View Recording of 6th JMD Webinar: Artificial Intelligence in Engineering Design
JMD’s 6th webinar was held on August 1, 2022, 12:00 PM EDT, and included four featured talks by Sayan Ghosh (GE Research), Christopher McComb (Carnegie Mellon University), Kshitij Mall (Purdue University), and Caitlin Mueller (MIT).
Bioinspiration of Product Architecture: Trading-off System Effectiveness for System Robustness
It is often desirable for engineered systems to sustain their functional effectiveness in the event of unforeseen disruptions. In analogy, biological systems are often physiologically adapted to survive both internal and environmental disruptions.
In Memoriam: Douglass J. Wilde (1929-2021)
Douglass J. Wilde, Professor of Engineering Design at Stanford University, was known to many of us for his scientific and engineering contributions, and for his simple and caring attitude towards everyone who encountered him — ‘Doug’ to us all.
Special Issue: Selected Papers for IDETC-CIE 2021 – April 2022
J. Mech. Des. April 2022, Volume 144, Issue 4 RESEARCH PAPERS Design Theory and Methodology So You Think Your System Is Complex?: Why and How Existing Complexity Measures Rarely Agree Anthony Hennig, Taylan G. Topcu, Zoe Szajnfarber J. Mech. Des. April 2022, 144(4): 041401. doi: https://doi.org/10.1115/1.4052701 If a Picture is Worth 1000 Words, Is a Word Worth 1000 Features […]
JMD’s 5th Webinar on Design Engineering in the Age of Industry 4.0
The video recording is now available for JMD’s 5th Webinar on “Design Engineering in the Age of Industry 4.0,” held on May 10, 2022.
Evaluating Quantitative Measures for Assessing Functional Similarity in Engineering Design
activities relevant to several applications, including competitive benchmarking, design-by-analogy, and patent infringement. Specifically, the work focuses on the similarity of functional implementations across products (as opposed to form), using structured functional models that are expressed mathematically.
Special Issue on Artificial Intelligence and Engineering Design – February 2022
J. Mech. Des. February 2022, Volume 144, Issue 2 Guest Editors: James Allison, Yaoyao Fiona Zhao, Christopher McComb, Michel-Alexandre Cardin, Paul Witherell, Yi Ren, Daniel Selva, Conrad Tucker Artificial intelligence (AI) has had a strong presence in engineering design for decades, and while theory, methods, and tools for engineering design have advanced significantly during this time, […]
2021 Reviewer Recognition
The Editorial Board thanks all reviewers for volunteering their expertise and time reviewing manuscripts in 2021 and announces awards for outstanding Reviewers of the Year and Reviewers With Distinction.
Inverse Aerodynamic Design of Gas Turbine Blades using Probabilistic Machine Learning
While designing a blade for an industrial gas turbine (IGT), one needs to consider multiple performance characteristics like aerodynamic efficiency, durability, and safety. The sequential and iterative nature of the process leads to extremely long cycle times and precludes a deeper understanding of the design space.