2021 Analysis of State Innovation
Which States are More Likely to Embrace and Adopt Smart Manufacturing? This is a very nice review, done by WalletHub, of a number of dimensions that may offer a good indication. Other great data in this article as well – Breakdown of Global Funding and a Global...
Strategy and Execution in Smart Manufacturing Must Meet in Middle – Gartner
A great blog post from Simon Jacobson of Gartner. The top three disconnects between C-Level and Non-C-Level in management, with respect to Smart Manufacturing are in Access to Skills, Solution Scalability and Investment Justification. Those are exactly the...
Energy Efficient Material Processing Through Automated Process Monitoring and Controls
PROJECT LEAD: Virginia Tech PARTNERS: University of Virginia, Pennsylvania State University, Arconic, Commonwealth Center for Advanced Manufacturing PROBLEM STATEMENT: Wireless sensor nodes impacted by electromagnetic, vibration, and thermal noise High volume of data...
Smart Manufacturing of Cement
PROJECT LEAD: University of Louisville PARTNERS: Argos PROBLEM STATEMENT: Cement manufacturing is energy-intensive (5GJ/t) and comprises a significant portion of the energy footprint of the composite material. Incorporating modern monitoring, simulation and control...
Production of Zero Defect (ZD) Slabs in Steel Continuous Casting
PROJECT LEAD: ArcelorMittal PARTNERS: Purdue University, Missouri University of Science & Technology, Rensselaer Polytechnic Institute PROBLEM STATEMENT: Absence of predictive maintenance and real-time quality prediction tools increases the overall energy...
Factory 4.0 Educational Toolkit
PROJECT LEAD: Pennsylvania State University PARTNERS: Massachusetts Institute of Technology, Arconic PROBLEM STATEMENT: Rapid pace of technology development has left educational systems scrambling to keep pace and adapt learning outcomes, resulting in inadequate...
Energy Management Systems for Subtractive and Additive Precision Manufacturing
PROJECT LEAD: University of Connecticut PARTNERS: Johnson & Johnson, United Technologies Research Center, Connecticut Center for Advanced Technology PROBLEM STATEMENT: Coordinated utilization of systems engineering, modeling, advanced controls, and data analytics...
Inferential Modeling for Driving Out Energy Waste
PROJECT LEAD: ThinkIQ PARTNERS: General Mills PROBLEM STATEMENT: Energy loses are largely invisible on the manufacturing floor. Wasted energy typically goes unnoticed for long periods of time. And it has proven difficult for manufacturers to determine when and where...