How Data, the Edge and Cloud are Transforming Manufacturing

Across the manufacturing landscape, innovations in connectivity, computing infrastructure and controller interoperability are transforming the way companies can get more value from their existing equipment to improve efficiency and operations. But in many cases, manufacturing facilities are bogged down by proprietary automation and control systems, legacy equipment and outdated approaches to data collection and integration.

By integrating new technologies such as 5G wireless connectivity, edge computing and understanding the types of data that should be sent to the cloud versus processed locally for real-time decision-making, companies can begin to gain competitive advantages and digitally transform.

Related Webinar: From the Edge to the Cloud, Smart Technologies Create Competitive Advantage

Watch for Free

“What we’ve seen in the last four years is that data went from a bit player to really a starring role,” says Irene Petrick, Senior Director of Industrial Innovation, Intel Internet of Things Group. “The challenge [for companies is how they] think about data in a completely different way. Do I need data in the moment? Do I need it over time? Those are questions we haven’t had the luxury of talking about too much.”

Petrick’s comments were part of the first webinar hosted by the Association for Advancing Automation (A3)’s new Intelligent Edge for Industrial Application series, which explores the Industrial Intelligent Edge, its capabilities and business impacts. Petrick was joined in the webinar by Jonathan Luse, General Manager of Product Planning for Intel’s IoT Group, and Ricky Watts, Director of the Industrial Solution Division (via videos at the recent Hannover Messe conference). The panel discussed themes and trends around edge computing, the cloud, connectivity, interoperability, security and the value of key partnerships.

Seeing the big picture before you start

In the webinar, panelists discussed how many companies often attempt to “smart small, fail fast, learn and redeploy”, which often ends up with “pockets of excellence” in different areas of the company, but do not integrate with each other to drive additional value.

“Based on the research we’ve done, we say start with the vision of what digital technologies and solutions can bring to your operations that you can’t do now, or that can improve what you’re doing from a performance or efficiency perspective,” says Petrick. “Start with a vision of what’s possible, and then identify smaller pieces that you can move forward – then you can deploy, learn, fail fast, learn quickly and redeploy.”

Preparing for a flood of data

When discussing data, Petrick outlined many of the processes involved as industrial companies begin to digitally transform, including collecting data from new sensors, actuators, meters, legacy systems, smart machines and human-machine interfaces, including robotics and other automated systems. With so much data available, many companies are struggling to figure out what is the “right data” to use, but also whether the data needs to be processed locally at the edge, or if it needs to move into a cloud environment for further processing and analytics.

“If I were a control operator or plant manager, I would be absolutely excited and cautious at the same time about the opportunity of what’s coming,” says Luse. “The ability to gather operational data at scale and generate meaningful information in near real time will lead to this sense of an unlimited opportunity for an industrial manufacturer

Petrick adds that customers need to have an architecture in mind and understand what they want to accomplish before they decide whether to send the data to the cloud or process it locally. “Data is only useful if it prompts action,” says Petrick. “So either I prompt action directly through updates to models and give real-time feedback to control systems, or I’m doing it by bringing in data and analytics to completely new types of models.”

The benefits of interoperability

One of the positive movements in the industrial IoT space is the willingness of companies to explore how to connect formerly proprietary systems to talk with one another to make operations more efficient. In one of the videos shown from the Hannover Messe show by Watts, he discussed the OPC Foundation, which is working on industrial interoperability standards to connect different PLCs. Ease of integration and interoperability are essential to digital transformation, particularly when we think about legacy systems. These issues span data, hardware and software.

Luse gave an example of the problem regarding interoperability that he has seen in the pharmaceutical industry. “In the lab environment they have all these data sets and all the recipes” for a new drug, he says. “But when they get to the high-volume manufacturing of that drug, there’s there are other operational processes and the lab data doesn’t translate into operational conditions. This represents a time-to-scale gap where the lab environment to the production environment has a lull because they have to take the recipe from the lab and re-tune it and revalidate it,” which takes potentially months to happen. “I look at the opportunity for Intel to help solve things like that,” says Luse. “If we can figure out how to go from lab data set integrating seamlessly to a production environment moving data securely and accurately across those environments, the net result of that is you get production of that pharmaceutical or drug faster. That will have a benefit on society that is well beyond the economics of the production factory.”

To learn more about some of the big trends discussed in the webinar, click here to view it on demand.

BACK TO ARTIFICIAL INTELLIGENCE BLOG