Igniting Technology focuses on SMART Workers
By Sharon Henry
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Irvine, June 03, 2015 --
More than 100 people attended the latest Igniting Technology program held May 28 at Calit2. Igniting Technology is a semiannual panel presentation sponsored by intellectual property law firm Knobbe Martens Olson & Bear LLP in partnership with the UC Irvine division of Calit2. Each event examines a critical issue that can be improved through technologies in development at UCI.
The evening’s topic, “SMART workers: Employing an IoT (Internet of Things) approach to advanced manufacturing,” featured six presenters, including researchers, industry partners, entrepreneurs and venture capitalists. Individual presentations were followed by a moderated question-and-answer session with the audience.
A leader in the Internet of Things movement, Calit2 has developed and integrated technology into devices and applications. When President Obama launched the Advanced Manufacturing Partnership, Calit2 saw an opportunity to apply its IoT and people-centric approach, and launched a Sustainable Manufacturing Alliance for Research and Training (SMART). SMART’s vision is to employ technology to empower workers with greater autonomy and decision-making responsibility, resulting in greater enterprise sustainability.
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“The focus on workers is critical to the evolution of U.S. industrial sectors,” G.P. Li, Calit2 Irvine director, said as he welcomed attendees.
Michael Guiliana, a partner at Knobbe Martens Olson & Bear, moderated the event. (Links to speakers’ presentation slides can be found below.)
MANUFACTURING INTELLIGENCE
“Traditionally, we’ve used workers to do manual labor,” said Mark Bachman, Calit2 IoT evangelist and UCI assistant professor of electrical engineering and computer science. But with IoT, the value of a worker shifts from using his/her hands to using to the brain, he added. Because the human being is the ultimate sensor, with the ability to learn, think and adapt better than any algorithm, Bachman predicts the SMART worker – an individual enabled by sensors in a “gamified” workplace – will become the ultimate manufacturing asset.
Jim Davis, UCLA vice provost of IT & chief academic technology officer, who is also principal investigator of the Smart Manufacturing Leadership Coalition, sees “huge opportunities” presented by manufacturing intelligence and by creating smart manufacturing platforms. “We’ve never been able to work with the machine side before,” he said. “What we are really trying to do is put data to meaningful use.” An example, Davis explained, would be to see inside a working furnace to gather data in real time. By understanding how data can be moved back and forth, manufacturers are already learning they can save energy and increase revenue.
Jim Davis sees “huge opportunities” in manufacturing intelligence.
Arquimedes Canedo suggests exploring the socio-technical aspects in the factory of the future.
Arquimedes Canedo, principal scientist at Siemens Corporate Technology, urged people to explore the socio-technical aspects in the factory of the future. Canedo noted that ongoing, open discussions in Germany are seeking ways to “strike a balance between the interests of employers, employees, unions, schools and government,” as digitalization of factories and the economy radically changes the way people work. He encouraged a “call for action in the U.S.” to initiate a dialogue around technology, worker safety and welfare, new team structures and continuous on-the-job educational opportunities.
CONNECTED INTELLIGENCE
“These days everything is being connected,"Kelly Frey, VP of product marketing for Telogis, told the crowd. “Everything is going to be built with a modem for connectivity, GPS for location, as well as sensors, and it’s not just consumer devices – it’s the things in our industries too.” Connected intelligence provides data that is more than merely supplying a location, he said.
Software in Google's self-driving car captures everything it sees moving – cars, trucks, birds, rolling balls, dropped cigarette butts, and fuses all that together to make its decisions while driving,” he said. “If it sees a cigarette butt, it knows a person might be creeping out from between cars. If it sees a rolling ball it knows a child might run out from a driveway,” Frey said, quoting Idealab founder and CEO Bill Gross.
Chuck Wambeke, president of Industrial Automation Consulting, Inc., discussed his experiences as an applications engineer, “working to empower the workforce in different environments” by automating manufacturing facilities in areas including industrial mineral processing, water production and distribution, and wastewater collection and treatment. “Most of the smaller communities only have a few people that are responsible for the wastewater system. They really need a more economic means of providing automation and access to their systems,” he said. By working with Verizon to establish private networks and a “communications backbone” for municipality infrastructures, plus customizing the user interface and using cloud hosting, “the workers can access that system with virtually any browser,” Wambeke said. “We’ve been able to reduce the cost by about 30 percent with this technology.”
SCALABLE INTELLIGENCE
The traditional way to predict failure in a machine involves extracting data from the field, building a model, and having conversations with subject matter experts who understand how to manipulate machines and scientists who can interpret data. “It’s a long and complicated process,” said Oren Goldschmidt, general partner, and chief technology and strategy officer at Frost Data Capital (a company that builds and sells startups focused on big data and analytics). “And how do you scale this process?” he asked.
Scalability is a human problem, not a machine-related problem, Goldschmidt believes. “We’ve provided these very experienced engineers, who work around pumps in the oil and gas space, with a user interface that lets them visualize the data,” he said. “What we focused on was how to translate their ability to see a pattern? How do you translate that into something a machine can do?” The company built a user interface that lets users describe patterns in a technical, but still familiar way, then translates that information into a predictive model. “We’ve translated the knowledge that this worker has into something that can run 24/7. You’ve got a human who is teaching the machine,” Goldschmidt said.
WORKER OF THE FUTURE
How well will the worker of the future accept IoT technology? “Nobody today is going to tell you how it’s going to be done 10 years from now,” Bachman said. “We’re going to see it evolve as our cultural norms accept certain technologies and don’t accept others, so it’s hard to predict. We find that people are willing to adopt these technologies if there’s a perceived benefit and they are part of the process. It’s easy to image some terrible scenarios and I’m sure we’ll see some. But it’ll be interesting to see how it evolves and what we do finally accept.”
Available presentations:
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