I am pleased to announce that the winner for the 2018 Editors' Choice Paper Award is: Zefang Shen, Gary Allison, and Lei Cui, An Integrated Type and Dimensional Synthesis Method to Design One Degree-of-Freedom Planar Linkages With Only Revolute Joints for Exoskeletons, J. Mech. Des., 140(9):092302-092302-12. The selection of this paper was based on the recommendations of the Associate and Guest Editors and guided by the following criteria (i) fundamental value of the contribution, (ii) expectation of archival value (e.g., expected number of citations), (iii) practical relevance to mechanical design, and (iv) quality of presentation. Plaques were awarded to the authors during the ASME 2019 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference (IDETC/CIE 2019) in Anaheim, California. I would like to congratulate the award recipients and look forward to continuing to work with the entire ASME community of editors, authors, reviewers, and staff to bring JMD to the next level of excellence.
It is my great pleasure to announce the recipients of two categories of 2018 Journal of Mechanical Design (JMD) reviewer awards. Serving as a reviewer for the journal is a critical service necessary to maintain the high quality of our publication and to provide authors with valuable peer review of their work. Together with the Editorial Board of the Journal of Mechanical Design, I would like to recognize the outstanding service of JMD reviewers in the following two categories.
2018 ASME “Reviewers of the Year” Award
The ASME Reviewers of the Year Award is given to reviewers who have made an outstanding contribution to the journal in terms of the quantity, quality, and turnaround time of reviews completed during the past year. The prize includes a wall plaque, 50 free downloads from the ASME Digital Collection, and a one-year free subscription to the journal. Winners are announced in the journal, posted on the ASME website and on the JMD companion website (http://www.asmejmd.org/). The 2018 winners of this award are:
2018 JMD “Reviewers with Distinction” Award
This JMD Reviewers with Distinction Award is given to reviewers who have made a meritorious contribution to the journal in terms of the number, quality, and turnaround time of reviews completed during the past year. The prize includes the choice of either a wall plaque or pdf award certificate. Winners are announced in the journal, posted on the ASME website and on the JMD companion website (http://www.asmejmd.org/). The 2018 winners of this award are:
I would like to congratulate all the award recipients and look forward to continuing to work with the entire ASME community of editors, authors, reviewers, and staff to bring JMD to the next level of excellence.
I am pleased to announce the inaugural special issue (Parts I and II) of the selected papers from the ASME International Design Engineering Technical Conferences (IDETC) 2018, Quebec City, QC, Canada, Aug. 26–29, 2018. This special issue has been organized for the purpose of expediting the process of converting high quality ASME sponsored conference papers into submissions to the ASME Journal of Mechanical Design (JMD). The submission was by invitation only, based on the recommendations from the respective IDETC conference organizers.
This year, the recommended list of papers from conference organizers represents roughly 15% of the IDETC papers from four conferences: (1) Design Automation, (2) Design Education, (3) Design for Manufacturing and the Life Cycle, and (4) Design Theory and Methodology. Power Transmission and Gearing Conference (PTGC) is held biannually, and there was no PTGC this year. Thanks to the hard work of the editorial board and the reviewers, the invited papers underwent an expedited review process which produced a good amount of high-quality papers for the special issue to be published in two parts: Part I in February 2019 and Part II in March 2019.
In the past, it often took too long to reference the JMD version of an IDETC paper, which has a negative impact on the knowledge exchange in the field as well as the journal impact factor. I am pleased that with the special issue initiative this year, we have finished the review of invited IDETC papers within three months of the IDETC conferences. These accepted papers represent the state-of-the-art engineering design research in their respective topic areas, and they are made available online immediately after the final acceptance. I would also like to note that even if a paper is not among the recommended list from conference organizers, we continue to encourage authors to submit their work to the regular JMD issues whenever they feel ready. Please note that the IDETC conference paper copyright does not prevent authors from sending the same paper to the ASME Journal of Mechanical Design.
The success of JMD is based on the scholarly contributions of authors, dedicated reviewers, staff members supporting the journal, and our board of Associate Editors who are leaders in their respective technical areas. Special thanks go to the following Associate Editors who played the critical role of coordinating the reviews of papers in this special issue: James Allison, Xiaoping Du, Scott Ferguson, Katja Holtta-Otto, Harrison Kim, Nam H. Kim, Gul E. Okudan Kremer, Mian Li, Christopher Mattson, Scarlett Miller, Samy Missoum, Tahira Reid, Carolyn Seepersad, G. Gary Wang, and Paul Witherell.
As we learn from running this IDETC special issue for the first time in JMD, I look forward to hear feedback from the community and will work toward running the special IDETC issue again next year.
Copyright © 2019 by ASME
By Wei Chen, Technical Editor, Journal of Mechanical Design
Starting with papers published in 2014, and continuing with papers published in 2015, and 2016, for the last three years the Journal of Mechanical Design (JMD) has awarded an annual Editors’ Choice Paper Award. As stated in Shapour Azarm’s 2014 Editorial, the selection criteria for the award include (i) fundamental value of the contribution, (ii) expectation of archival value (e.g., expected number of citations), (iii) practical relevance to mechanical design, and (iv) quality of presentation.
For the 2017 Editors’ Choice Award selection, after compiling a list of high quality papers (all published in 2017) nominated by the Associate Editors (AEs) and Guest Editors, I formed a three-member ad-hoc committee representing different topic areas of JMD. In addition to the nominated papers, I asked the committee to consider papers that were chosen as 2017 Featured Articles (posted on www.asmejmd.org). After carefully considering all of these papers, I am pleased to announce that the committee’s final selections for the 2017 Editors' Choice Paper Award and three Honorable Mentions are:
2017 Editors' Choice Paper Award:
Joran Booth, Jeffrey Alperovich, Pratik Chawla, Jiayan Ma, Tahira Reid, and Karthik Ramani, “The Design for Additive Manufacturing Worksheet,” J. Mech. Des., 139(10):100904-100904-9 (2017).
2017 Editors’ Choice Paper Award Honorable Mentions (in no specific order):
Dipanjan Ghosh, Andrew Olewnik, Kemper Lewis, Junghan Kim, and Arun Laksmanan, “Cyber-Empathic Design: A Data-Driven Framework For Product Design,” J. Mech. Des., 139(9):091401-091401-12 (2017).
Toumadher Barhoumi and Dongsuk Kum, “Automatic Enumeration of Feasible Kinematic Diagrams for Split Hybrid Configurations With a Single Planetary Gear,” J. Mech. Des., 139(8):083301-083301-11 (2017).
Yong Hoon Lee, Jonathon Schuh, Randy Ewoldt, and James Allison, “Enhancing Full-Film Lubrication Performance Via Arbitrary Surface Texture Design,” J. Mech. Des., 139(5):053401-053401-13 (2017).
The authors of the Editors’ Choice Paper Award were presented with plaques during the August 2018 IDETC meetings in Quebec City. Authors of the honorably mentioned papers were awarded certificates.
Please join me in congratulating the authors of these four papers for their excellent work. I also would like to express my appreciation for all of the current and former AEs and GEs who participated in the nomination of the papers. In particular, I want to thank the ad hoc selection committee for their careful selection of the final awards. We look forward to more high quality publications in JMD.
All four papers are accessible for free viewing on ASME's Digital Collection homepage (https://asmedigitalcollection.asme.org/)
Raymundo Arroyave, James Guest, Carolyn Conner Seepersad, Andres Tovar and Yan Wang
J. Mech. Des 140(11), 110301; doi: 10.1115/1.4041254
The design of engineered materials and structures is a growing and increasingly impactful field of research that intersects materials science, engineering design, engineering mechanics, manufacturing, and data science. The overarching goal is to accelerate the discovery of new materials for engineering applications. The approach compliments a traditionally empirical, trial-and-error approach to materials discovery with an inverse, requirements-driven approach that strategically leverages material databases, simulations, and engineering design algorithms and methods to synthesize new materials and structures.
The inherently interdisciplinary nature of materials design makes it not only challenging but also intriguing to growing cadres of design engineers and materials scientists who are driven by the opportunity to explore new material systems that meet increasingly ambitious performance goals. This type of design exploration requires new design frameworks and tools that can search high-dimensional, multiscale design spaces from a practical perspective, such that the resulting materials can be fabricated with existing and emerging manufacturing processes. Ongoing work in materials discovery and computational materials engineering is essential for enabling materials design research, but this work must be accompanied by design frameworks for solving the inverse problems that are inherent to the field. Arroyave, Shields, Chang, Fowler, Malak, and Allaire highlight many of these challenges as articulated by participants in a workshop on interdisciplinary research on designing engineering material systems. They describe not only some of the conceptual barriers between the materials and engineering design research communities but also the open research questions motivated by challenges in the field.
One of the challenges facing the materials design research community is representing and reconstructing microstructures in a way that is conducive to design exploration and optimization. Yang, Li, Brinson, Choudhary, Chen, and Agrawal apply deep adversarial learning approaches for representing microstructure with low-dimensional latent variables that form the basis for more efficient and more accurate design exploration than competing approaches. Ghumman, Iyer, Dulal, Munshi, Wang, Chien, Balasubramanian, and Chen utilize a spectral density function methodology for representing and reconstructing microstructures for simulation-based design of organic photovoltaic cells. Yang, Xu, Chuang, and Zhan introduce a structural equation modeling-based strategy for reducing the dimensionality of the design space for optimizing multilayer composites. Finally, Acar merges microstructural design with reliability-based design optimization to consider the impact of microstructural uncertainties on material properties.
A related challenge is the optimization of material topology with research efforts now spanning macrostructural and microstructural scales. Many of these research efforts also address the challenge of designing the topology of structures and their constituent micro- or mesostructures concurrently. Du, Zhou, Picelli, and Kim address the challenge of topology optimization of architected materials with spatial variations in structure by introducing a connectivity index that leads to well-connected spatial variations in unit cells throughout a component. Smyl also focuses on spatial variations by introducing an inverse method for optimizing spatially varying elastic material properties in structural domains subject to multiple target displacements and loading conditions. Liu, Detwiler, and Tovar describe clustering techniques for improving the efficiency of cellular materials design for crashworthiness, which is an inherently nonlinear problem. Kazemi, Vaziri, and Norato introduce a topology optimization approach, based on an extension of the geometric projection method, for structures composed of discrete components and multiple materials. Zhang, Liu, Du, Zhu, and Guo introduce a moving morphable component approach for the topology optimization of rib-stiffened structures.
A rapidly growing subfield of materials design is the design of metamaterials, which gain their unique properties from the arrangement of material rather than the composition of the underlying material itself. Delissen, Radaelli, Shaw, Hopkins, and Herder design isotropic metamaterials with constant stiffness and zero Poisson's ratio over large deformations and demonstrate their properties with an additively manufactured prototype. Park and Rosen focus on designing and modeling the behavior of additively manufactured lattice structures more accurately by incorporating geometric approximation errors and joint stiffening into homogenized models of their mechanical properties. Wang, Arabnejad, Tanzer, and Pasiniutilize homogenized lattice properties and topology optimization for the design of a microarchitected hip implant, mitigating peri-implant bone resorption resulting from stress shielding. Petrovic, Nomura, Yamada, Izui, and Nishiwaki introduce an optimization strategy for tailoring orthotropic material orientation for enhanced heat dissipation. Hau, York, Rizzello, and Seelecke establish a model-based strategy for scaling the geometry of dielectric elastomer membrane actuators for mechatronics applications. Ortiz, Zhang, and McAdams introduce a new topology for aluminum foams inspired by the architecture of the pomelo peel and demonstrate its superior impact resistance and damping behavior. In an application very similar to metamaterials, functionally graded materials are designed by spatially arranging multiple material phases to achieve unique combinations of properties; those arrangements are typically enabled by additive manufacturing. Kirk, Galvan, Malak, and Arroyave introduce a methodology for planning the path of a functionally graded material from one material phase to another while avoiding undesirable intermediate phases.
Finally, several researchers are establishing multiscale, multidisciplinary design exploration and optimization approaches that are particularly appropriate for materials design applications. Morris, Bekker, Haberman, and Seepersad leverage Bayesian network classifiers for efficient multilevel design exploration of metamaterials and utilize the classifiers for rapid evaluation of manufacturability. Ghoreishi, Mokeri, Srivastava, Arroyave, and Allaire establish a framework for the fusion of information from multiple computational and experimental sources by exploiting correlations among them and by sequentially querying them via a value-gradient policy. Finally, Nellippallil, Rangaraj, Gautham, Singh, Allen, and Mistree establish an inverse method for design exploration of process–structure–property–performance spaces that are encountered frequently in materials design.
The papers in this special issue range from microstructural design to metamaterials design to topology optimization to multilevel design exploration. As such, they are representative of the wide variety of emerging research at the intersection of materials and engineering design. It is our hope that the contents of this special issue will continue to stimulate new advances in the design of engineering materials.
Copyright © 2018 by ASME
[+] Author and Article Information
J. Mech. Des 140(1), 010201; doi: 10.1115/1.4038545
As I begin my term (January 2018 to December 2022), as Technical Editor for the Journal of Mechanical Design (JMD), I would like to wish a Happy New Year to all of the journal stakeholders: readers, authors, reviewers, Associate Editors, Guest Editors, and staff. I feel deeply honored and privileged to be appointed by the ASME Executive Committee of the Design Engineering Division (DED) and the Technical Committee on Publications and Communications (TCPC) to serve as the new Technical Editor of JMD. I feel especially honored to assume this role because I have always looked up to the past three Editors, Professors Michael McCarthy (University of California, Irvine, CA, 2003–2007), Panos Papalambros (University of Michigan, 2008–2012), and Shapour Azarm (University of Maryland, 2013–2017), as technical leaders and as role models in the field. Their dedication and leadership have led to the success of JMD, which is viewed as one of the few top journals world-wide in the area of design engineering. I am excited to follow their path, but also challenged to bring the journal to the next level of excellence.
Journal of Mechanical Design serves the broad design community as the venue for scholarly, archival research in all aspects of the engineering design activity and welcomes contributions from all areas of design with an emphasis on synthesis. Example categories of topics include, but are not limited to: (1) design automation, (2) design theory and methodology, (3) design education, (4) design for manufacturing and the life cycle, (5) design of direct contact systems, including cams, gears, and power transmission, (6) design of mechanisms and robotic systems, (7) design of energy, fluid, and power handling systems, and (8) design innovation and devices. The connecting thread among these topics is the emphasis on design, rather than just analysis.
During the past few years, JMD's impact factor has continuously improved, rising to 2.565 in year 2016, and is rated by ISI to be in the top quartile among 130 journals in the mechanical engineering field. The number of annual submissions has steadily increased to close to 870 papers in 2016. In my role as Editor, I will work toward ensuring an efficient, fair, and timely review process while maintaining the journal's high standards for paper quality. My predecessors have established an impressive array of best practices for journal operation, such as streamlining and promoting timely publication of contributions, inviting guest editorial and special issues for promoting emerging design areas, creating an editor's choice award for encouraging high quality work, and developing a new companion website1 as a valuable communication and promotional tool. I will continue these best practices while identifying and implementing new ideas for further advancing JMD.
While it will certainly take me some time to learn about JMD's operations and develop new ideas, there are a few areas I plan to begin working on. First, I will strive to reduce further the review time from submission to publication by working closely with Associate Editors and journal staff. As a part of this effort, I will encourage and facilitate a faster conversion of the ASME conference papers to journal submissions. Second, I will work with international leaders in design engineering to further promote JMD world-wide, especially in regions where the submissions are currently low. Third, I will work on attracting technical leaders in the field to write review articles on key JMD topics. Fourth, to illustrate the relevance and impact of design research on industry practices, I will work to attract more submissions from industry, papers with industrial design applications, and papers on design innovation. Finally, to further bring up the level of scholarship in design research, I will promote the use of rigorous design research methods and raise the awareness of validation protocols.
The past decade has seen a continued growth of interdisciplinary design research, beyond the traditional scope of mechanical design, that involves a wide range of engineering and nonengineering disciplines, e.g., materials science and engineering, mechanics, social science, arts and architecture, economics, market research, computer and information science, and communication studies, to name a few. Real design problems are not defined solely by technical concerns. They involve individuals, groups, organizations, and societies that call for cross-disciplinary collaborations and research. JMD will continue to embrace interdisciplinary design research topics and encourage submissions from teams of interdisciplinary researchers who work on theories and methods to support the design of emerging engineered systems.
The success of JMD is based on the scholarly contributions of authors, dedicated reviewers, staff members supporting the journal, and our board of Associate Editors and Guest Editors who are leaders in their respective technical areas. The current Associate Editors include Oscar Altuzarra, Christina L. Bloebaum, Massimo Callegari, Dar-Zen Chen, Xiaoping Du, Scott Ferguson, James K. Guest, Katja Holtta-Otto, Harrison Kim, Nam H. Kim, Mian Li, Mohsen Kolivand, Gul E. Okudan Kremer, Yu-Tai Lee, Christopher Mattson, Samy Missoum, David Myszka, Ettore Pennestri, Carolyn Seepersad, Rikard Soderberg, Irem Tumer, G. Gary Wang, Paul Witherell, and Hai Xu. Guest Editors include Raymundo Arroyave, Andres Tovar, and Yan Wang. I thank all of the Associate and Guest Editors for their dedicated service to the journal. I am also pleased to let you know that Ms. Amy Suski, who has assisted the most recent Editor Shapour Azarm, is willing to continue on as Assistant to the Editor. During the past five years, JMD has benefited enormously from her experience in assisting the Editors of multiple journals.
In summary, I am excited about this new opportunity to serve ASME and the broad technical community of engineering design. I look forward to working with every one of the JMD stakeholders to bring the journal to the next higher level of excellence.
Copyright © 2018 by ASME
Topics: Engineering design , Design , Design engineering , Innovation
J. Mech. Des 139(12), 120201; doi: 10.1115/1.4038271
Although it has been my privilege and honor to serve as Technical Editor (TE) of the ASME Journal of Mechanical Design (JMD) for the last five years, at the end of December 2017 when my term ends, I will hand over the journal to the excellent leadership of the next TE. As this is my last Editorial, it is an ideal opportunity to give a report on the state of the journal and express my gratitude to those who have contributed their hard work and expertise to JMD throughout my term (2013–2017).
Over the last five years, JMD has received contributions from all areas of engineering design with emphasis on synthesis. Example topics include:
(i) design automation, including design representation, virtual reality, geometric design, design evaluation, design optimization, risk- and reliability-based optimization, simulation-based design under uncertainty, design sensitivity analysis, system design integration, ergonomic and aesthetic considerations, design for market systems, data-driven design, origami and tessellation in design, design for user experience, needs and preferences, and design for materials and structures;
(ii) design of direct contact systems, including design of cams, gears, and power transmission systems;
(iii) design education;
(iv) design of energy, fluid, and power handling systems;
(v) design innovation and devices, including design of smart products and materials;
(vi) design for manufacturing and the life cycle, including design for the environment, DFX, design for additive manufacturing, and sustainable design;
(vii) design of mechanisms and robotic systems, including design of macro-, micro-, and nanoscaled mechanical systems, machine component, and machine system design; and
(viii) design theory and methodology, including creativity in design, decision analysis, design cognition, bio-inspired design, and design synthesis.
Selected key statistics drawn from Journal Tool for the years 2013–2017 reveal a steady increase in the number of submissions, an increase in selectivity, and significant reduction in review times. For example:
In addition to steadily improving its statistics, JMD has endeavored to solicit the best quality papers and promote the visibility of the journal. Since 2013, JMD has had a number of successful special issues on a variety of emerging topics, as listed below:
Following the example of some of the other ASME journals, JMD also began the process of recognizing outstanding papers. In this regard, in May 2014 I wrote an Editorial in JMD titled: “Announcing JMD's Annual Best Paper Award Guidelines.” That editorial discussed the motivation, purpose, criteria for selection, and selection process. However, after further thoughts and inputs from other ASME Editors, it was decided to rename the award as the “Editors' Choice” paper award rather than “Best Paper” award. I then formed and charged a committee to select Editors' Choice papers from a list of papers that were nominated and voted by associate and special issue guest editors. From that list, the committee selected one paper for each of the years 2014–2016 and granted Editor's Choice Paper Award to the authors of each. The papers awarded were as follows:
The continued success of JMD has been due to the extraordinary hard work and dedication of numerous individuals, including technical editors (and their editorial board) who served the journal before me, associate editors, guest editors, my Editorial Assistant (Amy Suski) whom I cannot thank enough for doing her job with utmost professionalism and precision, and the ASME publication staff (Colin McAteer, Journals Manager; Jennifer Smith, Production Coordinator; and ASME staff Beth Darchi and Tamiko Fung) who patiently resolved numerous publication related issues. I am also indebted to our reviewers whose insightful reviews clearly show that they do care deeply about the quality of papers published in the journal.
Finally, I wish all the best for the next TE of JMD!
Below is a listing and short biography of the associate editors and special issue guest editors who served the journal during the period 2013–2017:
Janet K. Allen, Associate Editor 2006–2013, earned her S.B. degree from the Massachusetts Institute of Technology and Ph.D. from the University of California, Berkeley, CA. She is a Professor and John and Mary Moore Chair of Industrial Engineering at the University of Oklahoma. The focus of Dr. Allen's research is a simulation-based design of complex systems and the management of uncertainty.
Oscar Altuzarra, Associate Editor 2012 to present, received his M.Sc. Mechanical Engineering degree and a Ph.D. degree in Mechanical Engineering from the Engineering School of Bilbao, Universidad del País Vasco (UPV/EHU), Leioa, Spain, and a Diploma in higher studies from the Coventry University in Coventry, Coventry, UK. He is a Professor in the Department of Mechanical Engineering at the Engineering School of Bilbao, UPV/EHU. His research interests are theoretical kinematics, mechanisms, design of parallel kinematic machines, robotics, and computational solutions to complex mechanical problems in the field of the theory of mechanisms.
Shorya Awtar, Associate Editor 2013–2015, earned a B.Tech. from the Indian Institute of Technology Kanpur, M.S. from the Rensselaer Polytechnic Institute, and Sc.D. from the Massachusetts Institute of Technology. He is an Associate Professor at the University of Michigan and the Founder and Chief Technology Officer of FlexDex Surgical. His research interests include machine design, flexure mechanisms, parallel kinematics, mechatronic systems, and precision engineering. Application areas include medical devices for minimally invasive surgery, motion stages for metrology and manufacturing, electromagnetic and electrostatic actuators, and microsystems.
Christina L. Bloebaum, Associate Editor 2016 to present, received her B.S., M.S., and Ph.D. degrees in aerospace engineering from the University of Florida in Gainesville, FL. She is the Dennis and Rebecca Muilenburg Professor of Aerospace Engineering at Iowa State University (ISU) in Ames, IA. She is also a member of the Virtual Reality Applications Center (VRAC) and the Human–Computer Interaction program at ISU. She conducts research in design of complex engineered systems, with an emphasis on achieving consistency in physics through incorporation of multidisciplinary design optimization as well as preferences through incorporation of value-based systems engineering and decision analysis.
Diann Brei, Associate Editor 2008–2013, earned her B.S.E degree in Computer Systems Engineering and her Ph.D. in Mechanical Engineering from Arizona State University. She is a Professor of Mechanical Engineering Department at the University of Michigan, Ann Arbor, MI and co-directs the General Motors/University of Michigan Multifunctional Vehicle Systems Collaborative Research Laboratory. Her research interests include integrated design methodology/processes, device innovation, smart materials and structures, and actuation.
Jonathan Cagan, Associate Editor 1998–2001 and 2008–2014, received his Bachelor of Science and Master of Science from the University of Rochester, and his Ph.D. from the University of California at Berkeley, all in Mechanical Engineering. He is the George Tallman and Florence Barrett Ladd Professor in Engineering, in the Department of Mechanical Engineering at Carnegie Mellon University, with courtesy appointment in the School of Design. At Carnegie Mellon he serves as Associate Dean for Graduate and Faculty Affairs in the College of Engineering, co-directs the Integrated Innovation Institute, and is a faculty co-director of the Swartz Center for Entrepreneurship. His research focuses on product development, computational innovation, and cognitive-based engineering.
Massimo Callegari, Associate Editor 2015 to present, received the Laurea degree in Mechanical Engineering from the University of Genova, Genova, Italy. He is a Professor of Machine Mechanics, Chair of the Board of Teachers of Mechanical Engineering degrees, member of the Steering Committee, and Deputy Director of the department of Industrial Engineering and Mathematical Sciences at the Faculty of Engineering of the Polytechnic University of Marche in Ancona, Italy. He has participated into different national and international research projects in the fields of automation, robotics, and innovative handling devices.
Dar-Zen Chen, Associate Editor 2015-present, received his B.S. degree from National Taiwan University (NTU) and M.S. and Ph.D. degrees in Mechanical Engineering from the University of Maryland, College Park, MD. He is a professor in the Department of Mechanical Engineering and Institute of Industrial Engineering at National Taiwan University. In addition to robotics, kinematics, and mechanism design, his research interests also cover intellectual property management, scientometrics, and competitive analysis.
Wei Chen, Associate Editor 2003–2006 and 2010–2013 and Guest Editor 2014–2015, earned her Ph.D. from the Georgia Institute of Technology, M.S. from University of Houston, and B.S. from Shanghai Jiao Tong University, China, all in mechanical engineering. She is a Wilson-Cook Chair Professor in Engineering Design at Northwestern University in the Department of Mechanical Engineering. Her research focuses on design under uncertainty, consumer choice modeling, and decision making in design.
Olivier L. de Weck, Associate Editor 2010–2013, obtained his degree in Industrial Engineering from ETH Zurich and S.M. and Ph.D. degrees in Aerospace Engineering from the Massachusetts Institute of Technology (MIT). He is an Associate Professor of Engineering Systems and Aeronautics and Astronautics at MIT. His research focuses on understanding how complex man-made systems evolve over time and how we can design them to be more changeable while maximizing lifecycle value.
Andy Dong, Associate Editor 2013–2016, earned a B.S., M.S., and Ph.D. from the University of California at Berkeley, all in Mechanical Engineering. He is a Professor and holds the Warren Centre Chair for Engineering Innovation in the Faculty of Engineering and Information Technologies at the University of Sydney. Professor Dong is an expert in the analysis of design data such as organizational interactions, design documents, and product data to forecast and manage the performance of engineering design.
Xiaoping Du, Associate Editor 2016 to present, received his Ph.D., M.S., and B.S. degrees in Mechanical Engineering from the University of Illinois at Chicago, IL, Chongqing University, Chongqing, China, and Shanghai Jiaotong University, Shanghai, China, respectively. He is a Curator's Distinguished Teaching Professor in the Department of Mechanical and Aerospace Engineering at Missouri University of Science and Technology. His research focuses on design under uncertainty, reliability, and optimization.
Qi Fan, Associate Editor 2012 to present, received his M.S. degree in mechanical engineering at Wuhan Transportation University and his Ph.D. from the University of Illinois at Chicago. He is a Senior Gear Theoretician and Director of Bevel Gear Technology (China) at The Gleason Works. He is the current Chair of the Committee of ASME Power Transmission and Gearing. His areas of interest include gear geometry and application, gear manufacturing process, machine tools, and machine elements.
Scott Ferguson, Associate Editor 2016 to present, received his B.S., M.S., and Ph.D. in Mechanical Engineering from the University at Buffalo. He is an Associate Professor in the Department of Mechanical and Aerospace Engineering at North Carolina State University and the director of the System Design Optimization Lab. His research in engineering design and system optimization explores challenges associated with the design of complex engineered systems and market-driven product design.
Zhang-Hua Fong, Associate Editor 2013–2015, received a B.S. degree from National Chung Hsing University and M.S. and Ph.D. degrees from National Chiao Tung University, all in mechanical engineering. He is a Research Professor in the Department of Mechanical Engineering and Dean of the College of Engineering at National Chung Cheng University in Taiwan.
Mary Frecker, Associate Editor 2005–2011 and Guest Editor 2012–2013, has a B.S. from the University of Dayton and an M.S. and Ph.D. in Mechanical Engineering from the University of Michigan. She is a Professor of Mechanical and Biomedical Engineering at the Pennsylvania State University. Her areas of interest include optimal design, compliant mechanisms, smart structures, and medical device design.
Feng Gao, Associate Editor 2012–2014, received his Ph.D. in mechanical engineering from the Beijing University of Aeronautics and Astronautics, China. He is a full professor and serves as the director of State Key Lab of Mechanical Systems and Vibration at the Shanghai Jiao Tong University. His research areas include macro- and microparallel manipulators, humanoid and multileg robots, and design and control of heavy-duty machinery with parallel mechanisms.
Ashitava Ghosal, Associate Editor 2006–2013, obtained B.Tech., M.S. and Ph.D. degrees in mechanical engineering from the Indian Institute of Technology at Kanpur, University of Florida at Gainesville and Stanford University, respectively. He is a Professor of Mechanical Engineering and a faculty member of the Centre for Product Design and Manufacturing at the Indian Institute of Science, Bangalore. His research interests include robotics and multibody mechanical systems, design of mechanical systems, and product design.
Massimiliano Gobbi, Associate Editor 2014–2017, was awarded a master's degree in Mechanical Engineering from Politecnico di Milano, Milan, Italy, and Ph.D. in Applied Mechanics. He is an Associate Professor of Mechanical Engineering at Politecnico di Milano. His research focuses on road vehicles engineering, optimization of complex systems, and advanced design.
David J. Gorsich, Associate Editor 2009–2015, received a Ph.D. in applied mathematics from the Massachusetts Institute of Technology, an M.S. in applied mathematics from George Washington University, and a B.S. in electrical engineering from Lawrence Technological University. He is the Chief Scientist of the U.S. Army Tank Automotive Research, Development, and Engineering Center (TARDEC). His areas of expertise include simulation, reliability-based design optimization, terrain modeling, spatial statistics, and other approximation methods.
James Guest, Associate Editor 2014 to present, received his Ph.D. and M.S.E. from Princeton University, and B.S.E. from the University of Pennsylvania, all in Civil Engineering. He is an Associate Professor of Civil Engineering at the Johns Hopkins University (JHU) and leads the JHU Topology Optimization Group whose research focuses on developing topology optimization algorithms for the design of materials and structures.
Katja Hölttä-Otto, Guest Editor 2015–2016 and Associate Editor 2016 to present, received her M.Sc. and Ph.D. in Mechanical Engineering from Helsinki University of Technology. She is an Associate Professor of product development at the Design Factory at Aalto University, Espoo, Finland. Her areas of specialization include creativity, need finding, design methodologies, and modular product platforms.
Larry L. Howell, Associate Editor 2004–2008 and Guest Editor 2012–2013, received his B.S. degree from Brigham Young University and his M.S. and Ph.D. degrees from Purdue University. He is a Professor, Associate Dean, and past chair of the Department of Mechanical Engineering at Brigham Young University (BYU), where he holds a University Professorship. Professor Howell's patents and technical publications focus on compliant mechanisms.
Chintien Huang, Associate Editor 2012–2014, received his B.S. degree from National Chung Hsing University and M.S. and Ph.D. degrees from Stanford University, all in mechanical engineering. He is a Professor in the Department of Mechanical Engineering at National Cheng Kung University in Taiwan. His areas of expertise include theoretical/computational kinematics and mechanism design.
Charles Kim, Associate Editor 2015–2016, received his B.S. in Mechanical Engineering from the California Institute of Technology and M.S.E. and Ph.D. in Mechanical Engineering from the University of Michigan, Ann Arbor, MI. He is an Associate Professor of Mechanical Engineering at Bucknell University. Professor Kim's primary technical research interests are in methodologies for the design of compliant systems and soft robotic actuators. Professor Kim is also involved in numerous curricular and co-curricular initiatives to synthesize design, innovation, and entrepreneurship.
Harrison Kim, Associate Editor 2013 to present and Guest Editor 2016–2017, received his B.S. and M.S. from the Korea Advanced Institute of Science and Technology, and his Ph.D. from the University of Michigan, all in Mechanical Engineering. He is a Professor in the Department of Industrial and Enterprise Systems Engineering at the University of Illinois at Urbana-Champaign and is affiliated with the Computational Science and Engineering Program at the University of Illinois. His research focuses on complex systems design, product design analytics, multidisciplinary design optimization, sustainability, market systems, and energy systems engineering.
Nam-Ho Kim, Associate Editor 2015-present, received his Ph.D. from the Department of Mechanical Engineering at the University of Iowa. He is a Professor of Mechanical and Aerospace Engineering at the University of Florida. His research areas are structural design optimization, design sensitivity analysis, design under uncertainty, prognostics and health management, nonlinear structural mechanics, and structural-acoustics.
Michael Kokkolaras, Associate Editor 2008–2014, received a Diploma in Aerospace Engineering from the Technical University of Munich and a Ph.D. in Mechanical Engineering from Rice University. He is an Associate Professor of Mechanical Engineering at McGill University. His research interests include multidisciplinary optimization, simulation-based engineering design, uncertainty quantification, decomposition and coordination methods, modeling and validation, systems of systems, product families, and optimization applications in engineering.
Mohsen Kolivand, Guest Editor 2016–2017 and Associate Editor 2017 to present, received his B.S. and M.S. from Tehran University and his Ph.D. from The Ohio State University, all in Mechanical Engineering. Dr. Kolivand is a Bevel Gear Design Manager at American Axle and Manufacturing, Inc., Detroit, MI. His areas of interest include gear geometry, gear manufacturing and inspection, gear efficiency, life estimation, wear analysis, and noise, vibration and harshness evaluation.
Gül E. Kremer, Associate Editor 2014 to present, received her Ph.D. from the Department of Engineering Management and Systems Engineering of Missouri University of Science and Technology. She is a Professor and C.G. “Turk” & Joyce A. Therkildsen Department Chair of Department of Industrial and Manufacturing Systems Engineering at The Iowa State University. Professor Kremer's research interests are in the areas of design education, design decision-making, and sustainability in product design.
Yu-Tai Lee, Associate Editor 2015 to present, received a B.S. in Mechanical Engineering from the National Taiwan University, and his M.S. and Ph.D. in Mechanics and Hydraulics from the University of Iowa. He was a Senior Scientist at the Computational Hydromechanics Division of Naval Surface Warfare Center, Carderock Division. His work has included designing high-pressure fans for Navy's mission-critical shipboard ventilation systems, and coupling computational fluid dynamics optimization schemes for naval ship HVAC compressors and hovercraft lift fans.
Mian Li, Guest Editor 2015–2016 and Associate Editor 2017 to present, earned his B.E. and M.S. in Control Engineering from Tsinghua University China, and his Ph.D. from the Department of Mechanical Engineering, University of Maryland at College Park. He is an Associate Professor in the University of Michigan-Shanghai Jiao Tong University Joint Institute and adjunct Associate Professor at the School of Mechanical Engineering, at Shanghai Jiao Tong University. His research work has been focused on robust/reliability-based multidisciplinary design optimization and control.
Craig Lusk, Associate Editor 2012–2015, earned his M.S. from Virginia Tech and Ph.D. from Brigham Young University. He is an Associate Professor in the Mechanical Engineering Department at the University of South Florida, where he teaches graduate and undergraduate courses on mechanisms and applied elasticity. His research interests include compliant mechanisms, MEMS, biomechanics, and spherical/spatial mechanisms.
Christopher A. Mattson, Associate Editor 2013 to present, received his B.S. and M.S. degrees from Brigham and Young University and his Ph.D. from the Department of Mechanical and Aerospace Engineering at Rensselaer Polytechnic Institute. He is a Professor of Mechanical Engineering at Brigham Young University (BYU). Professor Mattson's research interests include product development, multi-objective optimization, computational design, and design for the developing world.
Samy Missoum, Guest Editor 2015–2016 and Associate Editor 2016 to present, received his doctorate in Mechanical Engineering from the National Institute of Applied Sciences in Toulouse, France. He is an Associate Professor in the Aerospace and Mechanical Engineering Department at the University of Arizona and the Director of the Computational Design Optimization of Engineering Systems (CODES) Laboratory. His research focuses on the development and advanced applications of new optimization, reliability, and risk assessment techniques for nonlinear problems exhibiting a high sensitivity to uncertainty.
Zissimos P. Mourelatos, Associate Editor 2009–2013 and Guest Editor 2015–2016, earned his Ph.D. from the University of Michigan. He is a Professor of Mechanical Engineering at Oakland University and holds the John F. Dodge Chair position of Engineering. Professor Mourelatos conducts research in the areas of design under uncertainty, structural reliability methods, reliability analysis with insufficient data, reliability-based design optimization, vibrations and dynamics, and noise, vibration, and harshness.
David H. Myszka, Associate Editor 2015 to present, received B.S. and M.S. degrees in mechanical engineering from the State University of New York at Buffalo, and M.B.A. and Ph.D. in mechanical engineering from the University of Dayton. He is an Associate Professor in the Department of Mechanical and Aerospace Engineering at the University of Dayton and co-director of the Design of Innovative Machines Laboratory, where he is involved in several academic and industrial projects related to machine and mechanism design, analysis, and experimentation.
Shinji Nishiwaki, Associate Editor 2012–2015, received his B.E. and M.E. degrees in the Department of Precision Engineering from Kyoto University, and Ph.D. in the Department of Mechanical Engineering and Applied Mechanics from the University of Michigan. He is a Professor in the Department of Mechanical Engineering and Science at Kyoto University, Japan. His areas of interest include topology optimization, optimum system design, and multidisciplinary design optimization.
Christiaan J. J. Paredis, Associate Editor 2011–2013, has an M.S. degree in Mechanical Engineering from the Catholic University of Leuven (Belgium), and an M.S. and Ph.D. in Electrical and Computer Engineering from Carnegie Mellon University. He is a Professor and Woodruff Faculty Fellow in the G.W. Woodruff School of Mechanical Engineering at Georgia Tech. His areas of interest include Model-Based Systems Engineering, decision-making under uncertainty, and design optimization.
Matthew Parkinson, Associate Editor 2012–2015, holds a Ph.D. in Biomedical Engineering, an M.S. in Industrial and Operations Engineering from the University of Michigan, and an M.S. in Mechanical Engineering from Brigham Young University. He is a Professor and Director of the Learning Factory at Pennsylvania State University in the College of Engineering. His research efforts focus on tools and methodologies for the design of artifacts that are robust to human variability.
Ettore Pennestrì, Associate Editor 2013 to present, received Laurea in Mechanical Engineering from the University of Rome La Sapienza and an M.S. and Doctor of Engineering Science from Columbia University, New York. He is a Professor of Mechanics Applied to Machines at the University of Roma Tor Vergata, Italy, and holds a teaching appointment at Università Campus Biomedico in Rome. His areas of specialization include powertrain design, mechanisms design, computational kinematics, biomechanics, and multibody dynamics.
Karthik Ramani, Associate Editor 2008-2014, earned his B.Tech. from the Indian Institute of Technology, Madras, M.S. from the Ohio State University, and Ph.D. from Stanford University, all in Mechanical Engineering. He is a Professor in the School of Mechanical Engineering and of Electrical and Computer Engineering (by Courtesy) at Purdue University. His expertise includes digital and computational geometry, shape design and analysis, shape and ontology search, and computational tools for early design innovation.
Kazuhiro Saitou, Associate Editor 2013–2016, received a B.Eng. degree from the University of Tokyo and M.S. and Ph.D. degrees from the Massachusetts Institute of Technology. He is a Professor of Mechanical Engineering at the University of Michigan, Ann Arbor, MI. His research interests include assembly design, structural optimization, manufacturing systems, and biomedical image processing.
James P. Schmiedeler, Associate Editor 2007–2013, received a B.S. degree from the University of Notre Dame and M.S. and Ph.D. degrees from The Ohio State University, all in mechanical engineering. He is a Professor in the Department of Aerospace and Mechanical Engineering at the University of Notre Dame. Professor Schmeideler's areas of interest include machine design, robotics, and biomechanics.
Carolyn Conner Seepersad, Associate Editor 2013 to present and Guest Editor 2014–2017, earned her B.S. degree from West Virginia University and M.S. and Ph.D. from Georgia Tech, all in mechanical engineering. She also earned a B.A./M.A. from Oxford University as a Rhodes Scholar. She is an Associate Professor and General Dynamics Faculty Fellow in the Mechanical Engineering Department at the University of Texas at Austin. Her research focuses on design automation, design of engineering materials and structures, set-based design, design for additive manufacturing, conceptual design, and innovation.
Kristina Shea, Associate Editor 2013–2016, earned her B.S., M.S., and Ph.D. in mechanical engineering from Carnegie Mellon University. She is a Professor for Engineering Design and Computing at ETH Zürich in Switzerland. Professor Shea's areas of expertise include design methods, design representations, synthesis, computational design, model-based design, and additive manufacturing.
Timothy W. Simpson, Associate Editor 2006–2013 and Guest Editor 2014–2017, received a B.S. degree in mechanical engineering from Cornell University and M.S. and Ph.D. degrees in mechanical engineering from the Georgia Institute of Technology. He is the Paul Morrow Professor of Engineering Design and Manufacturing at the Pennsylvania State University in University Park. He also holds faculty appointments in Mechanical and Nuclear Engineering, Industrial and Manufacturing Engineering, Architecture, the School of Engineering Design, Technology, and Professional Programs, and the College of Information Sciences and Technology. His research focuses on product family design, product platforms, additive manufacturing, and design innovation.
Avinash Singh, Associate Editor 2007–2013, received his B. Tech. degree from the Institute of Technology, BHU, India, and his M.S. and Ph.D. degrees in Mechanical Engineering from the Ohio State University. Dr. Singh is an Engineering Group Manager—Advanced Torque Converters and Gear Systems, in the Advanced Power Transfer Group of GM Powertrain, General Motors Corporation. He works on power transmission component technology and his research interests are in the areas of gear system design and analysis, dynamics and noise, development and validation of high fidelity models, power losses, rotating system diagnostics, and fatigue life prediction.
Alexander H. Slocum, Associate Editor 2009–2014 and Guest Editor 2012–2013, earned S.B., S.M., and Ph.D. degrees from the Massachusetts Institute of Technology (M.I.T.). He is the Walter M. May and Hazel May Professor of Mechanical Engineering at the Massachusetts Institute of Technology. His areas of interest include machine elements, precision machine design, medical devices, and energy harvesting machines.
Rikard Söderberg, Associate Editor 2012 to present, received his Ph.D. from Chalmers University of Technology. He is the head of the department for Industrial and Materials Science and Director for Wingquist Laboratory. Dr. Söderberg has been a scientific advisor for the Fraunhofer Chalmers Centre of Industrial Mathematics since it was found in 2001 and is Chairman of its Board of Directors. His research focuses on minimizing the effect of geometrical variation and includes industrial design aspects, visualization, robust design, statistical variation simulation, optimization, assembly modeling and analysis, inspection preparation, and analysis.
Janis Terpenny, Associate Editor 2008–2014, earned a B.S. degree in Applied Mathematics from Virginia Commonwealth University, an M.S. degree in Industrial Engineering and Operations Research, and a Ph.D. degree in Industrial and Systems Engineering from Virginia Tech. She is the Peter & Angela Dal Pezzo Chair and Department Head of the Harold & Inge Marcus Department of Industrial and Manufacturing Engineering at Penn State. Her research interests include engineering design and smart manufacturing, knowledge and information in design, product families and platforms, product obsolescence, complexity of products and systems, cloud computing, and design education.
Kwun-Lon Ting, Associate Editor 2006–2014, received a B.S. from National Taiwan University, M.S. from Clemson University, and Ph.D. from Oklahoma State University. He is a Professor of Mechanical Engineering at Tennessee Tech. His research interests include kinematics, compliant mechanisms, robotics, and optimization.
Irem Tumer, Associate Editor 2012 to present, received her Ph.D. in Mechanical Engineering from The University of Texas at Austin. She is a Professor at Oregon State University, where she leads research in complex system design as part of the Design Engineering Labs, and currently serves as Associate Dean for Research for the College of Engineering. Her expertise is system-level design and analysis for software-intensive engineered systems, focusing on risk and failure analysis and engineering design theory and methodology.
G. Gary Wang, Associate Editor 2013 to present, received his B.Sc. and M.Sc. from School of Mechanical Engineering, Huazhong University of Science and Technology, and obtained his Ph.D. in mechanical engineering from University of Victoria. He is a professor at Simon Fraser University (SFU) in Vancouver, BC, Canada. His research focuses on engineering optimization, metamodel-based design optimization, design visualization, and design for manufacturing.
Paul Witherell, Guest Editor 2016–2017 and Associate Editor 2017 to present, received his Ph.D. from the Department of Mechanical and Industrial Engineering at the University of Massachusetts Amherst. He is a Mechanical Engineer in the Systems Integration Division of the Engineering Laboratory at the National Institute of Standards and Technology, where he manages a project on Systems Integration for Additive Manufacturing and serves as the Associate Program Manager of the Measurement Science for Additive Manufacturing program in the Engineering Laboratory. His research interests include design for additive manufacturing, digital thread for additive manufacturing, design optimization, knowledge representation in product development, ontology and semantic relatedness for design manufacturing, and sustainable manufacturing.
Hai Xu, Associate Editor 2015 to present, received his Ph.D., M.S., and B.S. degrees in Mechanical Engineering from The Ohio State University, The University of Michigan-Dearborn, and Nanjing University of Science and Technology, China, respectively. He is a Senior Staff Engineer of the General Motors Company and serves as a Driveline Gear Technical Specialist at GM's Global Vehicle Components and Subsystems Unit, primarily responsible for hypoid gearing technology development. His expertise is in gear design and manufacturing methods, gear geometry and applications, gear tribology, power loss, fatigue, and noise and vibration.
Hong-Sen Yan, Associate Editor 2007–2013, holds a B.S. from the National Cheng Kung University (NCKU), M.S. from the University of Kentucky, and Ph.D. from Purdue University, all in mechanical engineering. He is an NCKU Chair Professor and an honorary member of IFToMM. Professor Yan's areas of interest include kinematics, conceptual design of mechanisms and machines, and reconstruction design of ancient machinery.
Bernard Yannou, Associate Editor 2008–2015 and Guest Editor 2014–2015, received his M.S. in Mechanical Engineering from Ecole Normale Supérieure of Cachan (ENSC), M.S. in Computer Science from Paris-6 University, and Ph.D. in Industrial Engineering from ENSC. He is a Professor of Industrial and Design Engineering and head of the Industrial Engineering Research Department, CentraleSupélec. His areas of interest include design science, design automation, design management/methodologies/new product development, artificial intelligence in design, innovation engineering, and sustainable design.
Special Issue Guest Editors:
Jesse R. Boyer, Guest Editor 2016–2017, holds two B.S.E. degrees from the University of Michigan in Aerospace Engineering and Naval Architecture and Marine Engineering. He is currently the Additive Manufacturing Fellow at Pratt & Whitney (P&W) and is involved curriculum development at the University of Connecticut and the University of Hartford. His research focus is on key process variables to control additive manufacturing, in-process monitoring for production, digital thread related to inspection, and additive manufacturing.
Matt Campbell, Guest Editor 2015–2016, received his B.S., M.S., and Ph.D. from Carnegie Mellon University. Dr. Campbell is a Professor of Mechanical Engineering at Oregon State University with research focusing on methods that independently create solutions for typical mechanical engineering design problems like gear trains, sheet metal, planar mechanisms, and planning for manufacturing, assembly, and disassembly. He has expertise in a variety of fields such as machine design, design theory, artificial intelligence, graph theory, and numerical optimization.
Clive L. Dym, Guest Editor 2015–2016, completed the B.S.C.E. at Cooper Union, an M.S. at Brooklyn Polytechnic Institute, and Ph.D. at Stanford University. Dr. Dym was a Professor Emeritus of Engineering at Harvey Mudd College where he was the Fletcher Jones Professor of Engineering Design and Director of the Center for Design Education at Harvey Mudd, as well as Engineering Department Chair. His interests included design theory, knowledge-based (expert) systems for engineering design, and structural and applied mechanics.
Ashok K. Goel, Guest Editor 2013–2015, earned his Ph.D. from the Ohio State University. He is a Professor in the School of Interactive Computing, and an Adjunct Professor in the School of Computational Science and Engineering and the Woodruff School of Mechanical Engineering at Georgia Institute of Technology in Atlanta. He is also the Director of Interactive Computing's Design and Intelligence Laboratory and a Co-Director of Georgia Tech's Center for Biologically Inspired Design. Professor Goel conducts research into human-centered computing, artificial intelligence, and cognitive science, with a focus on computational design, modeling, and creativity.
Julie S. Linsey, Guest Editor 2015–2016, received her Ph.D. in Mechanical Engineering at the University of Texas at Austin. She is an Associate Professor in the George W. Woodruff School of Mechanical Engineering at the Georgia Institute of Technology. She founded and leads the Innovation, Design Reasoning, and Engineering Education (IDREEM) Lab. Dr. Linsey's research area is design cognition including systematic methods and tools for innovative design with a particular focus on concept generation and design-by-analogy.
Ying Liu, Guest Editor 2016–2017, obtained his Bachelor and Master's degrees from the Mechanical Engineering Department at the Chongqing University, China, and his Ph.D. from the Innovation in Manufacturing Systems and Technology program under the Singapore MIT Alliance at the National University of Singapore. He is an Associate Professor with the Institute of Mechanical and Manufacturing Engineering at the School of Engineering in Cardiff University, Cardiff, Wales, UK. His research interests focus primarily on design informatics, manufacturing informatics, intelligent (digital) manufacturing, design methodology and process, product design, and advanced ICT in design and manufacturing.
Sankaran Mahadevan, Guest Editor 2015–2016, obtained his B.Tech. from the Indian Institute of Technology, Kanpur, M.S. from Rensselaer Polytechnic Institute, and Ph.D. from Georgia Institute of Technology. Professor Mahadevan is the John R. Murray Sr. Professor of Engineering at Vanderbilt University, where he has appointments in Civil and Environmental Engineering and Mechanical Engineering and is a Co-Director of Laboratory for Systems Integrity and Reliability. His areas of research interest include reliability and risk analysis, design optimization, structural health monitoring, model verification and validation, and uncertainty quantification.
Daniel A. McAdams, Guest Editor 2013–2015, received his Ph.D. from the University of Texas at Austin. He is a Professor of Mechanical Engineering in the Department of Mechanical Engineering at Texas A&M University and directs the Product Synthesis Engineering Research Lab. Dr. McAdams' research interests are in the area of design theory and methodology with specific focus on functional modeling, innovation in concept synthesis, biologically inspired design methods, inclusive design, and technology evolution as applied to product design.
David Rosen, Guest Editor 2014–2015, received his Ph.D. at the University of Massachusetts in mechanical engineering. He is a Professor and Associate Chair for Administration in the School of Mechanical Engineering and Director of the Rapid Prototyping and Manufacturing Institute at the Georgia Institute of Technology. His research interests include computer-aided design, additive manufacturing, and design methodology.
Robert B. Stone, Guest Editor 2013–2015, completed his Ph.D. in Mechanical Engineering from The University of Texas at Austin. He is Professor in the School of Mechanical, Industrial and Manufacturing Engineering at Oregon State University. Dr. Stone's research interests include design theories and methodologies, specifically product architectures, functional representations and automated conceptual design techniques, and biologically inspired design.
Charlie C. L. Wang, Guest Editor 2016–2017, received a B.Eng. degree in mechatronics engineering from Huazhong University of Science and Technology, Wuhan, China. He received his M.Phil. and Ph.D. degrees in mechanical engineering from Hong Kong University of Science and Technology. He is a Professor and Chair of Advanced Manufacturing in the Department of Design Engineering at Delft University of Technology, Delft, The Netherlands. His research interests include geometric computing, computer-aided design, advance manufacturing, and computational physics.
Yan Wang, Guest Editor 2016 to present, received his B.S. from Tsinghua University, M.S. from Chinese Academy of Sciences, and Ph.D. from the University of Pittsburgh. He is an Associate Professor at the Woodruff School of Mechanical Engineering, Georgia Institute of Technology. His research focus is on modeling and simulation-based design and multiscale systems engineering.
Christopher Williams, Guest Editor 2014–2017, received a B.S. degree with High Honors at the University of Florida and M.S. and Ph.D. degrees from Georgia Tech, all in mechanical engineering. He is an Associate Professor and J. R. Jones Senior Faculty Fellow at Virginia Tech in the Department of Mechanical Engineering. He also serves as the Associate Director of the Macromolecules Innovation Institute. His expertise is in additive manufacturing (processes and materials), design for additive manufacturing, and engineering design education.
Harrison Hyung Min Kim, Ying Liu, Charlie C.L. Wang and Yan Wang
J. Mech. Des. 2017;139(11):110301-110301-3. doi:10.1115/1.4037943.
With the arrival of cyber-physical systems or “internet of things” era, massive human- and machine-generated data will create unprecedented challenges and at the same time unmatched opportunities in advancing the theory, methods, tools, and practice of data-driven design for products, systems, and services. By exploiting such huge, versatile, and highly contextualized through-life data, design engineers can harness their organization's competitive edge by uncovering patterns, novel insights, and knowledge for data-driven design. The aim of this special issue is to bring together original and archival articles that present significant contributions in advancing the field of data-driven design.
The initial idea of the special issue originated from a discussion among Ying Liu, Yan Wang, and Charlie Wang during ASME IDETC/CIE 2016 in Charlotte and was enthusiastically supported by Journal of Mechanical Design's Editor, Dr. Shapour Azarm, and Harrison Kim, who later was invited to join as one of the guest editors. Through a world-wide dissemination of the special issue's call for papers, we received 85 submissions, among which 36 papers were selected for peer review evaluation by a minimum of three reviewers. After a minimum of two rounds of review, 20 papers of different types were accepted for publication, including 18 research papers, one review paper, and one technical brief. The key topics among the accepted papers are: D3 methods (foundation and principles), variability and uncertainty in D3, team dynamic in D3, D3 and lifecycle, and D3 applications and case studies with overarching utilization of data from a wide variety of sources and with different magnitude and sizes. The level of enthusiastic response to our call for papers from the design engineering community confirmed our belief that the community is poised to take a leadership role in advancing knowledge and application domains of D3. Below is provided a short summary of the papers in this issue following the previously mentioned subgrouping of the topics.
The paper, “An Integrated Approach for Design Improvement Based on Analysis of Time-Dependent Product Usage Data” by Ma et al., illustrates that product usage data are used to monitor the performance of functional modules in a hierarchical view. The kernel principal component analysis is applied to reduce the dimension of time-dependent performance feature data set corresponding to functional modules, before Gaussian mixed model fitting is used to model degradation under uncertainty. Health degradation severity of each function thus can be characterized from the distributions. To-be-modified design parameters are then identified from the functions with severe degradation tendencies.
The paper, “A Data-Driven Text Mining and Semantic Network Analysis for Design Information Retrieval,” by Feng Shi et al., proposes an approach of ontology-based design concept “wordnet” to address some of the current limitations in design document retrieval. The key technique relies on text mining to establish an unsupervised learning ontology network. Validation through an engineering design case study shows that the proposed approach is able to recognize those highly related complex design tasks and their associations with different engineering elements.
The paper, “V4PCS: Volumetric 4PCS Algorithm for Global Registration,” by Huang et al., provides a geometry registration algorithm that helps identify the similarity between two designs, where the optimum alignment of two surface tessellation models is found efficiently from sampled vertices. The paper shows that the design comparison can support rapid product customization.
The paper, “A Systematic Function Recommendation Process for Data-Driven Product and Service Design,” by Zhang et al. presents a systematic function recommendation process to suggest new functions to an existing product and service. Different from the conventional approaches where new functions are largely formulated by experienced designers, the proposed approach builds upon recommendation systems that dynamically catch the trendy requirements from targeted users that are not recognized by existing product and service yet. A detailed case study reveals the merits of the proposed approach.
The paper, “Beyond the Known: Detecting Novel Feasible Domains Over an Unbounded Design Space,” by Chen and Fuge, presents a data-driven adaptive sampling technique—ε-margin sampling—to discover feasible domain in an unbounded design space in an efficient manner. The method both learns the domain boundary of feasible designs, while also expanding the knowledge of the design space as available budget increases. The authors also couple design manifolds with ε-margin sampling to actively expand high-dimensional design spaces without incurring the exponential penalty. The approach is demonstrated in real-world examples of glassware and bottle design cases.
The paper, “Data-Driven Sizing Specification Utilizing Consumer Text Reviews,” by Chaklader and Parkinson, introduces a new method to determine preliminary design specifications related to human–artifact interaction. The proposed new approach primarily uses text mining of a large number of consumer reviews to suggest human variability information that is essential for interaction. A weighted phrase rating metric is studied which does not require any human intervention but quickly and economically provides information useful to the establishment of design specifications.
The paper, “Automated Extraction of Function Knowledge From Text,” by Cheong et al., develops a method to automatically extract function knowledge from natural language text. The extraction method uses syntactic rules to extract subject–verb–object triplets from parsed text. Then, the Functional Basis taxonomy, WordNet, and word2vec were leveraged to classify the triplets as artifact-function-energy flow knowledge. The method can find function definitions for 66% of the test artifacts. For those artifacts found, 50% of the function definitions identified are compiled in a well-known design repository. In addition, 75% of the most frequent function definitions found by the method are also defined in the same design repository.
The paper, “A Convolutional Neural Network Model for Predicting a Product's Function, Given Its Form,” by Dering and Tucker, introduces a deep learning approach based on three-Dimensional Convolutions that predicts functional quantities of digital design concepts. Case studies have been presented in this paper to verify the research questions that are derived from this work, including whether the learned 3D convolutions are able to accurately calculate the functional quantities, determine what the latent features discovered by this network mean, and assess whether the proposed model can perform better than other deep learning approaches.
The paper, “Mitigating Online Product Rating Biases Through the Discovery of Optimistic, Pessimistic, and Realistic Reviewers,” by Lim and Tucker, offers a new method to lower user rating biases that are caused by customers' optimism or pessimism. By considering the rating history and tendency of a reviewer, the work backed by an unsupervised model aims to adjust the influence on ratings in order to provide customers a more objective and accurate feedback.
Variability/Uncertainty in D3
The paper, “Modeling the Variability of Glenoid Geometry in Intact and Osteoarthritic Shoulders,” by de Vries and Parkinson, presents a research work to model the geometric variability of the glenoid of the scapula. The pipeline based on geometric fitting, radial basis functions, and principal component analysis, which can represent the glenoid in a new manner. The work was validated against existing approaches and CT scans from 42 patients. The models created is expected to help surgeons and engineers to understand the effects of osteoarthritis on bone geometry, as well as the range of variability present in healthy shoulders.
The paper, “A Taylor Expansion Approach for Computing Structural Performance Variation From Population-Based Shape Data,” by Wang and Qian, investigates a Taylor expansion based method for computing structural performance variation over its shape population. To overcome the potential inaccuracy of Taylor expansion for highly nonlinear problems, a multipoint Taylor expansion technique is proposed in the paper, where the parameter space is partitioned into different regions and multiple Taylor expansions are locally conducted. It works especially well when combined with the dimensional reduction of the principal component analysis in the statistical shape modeling.
The paper, “Mining Process Heuristics from Designer Action Data via Hidden Markov Models,” by McComb et al., shows an application of data-mining techniques to quantitatively study the processes that designers use to solve configuration design problems that are characterized by the assembly of components into a final desired solution. The extraction of human problem-solving heuristics is automated through the application of hidden Markov models, which show that designers proceed through four procedural states in solving configuration design problems.
The paper, “Predicting Future Importance of Product Features Based on Online Customer Reviews,” by Jiang et al., illustrates that opinion mining is adopted to extract product features from customers' reviews. Fuzzy sets and rules are used to accommodate the imprecision of natural languages. The importance levels or weights of different product features are determined through fuzzified frequencies and sentiment scores. The fuzzy time series method is also applied to predict future importance weights.
Team Dynamics in D3
The paper, “Concept Clustering in Design Teams: A Comparison of Human and Machine Clustering,” by Zhang et al., presents a machine learning tool to cluster design concepts and compares the outcome to that of manual clustering. The goal of the clustering algorithm is to support design teams in identifying possible areas of “over-clustering” and/or “under-clustering” in order to enhance divergent concept generation process. The approach was demonstrated by the data generated in a graduate new product development class.
D3 and Lifecycle
The paper, “Visual Analytics Tools for Sustainable Lifecycle Design: Current Status, Challenges, and Future Opportunities,” by Ramanujan et al., provides a review of previous research that has created visual analytics tools in sustainable lifecycle design and highlights existing challenges and future opportunities. The opportunities are highlighted for different stages of lifecycle—design, manufacturing, distribution and supply chain, use-phase, and end-of-life.
The paper, “InnoGPS for Data-Driven Exploration of Design Opportunities and Directions: The Case of Google Driverless Car Project,” by Luo et al., demonstrates that patent mining techniques can be applied to identify technological neighborhoods by analyzing proximity of patent domains in graph models. Future design and technological opportunities can be discovered by adopting the proposed method.
D3 Applications and Case Studies
The paper, “Data-Driven Styling: Augmenting Intuition in the Product Design Process Using Holistic Styling Analysis,” by Ranscombe et al., proposes the Holistic Styling Analysis (HSA) for improved digital shape comparison applied to 3D geometry of products. HSA provides objective assessment of difference in appearance to form the basis for designers to rationalize styling to other stakeholders during the design process. The approach enables styling designers to use data to drive their activities in the same manner as other stakeholders. An automotive case study validates the proposed approach by providing objective reference measures for differentiation in multiple products.
The paper, “Identification of Performance Requirements for Design of Smartphones Based on Analysis of the Collected Operating Data,” by Zhang et al., showcases the case when designers of smartphones analyze the operating data for CPU performance and utilization. A sigmoid like function is used to approximate the cumulative distribution function in order to identify customer satisfaction and the point of cost effectiveness.
The paper, “Dynamic Data-Driven Design of Lean Premixed Combustors for Thermoacoustically Stable Operations,” by Chattopadhyay et al., uses collected experimental data to generate stability map of combustor in design parameter space. Support vector machine and Markov models are used to identify system states. The relationship between operational conditions and system response is built with a Gaussian process regression. Designers can then use such relationship to perform design optimization.
The paper, “Mining Patent Precedents for Data-driven Design: The Case of Spherical Rolling Robots,” by Song and Luo proposes a heuristic approach to patent data-driven design and demonstrates the approach in a case study of spherical rolling robot. The approach is an iterative and heuristic methodology to exhaustively search for patents as precedents of the design of a specific technology or product for data-driven next design. Designers can utilize the methodology to make sense of retrieved patent data to explore new design opportunities.
Finally, the guest editorial team would like to take this opportunity to thank all of the contributing authors for their excellent work. We are also very grateful to the reviewers for offering their precious time and efforts and for providing constructive comments in a timely manner, especially for those submissions that were reviewed for three or even four rounds. Without all of you, this special issue would not be possible. Enjoy reading the papers!
For the complete special issue visit ASME's Digital Collection
Special Section: Designing for Additive Manufacturing: Recent Advances in Design for Additive Manufacturing
J. Mech. Des 139(10), 100901; doi: 10.1115/1.4037555
Now in its 40th year of existence, ASME's Journal of Mechanical Design has covered a wide range of topics on behalf of the Design Engineering Division. The past 40 years have seen countless advances in mechanical design, developing new knowledge in areas ranging from simulation to representation to communication, among others. These advances have often been complemented by similar advances in manufacturing, and traditional manufacturing processes such as machining and injection molding have been investigated heavily by the engineering design community. Today, however, we are in the midst of a paradigm shift. Whereas design methods in the past sought to overcome the design constraints imposed by manufacturing technologies, emerging digital manufacturing processes are removing many of these barriers and introducing new ones that are not yet fully understood. As a result, the additional degrees-of-freedom offered via selective (multi-) material addition/subtraction have exceeded our current design proficiencies. Additive manufacturing (AM) is at the forefront of this shift, and our engineering design software, methods, and tools are struggling to keep pace.
As many readers know, AM provides unprecedented freedom for designing and engineering parts that are fabricated layer-by-layer. AM enables novel designs for a wide array of uses and applications in a range of industries, including aerospace, consumer goods, defense, energy, and medical, among others. Components can be easily light-weighted with topology optimization and lattice structures, complex assemblies can be consolidated into single 3D-printed geometries to reduce manufacturing complexity, and multimaterial fabrication techniques made possible by several AM processes enable never before seen functionally graded materials. In short, AM is changing not only what we design but also how we design, and a recent National Science Foundation Workshop on Additive Manufacturing Education and Training revealed that Design for Additive Manufacturing was the most pressing need for (re)training the engineering workforce. Consequently, this Special Section explores recent advances in the theories, methods, tools, and guidelines in Designing for Additive Manufacturing (DFAM). These contributions are empowering engineers to design and realize new parts, products, and systems that leverage AM processes' full capabilities, and in turn, are accelerating the adoption and application of AM technology.
This Special Section is the second of its kind within the Journal of Mechanical Design, following the 2015 Special Issue: Design for Additive Manufacturing: A Paradigm Shift in Design, Fabrication, and Qualification. Since the previous issue, AM has maintained a high level of interest and continues to flourish as design and manufacturing technology have advanced at a feverish pace. America Makes, the first Manufacturing USA Institute, remains a strong advocate for AM technology, providing numerous partnership opportunities for industry and academia to join forces to help accelerate AM adoption. The Additive Manufacturing Standards Collaborative has documented the needs for Design for AM standards and development. Meanwhile, DARPA's transformative design (TRADES) program was established to advance the foundational mathematics and computational tools required to generate and better manage the enormous complexity of design in today's increasingly digital manufacturing environment. Finally, companies like Autodesk, Dassault, Parametric Technologies Corporation, and Siemens are in a neck-and-neck race to field integrated computer-aided design, modeling/simulation, and process planning software support for AM.
Like the previous special issue, we have aimed to present readers with state-of-the-art research regarding DFAM in this special section. The papers in this special section can be categorized into three broad categories: (1) Review of State-of-the-Art, (2) Advances in State-of-the-Art, and (3) DFAM Case studies. Together, these papers highlight the advancements made in the past 2 years in DFAM in the engineering design community. This snapshot of where we currently stand as a design community, and how AM technologies are driving advances in new design paradigms and industrial applications, demonstrates how far we have come within a short period of time. The industrial adoption of AM continues to expand, with numerous companies now using AM processes to produce end-use artifacts in large quantities. AM technologies and material capabilities have continued to rapidly improve, and in turn, have continued to spur new opportunities for design theory, methodology, and automation.
We expect that this will not be the last Special Issue or Special Section on Design for Additive Manufacturing—only the latest. As industry increasingly recognizes AM as viable production technology and integrates it within their existing manufacturing process chain, the need for expanding the mechanical design capabilities for engineers is sure to follow.
Timothy W. Simpson, Pennsylvania State University, firstname.lastname@example.org
Jesse Boyer, Pratt & Whitney, email@example.com
Carolyn Seepersad, University of Texas, Austin, firstname.lastname@example.org
Christopher B. Williams, Virginia Tech, email@example.com
Paul Witherell, NIST, firstname.lastname@example.org
For the Full Special Section visit ASME's Digital Collection
J. Mech. Des 139(8), 080201 (2017)
I am pleased to announce the Journal of Mechanical Design's (JMD's) Editors' Choice Paper Awards for the years: 2014, 2015, and 2016.
Back in May 2014, I wrote an Editorial in JMD titled: “Announcing JMD's Annual Best Paper Award Guidelines.” In that editorial, I outlined the procedures we planned to follow to choose a yearly best paper from papers published in JMD in that year. However, after much further thought and input from the design engineering community, including many JMD Associate and Guest Editors and Editors of other ASME journals, I have decided to call this award: “Editors' Choice Paper Award.” The words “Editors' Choice” were used to refer to the Associate Editors (AEs) and Guest Editors (GEs) involvement in the nomination and selection process.
Let me review the process of selecting the editors' choice paper(s). First, the AEs and GEs involved with the journal in a particular year were asked to nominate papers from those published in JMD in that year. Next, AEs and GEs were asked to vote on the nominated papers. Finally, a three-member committee from current and/or former AEs was formed to finalize the selection. The charge to the committee was to select one or more papers from JMD papers published in each of the years 2014, 2015, and 2016 and which were nominated and voted on by AEs/GEs.
As stated in my 2014 Editorial, the selection criteria used were based on (i) fundamental value of the contribution, (ii) expectation of archival value (e.g., expected number of citations), (iii) practical relevance to mechanical design, and (iv) quality of presentation. The selection committee informed me that in addition to these criteria, it considered the following two criteria: “The breadth of interest and applicability” and “whether the paper addressed an emerging area or an area of immediate interest in the community.” With its final selection, the committee also indicated that: “while we had strong consensus around the papers that were selected, we wanted to make sure that taken as a body the three papers represented a variety of communities and interests (e.g., we did not want three optimization papers or three gear train papers).”
I am now pleased to inform you that the selection committee has finalized and informed me of their selection of Editors' Choice Paper Awards for each of the years 2014–2016, as listed below:
Each author of these papers will receive a plaque in recognition for their award. Also, all three papers can now be accessed FREE online at ASME's Digital Collection homepage.
Please join me in congratulating the authors of these papers. I also would like to take this opportunity to thank all of the current and former AEs and GEs who participated in the nomination of the papers and voted on them. In particular, I want to thank the selection committee who had to carefully read through a large number of the papers and collectively make their final choices!
While I anticipate that there will be room for improvement in the selection process, I am hoping that the Editors' Choice Paper Award becomes a JMD tradition and an annual event.
Shapour Azarm, Technical Editor