Special Section on Designing for Additive Manufacturing Now Available Online in October 2017 Issue
Call For Papers: Special Issue on Design of Engineered Materials and Structures
JMD Welcomes Mohsen Kolivand, Mian Li, and Paul Witherell to the Editorial Board
JMD Announces Editors' Choice Paper Awards for the years: 2014, 2015, and 2016
Automatic Enumeration of Feasible Kinematic Diagrams for Split Hybrid Configurations With a Single Planetary Gear
Tounadher Barhoumi, Dongsuk Kum
Power-split hybrid electric vehicles embody two electric machines in addition to the internal combustion engine, and it employs one or more planetary gear sets (PG) while disposing of the transmission. Most of the prior studies on the design of power-split hybrids focused on finding optimal powertrain configurations, which are configurations specifying the components connections. However, a selected powertrain configuration cannot be physically realized as it does not specify the components arrangements in three dimensional space. Read more...
Cyber-Empathic Design: A Data-Driven Framework for Product Design
Dipanjan Ghosh, Andrew Olewnik, Kemper Lewis, Junghan Kim, and Arun Lakshmanan
Understanding consumer perceptions of products and the potential impact of those perceptions on purchase decisions is critical information that should influence product development decisions. Though firms often seek consumer feedback on products, such feedback often occurs long after product use and lacks specific details about the interaction, usage context, etc. This work introduces a novel framework – Cyber-Empathic Design – that integrates sensor data and real-time user feedback to develop a more accurate model of user perceptions. Read more...
Mining Process Heuristics from Designer Action Data via Hidden Markov Models
Christopher McComb, Jonathan Cagan, and Kenneth Kotovsky
Configuration design problems are common in everyday life as well as engineering, with examples ranging from the selection and arrangement of furniture for a living room to the type of problem-solving used by NASA engineers to return Apollo 13 safely to Earth. There are many theoretical approaches for solving configuration design problems but few studies have examined how humans naturally solve them. This work used data-mining techniques (specifically hidden Markov models) to study the behavioral patterns shown by humans solving two distinct configuration design problems. Read more...
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