Secure Cloud Manufacturing
The long-term goal of this research project is to develop methods and techniques to make large-scale manufacturing systems safer, more secure, and more productive, enabling them to produce high-quality products for consumers at modest cost.
This project utilizes a small manufacturing system that consists of three industrial robots, four machine tools, and two conveyors, with an integrated industrial control system (from Rockwell Automation) connected by Ethernet/IP. The testbed is instrumented with presence sensors, inspection cameras, an interactive HMI display, and a computer for synchronization of real-time and historical data to a cloud platform. The research goals around the testbed include: control development and validation, learning control, agent-based control, optimizing scheduling, reconfigurable control, cloud-based manufacturing, security of cyber-physical systems, etc. One key enabler for the research program is having simulation models of the different system components that can be validated off-line, or in a hardware-in-the-loop framework. Another key enabler is the hosting of testbed-generated data in a deployed cloud environment to enable real-time cloud analytics, predictive maintenance, and remote system monitoring.
More Information: 2017-Cloud-Manufacturing
Students who successfully match to this faculty research team will be required to sign the following document in January 2017:
Student IP Agreement for Faculty Research Teams
How to Apply
- Skill level All levels
- Students 8-16
- Likely Majors AERO, CE, CS, ECE, EE, IOE, MATH, ME, MIDAS, PHYSICS, SI, STATS
- Course Substitutions ME 590, MIDAS, ECE Cognate
- IP & NDA Required? Yes
- Summer Opportunity Summer Funding Application
Mechanical Design Integration Subteam (3 Students)
Specific Tasks: mechanical design, prototyping, sensor integration
- Likely Majors: ME, AERO, PHYS
Controls Subteam (3 Students)
Specific Tasks: algorithm development, PLC programming, quality analysis
- Likely Majors: CSE/CS-LSA, CE, ME, EE, ECE
Cloud & Enterprise Subteam (3 Students)
Specific Tasks: cybersecurity implementation, cloud system design, database creation and management
- Likely Majors: CSE/CS-LSA, CE, ECE, Information (SI), MIDAS
Simulation Subteam (3 Students)
Specific Tasks: MATLAB/Arena Simulation, throughput analysis, 3D visualization
- Likely Majors: MATH, ME, IOE, STAT, Information (SI), MIDAS
Apprentice Researcher (4 Students)
Requirements: interest in project material, willingness to develop skills. OPEN TO FRESHMEN AND SOPHOMORES ONLY.
- Likely Majors: ANY
Faculty Sponsor: Dawn M. Tilbury
Associate Dean for Research, College of Engineering
Professor Tilbury received her B.S. degree in Electrical Engineering, summa cum laude, from the University of Minnesota in 1989, and her M.S. and Ph.D. degrees in Electrical Engineering and Computer Sciences from the University of California, Berkeley, in 1992 and 1994, respectively. In 1995, she joined the Mechanical Engineering Department at the University of Michigan, Ann Arbor, where she is currently Professor, with a joint appointment as Professor of EECS. Her research interests include distributed control of mechanical systems with network communication, logic control of manufacturing systems, reliability of ground robotics, and dynamic systems modeling of physiological systems. She was elected Fellow of the IEEE in 2008 and Fellow of the ASME in 2012, and is a Life Member of SWE.
Faculty Sponsor: Kira Barton
Assistant Professor of Mechanical Engineering
Professor Barton (firstname.lastname@example.org) received her B.S. degree in Mechanical Engineering from the University of Colorado at Boulder in 2001. Barton continued her education in mechanical engineering at the University of Illinois at Urbana-Champaign and completed her M.S. and Ph.D. degrees in 2006 and 2010, respectively. She held a postdoctoral research position at the University of Illinois from Fall 2010 until Fall 2011, at which point she joined the Mechanical Engineering Department at the University of Michigan at Ann Arbor.
Her primary research focus is on precision coordination and motion control for emerging applications, with a specialization in iterative learning control. Barton’s work intersects controls and manufacturing and combines innovative manufacturing processes with enhanced engineering capabilities. The potential impact of this research ranges from building high-resolution DNA sensors for biological applications, to the integration of advanced sensing and control for rehabilitation robotics.
Faculty Sponsor: Morely Mao
Professor of EECS
Professor Mao’s current research focus encompasses software-defined networking, internet security, next-generation internet protocols, and mobile systems. She is a recipient of the Sloan Fellowship, the NSF CAREER Award, the ARMY YIP Award, and an IBM Faculty Award. Her other honors include the Morris Wellman Faculty Development Professor and EECS Achievement Award at University of Michigan. She has participated and played leadership roles in several large joint research efforts with funding from government as well as industry, including those involving researchers at AT&T, IBM, and at other universities. Her group has successfully developed several important prototypes based on the research work. Many such prototypes have been converted into commercial products through close collaboration with researchers in industry such as AT&T, Google, and Docomo. In addition, software prototypes such as MobiPerf and Powertutor focused on mobile platform characterization have been open-sourced and widely used by researchers in academia and industry.