The Center for Materials Property Data (CMPD) is a multi-university effort with industry that generates and collects transient materials property data for manufacturing process models and materials behavior discovery. These data are vital to the accuracy of the models and can significantly reduce the high costs and time spent on trial-and-error methods that have been used for years.
The center was established by three academic institutions, Worcester Polytechnic Institute, University of Connecticut, and the University at Buffalo, in cooperation with ASM International. Each academic partner brings unique scientific expertise to the program while ASM International serves as the materials data archive, enabling easy access to data by industry members and non-members.
CMPD is a collaborative, member-driven center. Portfolio projects are proposed by member companies and carried out by the academic members. Member companies help govern the center, have unrestricted access to data, select and share management of data generation projects, and benefit from shared expertise.
CMPD also has access to UConn Tech Park’s state-of-the-art equipment, a tremendous resource for collecting dynamic materials property data. More sophisticated equipment means better data; better data means more reliable models and better predictions of material behavior during processing.
The CMPD approach is becoming a more common trend in industry, with a shift away from the trial-and-error approach for process development and a desire to be able to model and predict materials behaviors.
Executive Director of UConn Tech Park Pamir Alpay is confident the program will continue to thrive and advance the university as a leader in innovation for manufacturing research and materials engineering. “CMPD is a massive project and plays a significant role in everything we’re doing at Tech Park on manufacturing technologies,” he says. “It’s a huge effort that serves a large community and it is making a big impact.”
For more information on CMPD, visit https://cmpd.asminternational.org/home.
The COVID-19 pandemic has affected manufacturers in every sector. In the face of disruptions to production and supply chains, disproportionate decreases in product demand and many other challenges, manufacturers are taking a close look at strategies that will help them be better prepared for future pandemics or other disasters. How will they protect their core businesses and keep their companies afloat?
Connecticut Manufacturing Resource Center (CMRC) at Tech Park is working with small- and medium-size manufacturers to develop long term solutions to this critical issue.
Using funds from a recently awarded $300K EDA CARES Act grant, CMRC is proactively helping companies establish contingency plans for effectively maintaining operations from an off-site location during a crisis. Participating companies receive access to product lifecycle digital technologies that establish a kind of smart backup at Tech Park, a digital twin of a company’s operations that helps ensure minimal disruption.
Joe Luciani, Director of the Proof of Concept Center (POCC) at Tech Park, helps manage the grant. He believes that this vital support is coming at a crucial time, stressing that “The pandemic has severely impacted these companies and they are eager to put safeguards in place.” Hadi Bozorgmanesh, PI for the grant and Director of CMRC, adds with conviction, “Our manufacturing sector is a major source of economic strength for Connecticut and we need to help these organizations find long term solutions as they start to recover from the crisis.”
CMRC is already seeing success. Sunil Agrawal, Vice President of R&D Dynamics Corporation, a manufacturing company in Bloomfield, CT, recently completed the program. He contacted Hadi with gratitude and praise for UConn’s outstanding dedication and support throughout the project. He affirmed his organization’s commitment to implement the recommended changes, and his conviction that “The result will be a company that is not only more efficient and capable, but more resilient in a crisis like the one brought on by the events of the last twelve months.”
The Enterprise Solution Center (ESC) at UConn Tech Park comprises four research centers: Quiet Corner Innovation Cluster (QCIC), Proof of Concept Center (POCC), Connecticut Manufacturing Simulation Center (CMSC), and Connecticut Manufacturing Resource Center (CMRC).
ESC takes an integrated approach to co-development of technology products and services to support the competitiveness of small and medium manufacturers.
Anna Tarakanova, Assistant Professor in Mechanical Engineering and Biomedical Engineering at UConn, studies ways that the structural features of complex networks like extracellular matrices (ECM) support their function. To explore this further, she decided to find a way to recreate her ECM micro-structure data into enlarged physical models that are visible to the naked eye.
She approached Joe Luciani, Director of the Proof of Concept Center (POCC), an experienced innovator at Tech Park. His extensive collaborative experience with faculty, students and companies of all sizes paired with his expertise utilizing POCC’s state-of-the-art prototyping and fabrication equipment was well aligned with Anna’s research goals.
To kick off the project, Anna provided her structural data set as a shareable source. Joe converted the file using 3D modeling software, Rhinoceros3D, with a visual programming plugin, Grasshopper3D, that crunched the data to produce a network of nodes and linkages – i.e., a 3D model. Joe used this 3D model to successfully print larger-than-life ECM samples in POCC’s Stratasys 3D printers. He also recorded the printing process by programming one of the center’s robots to hold a camera and move through a few waypoints.
Anna provides some additional insight into her research. She explains, “Our research is focused on understanding the structure-function connectivity of complex heterogeneous systems like extracellular matrix (ECM) networks [the printed specimen] by establishing a microstructure-resolved deep learning framework that couples imaging data of matrix microstructure with multiscale computational modeling from the nanoscale, 3D printed prototyping, and in vitro mechanical testing of tissue specimens.”
The project is a new collaboration between Professor Tarakanova, Hongyi Xu, Assistant Professor in Mechanical Engineering at UConn, and David M. Pierce, Associate Professor in Mechanical Engineering and Biomedical Engineering at UConn.
“This is an exciting new line of convergent research that utilizes heterogeneous 2D experimental microscopic imaging data to stochastically reconstruct realistic 3D matrix structures through a statistically-driven, generative deep learning approach for a representative model system: healthy and osteoarthritic articular cartilage, ” says Pierce.