Walk onto any manufacturing floor, and you’ll probably see a dramatic range in computer technologies, ranging from the latest highly automated machines to decades-old equipment with primitive data systems. Oh, and don’t forget the human operators working with pads of paper. Each day when millions of manufacturing employees across the United States go to work on production lines, “they basically are told, put your smartphones and tablets away, forget they exist,” says Natan Linder, co-founder of Tulip. “That’s pretty crazy, and it’s something we need to fix.”
We enable manufacturers to create shop floor apps, much like the apps on your phone, that allow you to access data and make decisions.
“In this era, we have to build apps for those people in the environments where they work,” Linder says. “Behind every product there are people, and we don't see that changing. It’s people who have the spark to figure out how to manufacture something two times cheaper, and it's people who train the next batch of employees, and it's people who have a bad day and make the terrible mistake that reduces manufacturing quality. Tulip, an MIT Startup Exchange STEX25 firm in Somerville, MA, focuses on bringing these employees on shop floors fully into the Internet era. The company’s manufacturing operating system allows process engineers to create shop floor apps, with interactive step-by-step work instructions that are enabled with sensing and data collection using Internet of Things (IoT) gateways. “The apps give you access through our cloud to an abundance of information and real-time analytics that can help you measure and fine-tune your manufacturing operations,” Linder says. In a pilot project with one Industrial Liaison Program partner in biopharmaceuticals, for example, the Tulip took on the challenge of training new operators on a highly complicated, customized and regulated manufacturing process. Previously, the only way to train new operators was to walk them repeatedly through all the steps with an experienced operator and a process engineer. Tulip quickly deployed its software along with IoT gateways for the machines and devices on the process, and managed to cut training time almost by half. App comparisons “We enable manufacturers to create shop floor apps, much like the apps on your phone, that allow you to access data and make decisions,” Linder says. “The apps help to guide people through the manufacturing process, and to provide a host of information and analytics.”
Tulip’s operating system has three components: a layer to connect tablets or smartphones or other interfaces, an IoT layer to connect manufacturing systems and devices, and a cloud environment for creating apps and analyzing their data in real-time. “Our cloud authoring environment basically allows you to just drag and drop and connect all the different faucets and links to create a sophisticated app in minutes, and deploy it to the floor, without writing code,” he says. Different types of manufacturing engineers will develop different types of apps, Linder notes. Quality engineers, for instance, typically gather data for analysis, with automated collection devices using various sensors such as thermal cameras, machine vision systems or digital calipers.
Manufacturing often remains mass production, but products also will be built and customized to order, which means our factories need to become much, much smarter. They need data-driven flexible production lines, and people will be the key factor in gaining access to these new smart factories.
Process engineers primarily focus instead on designing work instructions. “These instructions are the key documents the industry uses to create step-by-step processes, but they usually end up as wallpaper, because humans learn and remember and just avoid using them,” Linder comments. “The problem is that this lowers the chance of changing a process, because it is tough to change a static document. It's easier to change a Tulip interactive document or app that has a digital thread and has an easy way to collect comments on the process and to share them around.”
“Once those apps are live and active, you can just hop on the backend and start querying our analytic system,” he says. “This provides tremendous insight into what you told people to do and what they actually did, with the tools and sensors and machines that they used. You have access to real-time information about what's happening on the floor, which is otherwise very hard to get, especially because you don't normally put sensors on people.” In one pilot project for a discrete manufacturing operation, for instance, an app can show a process engineer what each individual operator carried out at a certain point in time. The engineer might see that the cycle time for one step is set to 10 seconds but nobody on the production line can hit that mark, while some operators have found a way to perform another step in the process more quickly than expected.
“That level of granularity is important when you're trying to get a manufacturing process tuned to be the best that it can be,” Linder says. “And labor is such a big component of the cost that this really comes down to the bottom line.” Growing Tulip A software engineer with particular interests in embedded engineering and manufacturing, Linder worked at several electronics firms before earning a PhD at the MIT Media Lab. (While at the Lab, he also cofounded Formlabs, which builds high-resolution 3D desktop printers.) As he worked on his doctorate, Linder and Tulip co-founder Rony Kubat studied human/machine interface problems in manufacturing in partnership with Media Lab sponsors. Spending a lot of time in factories, the two graduate students spotted a much bigger problem on the shop floors. “Operators working with very sophisticated automation were using pads of paper, which is mind-boggling,” he says. “They don't communicate or access information in the way we take for granted.” That challenge called for a new type of information platform, and Linder and Kubat founded Tulip in 2014 to build it. “Our ideal partners are manufacturing organizations who want to leverage their manufacturing work force,” Linder says. “They want to give tools of this century to the people on the lines, enable them to make quick decisions on the fly, and rely on them to take their production processes a step further.” “Manufacturing often remains mass production, but products also will be built and customized to order, which means our factories need to become much, much smarter,” he adds. “They need data-driven flexible production lines, and people will be the key factor in gaining access to these new smart factories.”