SiDi Uses 3D Printer to Produce Protective Masks for Rehab Clinic

We recently joined a design team led by engineering professors Raj Rao, Wenchao Zhou and Zhenghui Sha at the University of Arkansas to use 3D printers to produce protective masks in response to the COVID-19 crisis. The team printed and delivered 50 protective masks to be used by a Northwest Arkansas rehabilitation clinic. The Ph.D. student Laxmi Poudel from SiDi Lab participated in this initiative and helped print about 35 masks. Prof. Zhou has produced two short videos, one showing how the masks are made and another showing clinicians how to assemble the masks. See the full story covered by UARK NEWS.

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SiDi Receives Grant from the National Science Foundation to Conduct Collaborative Research

The University of Arkansas, Northwestern University and Ford Motor Company will form a joint force to conduct collaborative research on customer preferences modeling in product design and development. The objective is to investigate what product customers consider and what they eventually purchase using a hierarchical, multidimensional network-based design approach. Motivated by the need to model socio-technical interactions in engineering design, this research combines design theory with network science to explore three interrelated topics: 1) two-stage multidimensional network models for customer preference modeling that consider product associations and social influence; 2) dynamic network models for predicting the impact of multi-competitor strategic decisions, and 3) knowledge transfer to demonstrate generalizability and creation of shared data resources to benefit research community. See the NSF website for more details about this project.

Collaborative Work Published by Journal of Mechanical Design

Our paper titled “Data-Driven Dynamic Network Modeling for Analyzing the Evolution of Product Competitions”, is recently accepted by the Journal of Mechanical Design, Transactions of the ASME. In this paper, we proposed a dynamic network-based approach to modeling the evolution of product competitions using multi-year buyer survey data based on Separate Temporal Exponential Random Graph Model. Our approach provides a pathway to gain insights into why a product maintains or loses its competitiveness over time. This study was performed in collaboration with Dr. Jian Xie from Beijing Institute of Technology and Dr. Wei Chen’s research group from Northwestern University. Congratulations.

SiDi Lab Organized “Solarized UARK Campus” Design Contest

In Fall 2109, SiDi Lab successfully organized the first design contest at the University of Arkansas campus on the topic of solar energy systems design. The motivation of this design contest is to prepare next-generation engineers to be skillful system designers and system thinkers. The contest relies on a computer-aided design (CAD) based framework to cultivate knowledge in the field of solar energy and the capability of synthesizing knowledge from different disciplines. This year, the participants were asked to engage in an authentic solar energy systems design for an on-campus architecture – Pomfret Hall on Stadium Drive. See more detail about this design contest here.

There were a total of 42 participants including undergrad students, graduate students and staff members. 35 participants successfully submitted their design solutions before the deadline. The top three winners were awarded during the awarding ceremony and two participants were recognized with special awards due to their significant time commitment in the design contest. This design contest sets forth a workable mechanism on how engineering education and design research can be synergistically integrated. SiDi Lab is looking forward to scale up the context in 2020 by collaborating industry partners, particularly local electric utility companies, such as Ozarks Electric Cooperative and Southwest Electric Cooperative.

$2.2M NSF Grant Received to Facilitate the Future of Design at Human-Technology Frontier

In this project, the University of Arkansas, the University of Illinois at Urbana-Champaign, Oregon State University, and the Concord Consortium will collaborate to define, implement, and disseminate generative design tools and projects for use in undergraduate courses. Research questions from three perspectives will drive the project: 1) Theoretical perspective: What are the essential elements of generative design thinking that students must acquire so they can work effectively at the human-technology frontier in engineering? 2) Practical perspective: To what extent and in what ways can the curriculum and materials support the learning of generative design as indicated by students’ gains in generative design thinking? and 3) Affective perspective: To what extent and in what ways can artificial intelligence affect the professional formation of engineers as indicated by the changes of students’ interest and self-efficacy in engineering? This project represents a novel application of artificial intelligence to engineering that could augment the creativity and productivity of the engineering workforce of the future. See the NSF website for more details about this project.

Welcome New PhD Students

This fall, two new PhD students working as Graduate Research Assistants joined in SiDi Lab: 1. Xingang Li graduated from Tianjin University, China with a BS degree in Mechanical Engineering. Prior to joining in the PhD program, Xingang worked in auto industry at OTICS Corporation in Japan for four years. He has practical working experience in design of automotive engine parts for major car manufacturers, such as Toyota and SAIC Motor Co., Ltd. 2. Yinshuang Xiao, who holds BS and MS in Mechanical Engineering, graduated from University of Electronic Science and Technology of China. Prior to joining in SiDi Lab, she was working as a R&D Engineer for new energy vehicles at SAIC Volkswagen in Shanghai. Yinshuang has extensive research experience in computational electromagnetic and EMC characteristics of EV component. Welcome on Board!

Our paper earned the Robert E. Fulton Best Paper Award

Our paper titled “A Deep Learning Based Approach to Predicting Sequential Design Decisions” was recently selected as the awardee of the Robert E. Fulton Best Paper Award from the Computers & Information in Engineering (CIE) Division of the ASME. Molla H. Rahman, the PhD student from SiDi Lab and the first author of this paper, presented the work at the 39th ASME CIE Conference in Anaheim, California, August 20. Please see more information here.

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