The initiative will make it possible for the system to detect early signs of wear, aging and fault conditions in the machines.
The Digital Manufacturing and Design Innovation Institute (DMDII) is providing $750,000 in funding while the other four entities are matching that amount through a cost-sharing agreement.
Dazhong Wu, senior research associate in the Harold and Inge Marcus Department of Industrial and Manufacturing Engineering (IME) and Janis Terpenny, professor and Peter and Angela Dal Pezzo Chair and Head of IME, are the lead researchers of the project.
They are joined by Robert Gao, Cady Staley Professor of Engineering and chair of the Department of Mechanical and Aerospace Engineering at Case Western Reserve University, Li Zhang, senior research scientist for industrial Internet of Things (IoT) at GE Global Research Center and Mark Beckmann, senior manager at Microsoft.
"The emergence of cloud computing, machine learning, and the IoT technologies makes it possible for a machine to function as an agent that is capable of intelligent behaviors, such as automatic fault and failure detection, self-diagnosis and proactive maintenance scheduling," said Wu.
The project, titled "Cloud-Enabled Machines with Data-Driven Intelligence," is set to begin Feb. 1 and will be funded by DMDII for 18 months.
"I cannot overstate how delighted I am about this project," said Terpenny. "This initiative brings together researchers and practitioners from manufacturing and software industries in collaboration with leading university researches. We are quite fortunate, here at Penn State, to have the facilities and equipment that are essential to advancing smart manufacturing technologies and methods."
Terpenny is specifically referring to the Factory for Advanced Manufacturing Education (FAME), which is housed within the IME department. FAME is a 10,000-square-foot integrated high-bay laboratory for teaching and research and is equipped with modern and legacy equipment.
"FAME provides the perfect environment for developments and experimentation for this project and the natural integration of research, teaching and impact with industry," she added.
In order to demonstrate the cloud-based manufacturing systems with data-driven intelligence, both legacy machines and general-purpose computer numeric control machines will be used as test cases.
"The overall goal of this research is to establish a generic framework for real-time process monitoring, diagnosis and prognosis for smart manufacturing using cloud computing and big data analytics," said Wu. "The outcome of this project has the potential to enable manufacturers to implement artificial intelligence into manufacturing machines."
DMDII was launched in 2014 through a collaboration with the U.S. Department of Defense and other partners to transform American manufacturing through digitization of the supply chain. The institute currently has more than 250 partner organizations from industry, academia, government, startups and community groups. DMDII is the first lab of UI LABS and is a member of the Manufacturing USA network.
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