August 18, 2025 Anaheim, CA

BiSSL Ph.D. candidate Hadear Hassan led the publication of an IDETC-CIE conference paper titled “Potential for Digital Technologies & Additive Manufacturing to Support Lean Manufacturing + Circular Economy Synergies” in collaboration with Aarhus University Ph.D. student (and former BiSSL MS student) Amira Bushagour and Dr. Abheek Chatterjee, who is a post doc at NIST and is a former BiSSL PhD student. The paper was presented in the SEIKM track on “Advanced Manufacturing and Supply Chain Systems Design and Analysis” co-chaired by Dr. Chatterjee.

ABSTRACT: Lean manufacturing and circular economy are two production paradigms aimed at addressing the challenges faced by traditional production models, such as resource constraints, environmental impacts, and waste generation. Lean manufacturing focuses on improving production efficiency by eliminating non-value-adding activities. Circular economy aims to reduce waste and resource consumption and support production demands by retaining valuable materials in the economy as long as possible. Recent research has indicated that the convergence of these paradigms is a promising strategy to support sustainable production and consumption. However, challenges remain in fully integrating these approaches, as lean manufacturing emphasizes efficiency without directly considering environmental concerns, a key goal of the circular economy. This research investigates if additive manufacturing and digital technologies (such as digital twins and product passports) offer potential approaches to support the synergies between lean manufacturing and circular economy initiatives. To this end, this article surveys how additive manufacturing and digital technologies support the core aspects of circular economy and lean manufacturing. Thereafter, the synergies between the core aspects of the two paradigms are analyzed with a focus on the application of digital technologies and additive manufacturing in supporting these synergies. Specifically, it is found that the integration of digital technologies with additive manufacturing enables real-time monitoring and predictive analytics. This integrated approach addresses the scalability and flexibility challenges of additive manufacturing implemented alone while enhancing waste reduction, resource optimization, and material life cycle transparency in lean manufacturing and circular economy applications. These findings provide stakeholders with valuable insights regarding simultaneously implementing lean manufacturing and circular economy principles – supporting financial benefits, reduced environmental impacts, and sustainable production growth. -Hassan, Chatterjee, Bushagour, Layton. (2025) “Potential for Digital Technologies and Additive Manufacturing to Support Lean Manufacturing and Circular Economy Synergies.” ASME 2025 International Design Engineering Technical Conferences and Computers & Information in Engineering Conference (IDETC-CIE). Anaheim, CA, USA.

June 26, 2025

Ph.D. student Hadear Hassan presented research on a dynamic model that uses bio-inspired design principles to evaluate manufacturing systems for sustainability and resilience, especially under disturbances, while linking system qualities to performance metrics like capital cost and demand met at the 2025 Manufacturing Science and Engineering Conference (MSEC), hosted by Clemson University in Greenville, SC. The paper was a collaboration with Amira Bushagour, Dr. Abheek Chatterjee, and Dr. Astrid Layton.

The paper presented is titled “Quantitatively Supporting System-Level Sustainability and Resilience in Manufacturing.”

Abstract: “Manufacturing is a key driver of both economic health and environmental burdens, reporting over 12.7 million workers in the U.S. and emitting 30% of greenhouse emissions. Manufacturing systems thus must be both sustainable and resilient to mitigate environmental degradation and maintain job security and operations in case of disturbances. Doing both in manufacturing, however, is non-trivial and quantitatively ambiguous. This work investigates a bio-inspired approach to quantitatively design for both. Twenty manufacturing floor plan architectures are evaluated using a bio-inspired system design approach and traditional manufacturing metrics. Ecological Network Analysis has been shown in prior work to offer system design guidance inspired by nature’s resilient and sustainable food webs. Traditional metrics such as capital cost, throughput, and capacity utilization correlate these ecological characteristics with manufacturing-specific goals for the first time. The architectures, in both their traditional and bio-inspired architectures, are tested under disturbance scenarios to determine if the bio-inspired designs offer superior performance from a manufacturing perspective. The evaluation highlights interdependencies between metrics that capture circular economy supporting efficient pathways and resilience supporting manufacturing convertibility. The results also form the beginnings of an assessment framework for the use of low data metrics in the early-stages of manufacturing systems design.” Hassan, H., A. Bushagour, A. Chatterjee, A. Layton. (2025) “Quantitatively Supporting System-Level Sustainability and Resilience in Manufacturing.” ASME Manufacturing Science and Engineering Conference (MSEC). Greenville, SC, USA.

June 21-25, 2025 in Montreal, Canada

Dr. Astrid Layton hosted a free workshop at the 2025 ASEE Conference & Exposition in collaboration with Dr. Julie Linsey from Georgia Tech. The NSF sponsored workshop was titled “Is My Makerspace Meeting Students’ Needs? How to gain quantitative information about your space using a student-tool network model” and focused on the use of the BiSSL developed GUI for makerspace network analysis.

Dr. Layton also presented a paper “IUSE: Analyzing Nestedness Variability for Bipartite Makerspace Tool-Tool Projection Models” on this makerspace network analysis work, with lead author BiSSL PhD student Pepito Thelly.

Dr. Layton presented another paper “Work in Progress: Examining the Network Growth Strategies of Early-Stage Entrepreneurs” on research done in collaboration with Dr. M. Cynthia Hipwell at Texas A&M and the NSF I-Corps program, with first authors BiSSL grad student Ria Madan and PhD student Hadear Hassan.

This year’s ASME IDETC-CIE conference saw one BiSSL Ph.D. student, Emily Payne, presenting her first-authored paper and Dr. Layton serving as an invited panelist for 2 panels.

Emily’s paper, “Integrating Machine Learning into the Design of Green Building Systems,” was presented in the SEIKM: Systems Engineering and Complex Systems.

Abstract: Sustainable infrastructure design is a complicated process often requiring detailed estimates specifications and constraints of the project scope to be compiled. Beyond the time-consuming gathering of project data sometimes the availability of completed projects is limited. Therefore, a method to produce similar designs with varied constraints requires a systems engineering perspective. Systems engineering provides a method to evaluate multidisciplinary design development while simultaneously following stakeholder requirements. Ecologically inspired systems have shown the ability to maintain balanced resources and structural relationships even under duress. Driven by the imperative to build sustainable infrastructure, this research explores the utilization of machine learning techniques to generate robust and reliable forecasts of green building specifications, even when design resources are scarce. To demonstrate the effectiveness of this approach, machine learning techniques were performed on a dataset of 93 green educational buildings, and on an oversampled dataset containing synthetically generated data points at the aim of certification level prediction. Both datasets contained metrics quantitatively characterizing cost, energy efficiency, and ecologically sustainable metrics specific to each building. Results indicate that the oversampled dataset allowed for better machine learning prediction among the classification algorithms considered. Oversampled data provided quality information offering cost minimization during initial design stages. This data suggests that oversampling is a reliable technique to amplify the design area of infrastructure projects when applied on data containing strong systemic classification patterns.

A panel session “Approaches to Environmental Sustainability, Perspectives from Europe and North America” hosted by the Design Society and organized by Dr. Julie Linsey invited me along with Dr. Abigail Clarke-Sather from the University of Minnesota Duluth and Dr. Devarajan Ramanujan from Aarhus University. The talks and discussion highlighted recent work at the interface of engineering design and circular economy.

Session Description: Minimizing impacts on the environment through clean energy, sustainability, and similar topics continues to grow and be critical topics in engineering.  It is a topic that attracts significant interest in both North America and Europe and benefits from the diverse regional perspectives.  In this special session, leading researchers from Europe and North America will present their perspectives on current needs, research approaches, cutting-edge research, and differing viewpoints.  This session will feature 7-minute short, thought-provoking presentations followed by panelist discussions and questions.   The focus will be on bringing diverse perspectives and cutting-edge research from both communities together, thereby building greater connections between the European Design Society community and the primarily North American ASME IDETC community. 

A panel special session “Opportunities at the Boundaries between Systems Engineering and Design Theory” hosted by the Design Theory and Methodology technical committee and organized by Drs. Bryan Watson and Alex Murphy invited me along with Diarny Fernandes from the Johns Hopkins University Applied Physics Laboratory and Dr. Matthew Mueller from PTC. The discussion highlighted useful intersections and emerging problems between design theory and systems engineering.