Scott Ferguson

Associate Professor

Dr. Ferguson and his team explore and advance how engineers design systems, arrive at actionable decisions, and frame problem objectives when faced with unresolvable uncertainties. Recognizing that engineering design is a decision-making process, their research products help engineers navigate the challenges of designing complex engineered systems, especially when there are uncertainties that are known but unquantifiable. The tools/methods that are developed as part of this work advance engineering design automation and design theory.

 

Engineering design requires the incorporation of interdisciplinary perspectives, creating solutions by synthesizing various components, dealing with uncertainty, and considering the unintended consequences of design decisions. Dr. Ferguson’s research is motivated by the fact that even the most basic engineering design decision requires a value analysis. Fundamental questions driving this work include:

  1. What information do product engineers need for making value-driven design decisions in a market-systems context?
  2. How we we maximize the user experience with a product/system?
  3. What is the right mix of products that should be offered?
  4. What is the relationship between system configuration/architecture and needs/preferences that change over time?
  5. How do we effectively manage change after a product/system has been fielded?

 

Dr. Ferguson and his team draw upon research advances in design automation, multiobjective / multidisciplinary optimization, customer preference modeling techniques (such as conjoint analysis and discrete choice theory), data analytics (including AI/ML), product customization, requirements definition, system architecture modeling, and change propagation techniques. Currently, the lab pursues four primary research directions:

  1. Preference/demand modeling, product platforming, and product customization/personalization
  2. Designing complex engineered systems capable of reconfigurability, evolvability and resilience
  3. Inverse engineering design using machine learning and AI
  4. Advancing engineering design education

 

To learn more about this work, please visit his lab website: Systems, Decisions, and Objectives Lab.

 

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), ME Capstone Design (MAE 416), Fundamentals of Product Design (MAE 426), and Introduction to Space Flight (MAE 467). He also teaches graduate sections of Fundamentals of Product Design (MAE 526) and created Engineering Design Optimization (MAE 531).

 

Publications

Deep Neural Networks in Natural Language Processing for Classifying Requirements by Origin and Functionality: An Application of BERT in System Requirements
Mullis, J., Chen, C., Morkos, B., & Ferguson, S. (2024), JOURNAL OF MECHANICAL DESIGN, 146(4). https://doi.org/10.1115/1.4063764
Margins in design - review of related concepts and methods
Brahma, A., Ferguson, S., Eckert, C., & Isaksson, O. (2023, June 21), JOURNAL OF ENGINEERING DESIGN. https://doi.org/10.1080/09544828.2023.2225842
Toward Quantifiable Evidence of Excess' Value Using Personal Gaming Desktops
Long, D., Morkos, B., & Ferguson, S. (2021, March 1), JOURNAL OF MECHANICAL DESIGN, Vol. 143. https://doi.org/10.1115/1.4049520
Assessing Lifecycle Value Using Object-Based Modeling by Incorporating Excess and Changeability
Long, D., & Ferguson, S. (2021), JOURNAL OF MECHANICAL DESIGN, 143(5). https://doi.org/10.1115/1.4048218
Studying Dynamic Change Probabilities and Their Role in Change Propagation
Long, D., & Ferguson, S. (2020), JOURNAL OF MECHANICAL DESIGN, 142(10). https://doi.org/10.1115/1.4046674
The Cost-Sorted Distance Method for Identifying Minima Within Firefly Optimization Results: Application to Engineering Design
Elliott, C. M., Ferguson, S. M., & Buckner, G. D. (2021), JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING, 21(1). https://doi.org/10.1115/1.4047554
Design for the Marketing Mix: The Past, Present, and Future of Market-Driven Engineering Design
Donndelinger, J. A., & Ferguson, S. M. (2020). [Review of , ]. JOURNAL OF MECHANICAL DESIGN, 142(6). https://doi.org/10.1115/1.4045041
Benefits and challenges of using unmanned aerial systems in the monitoring of electrical distribution systems
Long, D., Rehm, P. J., & Ferguson, S. (2018), The Electricity Journal, 31(2), 26–32. https://doi.org/10.1016/J.TEJ.2018.02.004
A case study of evolvability and excess on the B-52 stratofortress and FA-18 hornet
Long, D., & Ferguson, S. (2017), Proceedings of the asme international design engineering technical conferences and computers and information in engineering conference, 2017, vol 4. https://doi.org/10.1115/detc2017-68287
Design for excess capability to handle uncertain product requirements in a developing world setting
Allen, J. D., Mattson, C. A., Thacker, K. S., & Ferguson, S. M. (2017), RESEARCH IN ENGINEERING DESIGN, 28(4), 511–527. https://doi.org/10.1007/s00163-017-0253-8

View all publications via NC State Libraries

Grants

  • Collaborative Research: Research: Investigating Jonassen??????????????????s Design Theory of Problem Solving in Support of Pedagogical Change in Introductory Aerospace Engineering
  • Advancing the Science of Measurement, Process Monitoring and Control for Additive Manufacturing, CAMAL Core Project
  • Assessing Computer Vision Effectiveness by Exploring Training Data Construction and Transfer Learning
  • A Breathable Polymer Film for Use in Virus Transmission Reduction Platforms in Non-hospital Settings
  • Impact Protection Design Solutions Using AI/Neural Networks
  • UAS Roadmap
  • Algorithm optimization and tuning for Under Armour
  • Powering Energy Efficiency & Impacts Framework: Mapping a comprehensive regional energy strategy for Upper Coastal Plain Council of Government Region (PEEIF)
  • Workshop: NSF CAREER Proposal Writing Workshop for Early Career Professionals; Charlotte, NC; August 23, 2016
  • Career: Giving You Almost What You Want - Customizing Products Through The Integration Of Market Modeling And Engineering Design
Scott Ferguson