throughout their operations.

OEMs Design with Data in Mind

End users know they need more data, but exactly what data they need now, and what they might need to succeed tomorrow, is often difficult to define. This is coupled with changing dynamics between OEMs and end users, where OEMs are expected to be integral to the success of the equipment for extended periods of time, and often must take a more active role in areas such as training, advising and integration to other processes.

These factors drive the need for OEMs to develop a new type of machine that not only provides more data, but data that can be easily accessed by other systems. Enter the data-ready smart machine.

What’s a Data-Ready Smart Machine?

Designing machines using data-ready technology offers a significant advancement in using operational data. These machines organize, contextualize and make information available for egress, allowing users to discover new insights across production lines, facilities and fleets of equipment.

This lets OEMs and end users define the data that’s needed and move it beyond the equipment level — breaking the digital transformation standoff where both parties struggle to align due to unclear data requirements and high upfront investment costs.

As a result, manufacturers can react to changes quickly in data requirements and meet future demands in a much faster, more efficient and lower-cost way.

Top 3 Key Value Points

Data-ready solutions give users the flexibility to introduce new components, revisit design and make adjustments, or modify applications to fit their unique needs. And no one gets locked into decisions that can’t be changed down the road. With the ability to organize and egress data and offer compatible sharing with nearly any external application, data-ready smart machines help provide value through:

• Data organization and contextualization.

• Decoupling and optimizing data flow.

• Combining functions such as visualization, data analysis, remote access and edge Industrial Internet of Things (IIoT).

Let’s look at these more closely.

Organize and Contextualize the Data. OEMs need to evaluate not only how to use data for additional value at the equipment level, but also how to stage that data for egress to the end user’s digital environments. Equipment data often appears as a large, and relatively flat, list of data points, offering little insight into the relevance of each data point.

By organizing the data into a model, individual data points can be grouped together to help define their relationship to one another. This includes additional data that helps define relationships between different parts of the model, providing contextualization to what is happening across the overarching process.

It’s this approach to organization and contextualization that begins the transformation of data into information.

Push vs. Pull: Decoupling and Optimizing Data Flow. There must be an intention behind how the data will be consumed. People can determine whether there’s going to be a steady stream of data — pulled by external end user applications such as supervisory control and data acquisition (SCADA) systems and Historians, or whether the data must be in a more transactional form — pushed at the right time from the control level to an application that is event driven.

Then, users need to make sure they have a modern platform that serves up the organized and contextualized data through a variety of IT-friendly protocols. Only meaningful data is collected and presented, easing the process of identifying the data needed by a specific end user application. Solutions that offer this optimization cut down on the data that’s sent out significantly, saving time and increasing productivity.

Combined Functions for a Machine-Level Solution. And, it’s important to recognize the need for a modern, machine-level solution that combines visualization, data analysis, remote access and edge IIoT. The ability to move data leads to a differentiated solution in the market. Many customers don’t know exactly what information they want. By taking this data-ready approach, it allows them to prepare equipment to be data flexible.

It is all in the name of efficiency. By unlocking the value in data-ready smart machines, users see an increase in efficiency and productivity right out of the gate.

Real-World Application: Performance Visibility

Traditionally, machine performance visibility was achieved by sending noncontextualized data to a local SCADA system and rarely further. Differences in reporting of data often led to an unclear picture of equipment and line performance.

With data-ready smart machines, performance data is organized into information models and, with a modern platform, giving greater insights at the machine level. The same information models can then provide a consistent picture of machine performance at the line level or beyond.

This information is even being made available to the OEM for them to monitor performance, offer support and gain powerful insights across their entire fleet of equipment — all from one source of information.

Horia Saulean, director of Robotic Solutions at DCC Automation, a Rockwell Automation gold-level OEM Partner, is an early adopter of a data-ready approach. “Our [end user] customers are really feeling the pain of labor shortages. They need to make informed decisions that help them achieve the highest OEE given their constraints,” he explains.

“Through implementation of data-ready solution sets in our equipment, we can give them information that supports predictive maintenance efforts and even power usage of the machines. This helps them make informed decisions about the use of their resources.”

New Levels of Efficiency

Data-ready smart machines provide a new approach to leveraging data, letting OEMs and end users unlock new levels of efficiency and business value. By decoupling data availability from consumption, users become intentional with how they organize information. This allows for more efficiency with less data being moved.

In addition, end users should have a modern platform to get the most value that combines visualization and the ability to egress that data from the equipment. Modern solutions provide the flexibility needed to navigate the complexities of digital transformation.  

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