Honeywell Connect Recap: Digital transformation, AI powering changes in manufacturing
Digital transformation remained a major theme at the second Honeywell Connect, but AI’s potential and use in manufacturing loomed large.
Digital transformation insights
- Digital transformation, coupled with artificial intelligence (AI), could have a major impact on how manufacturers run their operations.
- Digital transformation’s four critical components for success are data, processes, people, and technology.
- Generative AI could surpass the internet’s impact, enabling the creation of novel solutions from vast amounts of data inaccessible to humans.
The second Honeywell Connect event highlighted many of the same themes from the first show last November: Emphasizing digital transformation to improve operations, intelligence and make workers more efficient and safer. This time, with the show in Dallas rather than Orlando, Honeywell’s emphasis, according to Honeywell Connected Enterprise president and CEO, Kevin Dehoff, is about learning from their customers and using those lessons to improve the future regardless of industry.
“What we see is all our customers are affected by a common set of industry trends and disruptive dynamics,” he said in his keynote address.
This is part of a larger effort by Honeywell as they announced plans to realign its business segments to three trends: Automation (building and industrial), aviation and energy transition. According to a statement released during the event, this shift is intended to deliver accelerated organic sales growth and inorganic capital deployment, creating greater value for shareholders. The new segmentation will take effect beginning first quarter 2024.
The rise of digital transformation and artificial intelligence (AI) are among the leading trends pushing manufacturing forward. While AI, particularly in the wake of ChatGPT, are catching everyone’s attention, the digitalization and automation of the manufacturing floor is changing how things are made and how operations are run.
“Digital transformation is a step-change toward operational performance improvement utilizing data and software to make operations more intelligent and autonomous,” Dehoff said.
While digital transformation is valuable, it is a tool that is only successful if used correctly. In many cases, companies—just as they did with the industrial Internet of Things (IIoT)—leapt before they looked and did not get value. The same is true for digital transformation.
“Four components must be there,” said Sheila Jordan, senior vice president and chief digital technology officer at Honeywell during a panel discussion. “Data, processes, people and the technology. Often, those four have to come together.” She added another cardinal rule later: “Don’t automate a bad process. It’s the worst thing you can do.”
The world is moving toward a more connected and converged system that brings integration, innovation, information and infrastructure together. Digital transformation is at the heart of the new paradigm for manufacturers.
AI’s growing role in manufacturing
Artificial intelligence (AI) has been used in industrial control and automation for years, but the rise of ChatGPT, large language models (LLM) and more are helping people realize how it can improve operations.
I’m stunned by how much it’s taken off,” Dehoff said. “We view AI as an enabler of autonomous control and assists in embedding more intelligence into supporting decisions.”
That said, AI is useful for some applications and not others according to John Waldron, COO of Honeywell in a panel discussion, saying, “We’re not going to thoughtlessly put AI into them and lose control of what they can do.”
Traditional AI has been the norm for a long time, but it is more deterministic whereas generative AI can evolve and learn and do most human-level knowledge work with similar performance. This can enhance and improve the work already being done and allow humans to take on new tasks and roles.
Jordan made a bold prediction regarding generative AI.
“Generative AI will be more impactful than the internet was,” she said. “Generative AI can take these ideas and insights and create new solutions. There’s a plethora of data out there and generative AI can take it to a place humans can’t physically go.”
The catch is many companies, like they were in their IIoT and digital transformation journeys, have a long way to go.
“Only 2% know how to scale their AI programs without significant challenges,” said Sunil Pandita, VP and GM for cybersecurity and connected industries at Honeywell.
That is a daunting—but also exciting—situation for companies as they look to leverage themselves toward the future of manufacturing with AI and machine learning (ML) making operations smarter in the right circumstances.
Waldron said, “There are absolutely applications where they are worthwhile. They are probabilistic, which is super useful. We’re able to create predictive models on where they might fail. Couple that with service data and learn the history of the asset, combined with the real-time data, to make sure we have the right solutions and best outcome. “
Digital transformation, AI and ML have the potential to take companies in a new and exciting direction, but companies first have to realize what it can potentially do for them.
That part will take a little longer.
Chris Vavra, web content manager, CFE Media and Technology, firstname.lastname@example.org.