Advanced Manufacturing 

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Novel hybrid feed drive built at S2A lab achieves superior positioning speeds and precision with 80% less energy.
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This project is sponsored by the National Science Foundation's CAREER Award # 1350202

Dynamically Adaptive Feed Drives for High Performance and Energy Efficient Manufacturing

Linear motors are used for fast and accurate motion delivery in a wide range of precision manufacturing machines. They however consume a lot of energy and generate a lot of heat in the process. In this project, we explore a mechatronic design concept where the electro-mechanical structure of linear motor driven machines is designed much like the power train of hybrid electric vehicles; i.e., their structure is designed to intelligently vary in real-time as a function of the manufacturing operation being performed, so as to simultaneously  achieve high performance and improved energy efficiency. 

Low-cost and Energy-efficient Reduction of Vibrations in Ultra-precision Manufacturing Machines 

Ultra-precision manufacturing (UPM) machines (e.g. ultra-precision machine tools, wafer scanners and micro CMMs) are designed to fabricate and measure complex parts having micrometer-level features and nanometer-level surface finishes. They are often plagued by a combination of ground vibrations and residual vibrations which occur while executing motion commands. We are carrying out a model-based study of the dynamics of passively isolated UPM machines to determine ways of reducing vibrations via design-level mechatronic optimization – without resorting to active vibration control – thus reducing costs and energy consumption
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Mori Seiki's NN 1000 ultra precision 5-axis machine tool used for demonstrating earlier research results
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This project is sponsored by the National Science Foundation's Grant # 1232915
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Novel stage designed at S2A-lab for vibration assisted nanopositioning research
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This project is sponsored by the National Science Foundation's Grant # 1562297

Enabling Low-cost, High-throughput Nanomanufacturing via Vibration Assisted Nanopositioning

Nanopositioners are mechanical devices used for precise positioning in a wide range of nanotech processes. This project investigates vibration assisted nanopositioning: a novel approach for applying high frequency vibration, combined with active vibration control, to nanopositioning stages. It holds promise to mitigate friction in roller bearing nanopositioning stages, thus improving their positioning speed and precision without significantly increasing their cost.

Knowledge-based Motion Command Generation for
​High-Speed High-Precision Manufacturing Machines​

Speed, accuracy and motion smoothness are conflicting requirements that must be fulfilled by today's high-speed high-precision manufacturing machines. Achieving these requirements optimally requires a shift from the current skill-based (trial and error) methods for command generation to a knowledge-based approach. We are investigating ways of improving the performance of advanced manufacturing machines by incorporating model-based knowledge into the motion commands they are required to execute 
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Photo courtesy of www.proto3000.com

Intelligent 3D Printers for Next Generation Manufacturing

This pilot project seeks to develop intelligent 3D printers that enable more flexibility and ease in printing of personalized products by unskilled users

Automotive

Enabling Performance and Fuel Efficiency Improvements in Vehicles by Developing Dynamic Models for Electric Power Assist Steering Systems

Electric power assist steering (EPAS) systems deliver improved fuel efficiency and flexibility to modern-day automobiles. However, they are plagued by a so-called "sticky feel" which adversely affects their performance. This project, funded by Ford Motor Company, seeks to develop dynamic models that provide insights on how to design and control EPAS to minimize the sticky feel thus enhancing the performance and wide-spread use of EPAS.

Enabling Improvements in Fuel Efficiency via Modeling and Design Optimization of GDI Actuators

The objective of this project is to improve fuel injector performance in Gasoline Direct Injection (GDI) engines via multi-physics modeling that encompasses electro-magnetics, collision dynamics, and fluid dynamics. Compared to the traditional port fuel injection systems in IC engines, GDI provides major advantages such as increased fuel efficiency, higher power output, and lower emission levels. This project is funded by the Ford Motor Company and MCubed 2.0. It is performed in collaboration with the Precision Systems Design Lab
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GDI Photo courtesy of www.motivemagazine.com
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Photo Courtesy of www.gearheads.org

Steering Systems for Next-generation Automobiles

This pilot project seeks to develop effective, reliable and safe steering systems for next-generation semi-autonomous and fully autonomous vehicles.

Low-Resource Settings

Pathways to Sustainable Manufacturing in
​Less Developed Countries

This pilot project explores a multi-disciplinary approach to foster economically, environmentally and socially sound manufacturing in less developed countries.
This project is partly sponsored by Procter and Gamble through MCubed Diamond