Scott Ferguson

Associate Professor

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  • Engineering Building III (EB3) 3244
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Dr. Ferguson’s long-term goal is to improve system design by exploring how customer needs and preferences impact engineering design decisions. We do this by advancing the state-of-the-art in engineering design theory  and design automation by creating tools and methodologies that help engineers navigate the interdisciplinary challenges associated with designing consumer products and complex systems.

Dr. Ferguson’s research addresses the science of engineering design and is motivated by the challenge that engineers must constantly balance tradeoffs. These tradeoffs result from the organizational, political and human interactions that serve to define the criteria under which the system operates. For any engineering problem, even the most basic decisions require making tradeoffs to maximize the value of the design. Fundamental questions driving this work include:

  1. What is the right mix of products to offer because of variety in customer taste?
  2. What drives customer purchasing / adoption decisions?
  3. What is the relationship between system configuration/architecture and needs and preferences that change over time?
  4. What information is needed to make effective design decisions when considering a market systems context?

Dr. Ferguson and his team draw upon research in design theory, multiobjective / multidisciplinary optimization, customer preference modeling, and complex systems. Currently, the lab pursues five primary research directions:

  1. Designing complex engineered systems capable of reconfigurability, evolvability and resilience
  2. Demand modeling, product platforming, and mass customization
  3. Design of engineered materials
  4. Product sustainability
  5. Improving engineering design education

To learn more about this work, please visit his lab website: System Design Optimization Laboratory.

Dr. Ferguson arrived at NC State in the Fall of 2008 and has taught undergraduate courses in Dynamics (MAE 208), Introduction to Aerospace Engineering (MAE 250), Aerospace Vehicle Performance (MAE 251), Introduction to Space Flight (MAE 453) and Fundamentals of Product Design (MAE 426). He has also created graduate-level classes in Engineering Design Optimization (MAE 531) and the Fundamentals of Product Design is also offered at the graduate level (MAE 526).

 

Education

Ph.D. 2008

Mechanical Engineering

University at Buffalo, State University of New York

M.S. 2004

Mechanical Engineering

University at Buffalo, State University of New York

B.S. 2002

Aerospace Engineering

University at Buffalo, State University of New York

B.S. 2002

Mechanical Engineering

University at Buffalo, State University of New York

Research Description

Dr. Ferguson’s research in the area of engineering design focuses on market-based product design and the design of complex engineered systems. His contributions toward technical feasibility modeling and product line optimization have been adopted by his industrial collaborators and have received interest from market research software companies in this area. Dr. Ferguson’s research has also helped define the area of reconfigurable system design, advanced understanding of how such configuration changes can mitigate unexpected system behavior, and studied how the information presented to designers can facilitate tradeoff decisions in the presence of multiple objectives.

Honors and Awards

  • ASEE New Mechanical Engineering Educator Award, 2015
  • ASME Design Automation Young Investigator Award, 2014
  • NC State Outstanding Teacher Award, 2012
  • National Science Foundation CAREER Award, 2011

Publications

Design for excess capability to handle uncertain product requirements in a developing world setting
Allen, J. D. and Mattson, C. A. and Thacker, K. S. and Ferguson, S. M. (2017), Research in Engineering Design, 28(4), 511-527.
Exploring architecture selection and system evolvability
White, S. and Ferguson, S. (2017), Proceedings of the ASME Design Engineering Technical Conferences, (), .
Exploring how optimal composite design is influenced by model fidelity and multiple objectives
Joglekar, S. and Von Hagel, K. and Pankow, M. and Ferguson, S. (2017), Composite Structures, 160(), 964-975.
A case study of evolvability and excess on the B-52 stratofortress and FA-18 hornet
Long, D. and Ferguson, S. (2017), Proceedings of the ASME Design Engineering Technical Conferences, (), .
Bubble tracking simulations of turbulent two-phase flows
Fang, J. and Bolotnov, I. A. (2016), Asme Fluids Engineering Division Summer Meeting, (), .
Design optimization and analysis of a prescribed vibration system
Malinga, B. and Ferguson, S. M. and Buckner, G. D. (2016), Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 2016, Vol 2b, (), 353-360.
Evaluation of system evolvability based on usable excess
Allen, J. D. and Mattson, C. A. and Ferguson, S. M. (2016), Journal of Mechanical Design (New York, N.Y. : 1990), 138(9), .
Excess identification and mapping in engineered systems
Cansler, E. Z. and White, S. B. and Ferguson, S. M. and Mattson, C. A. (2016), Journal of Mechanical Design (New York, N.Y. : 1990), 138(8), .
Exploring the relationship between excess and system evolutions using a stress-test
Cansler, E. Z. and Ferguson, S. M. and Mattson, C. A. (2016), International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 2015, vol 7, (), .
Modeling noncompensatory choices with a compensatory model for a product design search
Shin, J. and Ferguson, S. (2016), International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 2015, vol 2A, (), .
Performance comparison of a bulk thermoelectric cooler with a hybrid device architecture
Antonik, M. and Ferguson, S. M. and O'Connor, B. T. (2016), International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 2015, vol 2b, (), .
Simulating variability of rework cost and market performance estimates in product redesign
Von Hagel, K. A. and Ferguson, S. M. (2016), International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 2015, vol 2A, (), .
Heat shrink formation of a corrugated thin film thermoelectric generator
Sun, T. L. and Peavey, J. L. and Shelby, M. D. and Ferguson, S. and O'Connor, B. T. (2015), Energy Conversion and Management, 103(), 674-680.
Navigating redesign and market desirability implications when considering increased product variety
Belt, A. and Von Hagel, K. and Ferguson, S. (2015), Journal of Engineering Design, 26(7-9), 236-258.
New perspectives on design automation: Celebrating the 40th anniversary of the ASME design automation conference
Ilies, H. and Parkinson, M. and Seepersad, C. C. and Kokkolaras, M. and Ragsdell, K. and Papalambros, P. and Mistree, F. and Williams, C. and Rai, R. and Panchal, J. and Ferguson, S. and DuPont, B. and Allison, J. (2015), Journal of Mechanical Design (New York, N.Y. : 1990), 137(5), .
Performance analysis of a thermoelectric cooler with a corrugated architecture
Owoyele, O. and Ferguson, S. and O'Connor, B. T. (2015), Applied Energy, 147(), 184-191.
Top down design using Bayesian network classifiers for composite panels
Von Hagel, K. and Joglekar, S. and Ferguson, S. and Pankow, M. (2015), Proceedings of the American Society for Composites: Thirtieth Technical Conference, (), 468-475.
Creating targeted initial populations for genetic product searches in heterogeneous markets
Foster, G. and Turner, C. and Ferguson, S. and Donndelinger, J. (2014), Engineering Optimization, 46(12), 1729-1747.
Effects of feedback on design space exploration
Foster, G. and Denhart, J. and Ferguson, S. (2014), Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 2013, vol 1, (), .
Enhanced targeted initial populations for multiobjective product line optimization
Foster, G. and Ferguson, S. (2014), Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 2013, vol 3A, (), .
Multi-objective design optimization of a variable geometry spray fuel injector
Archer, J. R. and Fang, T. G. and Ferguson, S. and Buckner, G. D. (2014), Journal of Mechanical Design (New York, N.Y. : 1990), 136(4), .
Performance analysis and technical feasibility assessment of a transforming roving-rolling explorer rover for Mars exploration
Edwin, L. E. and Denhart, J. D. and Gemmer, T. R. and Ferguson, S. M. and Mazzoleni, A. P. (2014), Journal of Mechanical Design (New York, N.Y. : 1990), 136(7), .
Using a goal-switching selection operator in multi-objective genetic algorithm optimization problems
Shaefer, D. and Ferguson, S. (2014), Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 2013, vol 3B, (), .
A concept selection framework for early sorting of reconfigurable system designs
Denhart, J. and Gemmer, T. and Ferguson, S. and Mazzoleni, A. (2014), Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 2013, vol 3B, (), .
A model for quantifying system evolvability based on excess and capacity
Tackett, M. W. P. and Mattson, C. A. and Ferguson, S. M. (2014), Journal of Mechanical Design (New York, N.Y. : 1990), 136(5), .
A review of mass customization across marketing, engineering and distribution domains toward development of a process framework
Ferguson, S. M. and Olewnik, A. T. and Cormier, P. (2014), Research in Engineering Design, 25(1), 11-30.
Exploring the effectiveness of using graveyard data when generating design alternatives
Foster, G. and Ferguson, S. (2013), Journal of Computing and Information Science in Engineering, 13(4), .
Assessing the effectiveness of using graveyard data for generating design alternatives
Foster, G. and Ferguson, S. (2012), Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 2011, vol 5, pts A and B, (), 563-576.
Exploring differences in preference heterogeneity representation and their influence in product family design
Sullivan, E. and Ferguson, S. and Donndelinger, J. (2012), Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 2011, vol 5, pts A and B, (), 81-92.
Exploring heterogeneity of customer preference to balance commonality and market coverage
Turner, C. and Ferguson, S. and Donndelinger, J. (2012), Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 2011, vol 5, pts A and B, (), 67-79.
Exploring marketing to engineering information mapping in mass customization: A presentation of ideas, challenges and resulting questions
Ferguson, S. and Olewnik, A. and Cormier, P. (2012), Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 2011, vol 5, pts A and B, (), 609-623.
The creation of design modules for use in engineering design education
Foster, G. and Holland, M. and Ferguson, S. and Deluca, W. (2012), Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, vol 7, (), 23-36.
Development of a changeable airfoil optimization model for use in the multidisciplinary design of unmanned aerial vehicles
Ferguson, S. and Tilstra, A. H. and Seepersad, C. C. and Wood, K. L. (2010), Proceedings of the ASME international design engineering technical conferences and computers and information in engineering conference, vol 5, pts a and b - 35th design automation conference, (), 57-68.
Designing a family of reconfigurable vehicles using multilevel multidisciplinary design optimization
Ferguson, S. and Kasprzak, E. and Lewis, K. (2009), Structural and Multidisciplinary Optimization, 39(2), 171-186.

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Grants

UAS Roadmap
NC Department of Transportation(8/01/17 - 7/31/19)
Powering Energy Efficiency & Impacts Framework: Mapping a comprehensive energy strategy for the Upper Coastal Plain Council of Governments Region
US Dept. of Energy (DOE) - Energy Efficiency & Renewable Energy (EERE)(10/01/16 - 9/30/18)
Workshop: NSF CAREER Writing Workshop for Early Career Professionals; Charlotte, NC; August 23, 2016
National Science Foundation (NSF)(8/01/16 - 7/31/17)
CAD Apps for Core Courses in AE and ME Curricula: Bridge Funding 
The MathWorks, Inc.(1/01/16 - 5/31/17)
Building a Business Case for UAS Use in Public Power Operations
American Public Power Association(12/16/14 - 11/30/16)
Transfer Spike Analysis and Redesign
Neogen(12/02/13 - 3/31/14)
Collaborative Research: Mitigating Emergent System Behavior through System Evolvability
National Science Foundation (NSF)(6/01/13 - 5/31/17)
Transforming Teaching Through Implementing Inquiry (T2I2)
National Science Foundation (NSF)(11/30/-1 - 7/31/16)
Enabling All-Access Mobility for Planetary Exploration Vehicles via Transformative Reconfiguration
National Aeronautics & Space Administration (NASA)(11/30/-1 - 10/31/12)
Transforming Teaching Through Implementing Inquiry (T2I2)
National Science Foundation (NSF)(8/01/11 - 7/31/13)