Session: DFMLC-02-01-Modeling and Optimization for Sustainable Design and Manufacturing

Paper Number: 89542

89542 - Adapting Modern Product Design to the Circular Economy 

The Circular Economy (CE) is an economic system that maximizes the time resources remain within the economy through re-circulation of materials. Transition to the CE, from a linear economy, is closely tied to information transfer between life cycle areas. Progress towards a circular economy will best be initiated at the product design stage where the decisions taken will have impact throughout the life cycle.  Product design, which is often manual, subjective, and speculative, can benefit from data from other stages of product, manufacturing, material, and supply chain life cycles. Specifically, the CE system can benefit from design systems that are real-time, designer-in-the-loop, and dynamic with respect to life cycle information streams. Five identified challenges toward adapting product design to the CE are 

  1. Consolidation and identification of \textit{Dfx} areas critical to CE
  2.  Realization of a digital thread to the design activities
  3. Incorporation of designer-in-the-loop and AI design agents
  4. Introduction of CE data-driven design methods
  5. Development of CE design standards

A review of the literature in each challenge area identifies future research areas that can address the challenges. Finally, a preliminary circular product design convergence model is introduced to illustrate a CE modern product design system that addresses the challenges and research opportunities. The work contributes a framework within which product design can be improved to aid in the realization of Design-for-the-CE. The circular product design convergence model can be a framework for exploring standards-driven and validated solutions to these challenges.

Presenting Author: Vincenzo Ferrero NIST

Presenting Author Biography: Vincenzo Ferrero received his Ph.D. in from the School of Mechanical, Industrial, and Manufacturing Engineering at Oregon State University. Currently, he is a researcher at the National Institute of Standards and Technology (NIST). His research addresses strategies toward data-driven product design, applied data knowledge synthesis, and data-driven fulfillment of Design-for-X objectives. His research aims to enhance design and manufacturing approaches with machine learning and data mining methods, with a particular interest in bridging Digital Twins and Circular Economy concepts. His background in data knowledge navigation, life cycle engineering, and machine learning has motivated collaborations across topics including data-driven CAD, assembly-function knowledge graphs and algorithms, automated functional modeling, and sustainable design tool development.

Authors:

Vincenzo Ferrero NIST
K. C. Morris NIST
Buddhika Hapuwatte NIST