Two former Apple design engineers – Anna Katrina Shedletsky and Samuel Weiss (photo) – have leveraged machine learning to help brand owners improve their manufacturing lines. The company, Instrumental, uses artificial intelligence (AI) to identify and fix problems with the goal of helping clients ship on time. The AI system consists of camera-equipped inspection stations that allow brand owners to remotely manage product lines at their contact manufacturing facilities with the purpose of maximizing up-time, quality and speed.
Shedletsky and Weiss took what they learned from years of working with Apple contract manufacturers and put it into AI software.
“The experience with Apple opened our eyes to what was possible. We wanted to build artificial intelligence for manufacturing. The technology had been proven in other industries and could be applied to the manufacturing industry,” Shedletsky, CEO at Instrumental, told Design News. “It’s part of the evolution of what is happening in manufacturing. The product we offer today solves a very specific need, but it also works toward overall intelligence in manufacturing.”
Capturing Manufacturing Know-How in the Software
Shedletsky spent six years working at Apple prior to founding Instrumental with fellow Apple alum, Weiss, who serves Instrumental’s CTO. The two took their experience in solving manufacturing problems and created the AI fix. “After spending hundreds of days at manufacturers responsible for millions of Apple products, we gained a deep understanding of the inefficiencies in the new-product development process,” said Shedletsky. “There’s no going back, robotics and automation have already changed manufacturing. Intelligence like the kind we are building will change it again. We can radically improve how companies make products.”
There are number examples of big and small companies with problems that prevent them from shipping products on time. Delays are expensive and can cause the loss of a sale. One day of delay at a start-up could cost $10,000 in sales. For a large company, the cost could be millions. “There are hundreds of issues that need to be found and solved. They are difficult and they have to be solved one at a time,” said Shedletsky. “You can get on a plane, go to a factory and look at failure analysis so you can see why you have problems. Or, you can reduce the amount of time needed to identify and fix the problems by analyzing them remotely, using a combo of hardware and software.”
Bringing Computer Eyes to the Factory Floor
Instrumental combines hardware and software that takes images of each unit at key states of assembly on the line. The system then makes those images remotely searchable and comparable in order for the brand owner to learn and react to assembly line data. Engineers can then take action on issues. “The station goes onto the assembly line in China,” said Shedletsky. “We get the data into the cloud to discover issues the contract manufacturer doesn’t know they have. With the data, you can do failure analysis and reduced the time it takes to find an issue and correct it.”
Instrumental includes a machine-learning Detect feature that highlights units that appear defective. When used in combination with the rest of Instrumental’s software tools, an engineer can identify an issue and then take the next step by virtually disassembling concerning units and even taking measurements to understand what is wrong. These remote and on-demand first pass failure analysis tools are designed to save time and communication between companies and the factories that make their products.
Instrumental system includes data-capture hardware at the manufacturing site. The hardware feeds data into the software for analysis. “We view ourselves as a manufacturing data company. We do have hardware because we have an off-the-shelf system that can be deployed at the contract manufacturer,” said Shedletsky. “We connect to the contract manufacturer to get the data. The data goes to the user via the cloud where it’s analyzed for defects,” said Shedletsky.
Rob Spiegel has covered automation and control for 17 years, 15 of them for Design News. Other topics he has covered include supply chain technology, alternative energy, and cyber security. For 10 years, he was owner and publisher of the food magazine Chile Pepper.
Images courtesy of Instrumental