Manufacturers ask and AI technology answers
The following article on Bennit AI was featured in Impact magazine and written by Beth W. Orenstein
Henry Ford, one of the world’s greatest manufacturers, had a right-hand man named Harry Bennett, known for helping Ford “get things done.” Based on his abilities, three manufacturing industry professionals have developed a way for every manufacturer to have a trusted assistant like Bennett, this one virtual and digital.
The app they created, called Bennit, not only serves as a production assistant but can also be tailored to users’ products, services and roles in their companies.
“Because Harry Bennett was found to be more of a brawler than a consensus builder, our team changed the spelling of the product (and company) name and took the opportunity to add ‘IT’ to it—thus Bennit,” says Michael Yost, one of the three founders and chief marketing officer.
The company, Bennit Inc., went from the idea stage in the middle of 2016 to engaging early adopters last year. Thanks to seed money, including a $25,000 grant from Innovation Fund Northeast Ohio, a number of companies—including a tire manufacturer in Northeast Ohio—are learning about what Bennit can do for them. Later this year, Bennit plans to launch an Early Adopter Program targeted at shift supervisors, who will be able to access the app via individual subscription.
The idea for the company emerged from the evolution of manufacturing worldwide. “There’s a renewed, sustained focus globally to enhance manufacturing through the use of advanced information technologies,” Yost says. Germany has Industrie4.0, China has Made in China 2025 and the U.S. talks of “smart manufacturing” – enabling all information about the manufacturing process to be available to help make smart decisions when and where it is needed across entire manufacturing supply chains and product lifecycles.
Yet most manufacturers are small to medium-sized companies, and they are left out of these initiatives, Yost says.
“Big data analytics (the process of examining large and varied data sets) on a global fleet of wind turbines to ensure uptime isn’t going to help a 20-person company that builds pallets in northern Ohio,” he says.
And even though manufacturers of all sizes have been installing devices to measure production and automating their equipment for decades, they still have gaps, Yost says. Industry insiders refer to the data not captured in IT systems as “dark data.”
“Most of what happens in a plant every day isn’t captured in an IT system,” Yost says. “So the manufacturers are right that they can’t analyze most of what happens.”
Bennit lives on data. It is constantly consuming them, interpreting them and learning from them.
“It connects manufacturing personnel to peers and information they need when they need it,” Yost says. “That information may come from existing systems such as the machines, or from their human resources department, or from Internet of Things (IoT) platforms. It even can come directly from fellow team members.”
The Bennit entrepreneurs have found a way to capture this information and use artificial intelligence and machine learning techniques to analyze individual and group sentiment and learn which factors play into a manufacturer’s success.
“As the system learns, it will ultimately have answers to problems for workers before they even know what questions to ask,” Yost says.
Yost sees Bennit working much like the iPhone’s Siri, Microsoft’s Cortana, or Amazon Echo’s Alexa. He offers these examples of how small to mid-sized manufacturers might use Bennit as a personal assistant.
- Troubleshooting. There’s a breakdown on a production line. Ask Bennit: “What are the most likely causes of this type of breakdown?” If it’s a component such as winders, ask, “Who is our company expert on winders?” Or, “Please show me the troubleshooting guide for this component.”
- Real-time collaboration. “Hey, Bennit, who ran into this same fault last? Please connect me to them.” Or, “Bennit, which operator runs this machine the best? Please tell the operator I would like to talk to him about what he is doing different.”
- Production optimization. “What are the top three reasons for our downtime in March?” Or, “Please recommend the best window to do planned maintenance on Press 7 before third shift.”
- General and personal assistance. “What is the last run of the day?” Or, “Who called in sick today on second shift?”
Bennit also can track workers’ activities to learn the best safety procedures on the manufacturing floor and what they might need to improve to prevent accidents.
When reviewing Bennit’s grant application, Dennis Cocco, director of the Innovation Fund, says he was impressed by both the immediate benefits manufacturing companies can experience with Bennit’s technology, and the potential it holds as AI evolves and manufacturers better understand its capabilities.
“AI is rapidly changing itself, and the world we live in,” Cocco says. “In the next 10 to 15 years it will have a profound impact on manufacturers in Northeast Ohio and I’m excited to see companies like Bennit harnessing its power now and showing companies how it can change their business for the better, while keeping the future wide open.”
Yost agrees. He often hears people talk about ‘smart manufacturing’ as a journey and believes there’s truth in that. “But that implies a long road ahead and we don’t think the road’s that long,” Yost says. “We encourage manufacturers to keep the end in mind, jump in now, and see where things go.”