Creating a real-time data-driven visual decision support system for the factory floor
Guiping Hu has set out to make manufacturing production more efficient. The associate professor of industrial and manufacturing systems engineering is working on a project for the Digital Manufacturing and Design Innovation Institute (DMDII) to develop a shop floor decision support system called FactBoard.
DMDII is a federally-funded research and development organization of UI LABS focused on projects that demonstrate and apply digital manufacturing technologies to increase the competitiveness of American manufacturing. Hu says FactBoard fits the bill because it will help manufacturers respond to changes in real time.
The project aims to convert thousands of existing, real-time data inputs into a collection of visual dashboards, creating a record of transactional data that can be used to make informed decisions about production.
“Each manufacturing floor is different – there may be a logistics problem or a production process that needs adjusted,” Hu says. “With FactBoard, we can use information based on data that is already available, set up parameters and organize data based on the needs of each shop.”
At Iowa State, four faculty members, five graduate students and several undergraduate research assistants are helping Hu with the project. Hu’s also working with Boeing, John Deere, Proplanner and Factory Right to develop the technology.
The group has been surveying manufacturing floors to identify 5-10 key problems that are common across industries. Narrowing that list down hasn’t been an easy task, but it’s why Hu says having a range of companies involved at the beginning of the project is so important.
She adds that because she has such a wide audience for FactBoard, the team is creating a system that can be incorporated within individual IT frameworks through XML integration methods.
Once FactBoard is implemented, Hu says manufacturing facilities can use it to improve how they manage inventory and on-time delivery methods as well as the efficiency and effectiveness of production equipment.