Production of complex structures via a swarm of simple, distributed agents is ubiquitous in biology (e.g., ant colonies, cellular formation of tissues), yet technological limitations have traditionally prevented this approach in manufacturing. In contrast, traditional manufacturing, from machining and casting to modern approaches such as roll-to-roll or additive manufacturing, require a deterministic plan which is executed in a series of precise, sequential steps. With miniaturization of robotics and novel inverse design tools, it is now feasible that the distributed, swarm approach used in nature could become an essential future manufacturing platform. The advantages of this approach include (1) the ability to produce complex multimaterial, multiscale structures without predetermined steps and (2) extreme robustness to manufacturing errors. This Future Manufacturing Seed Grant (FMSG) will establish the theoretical foundation and the practical tools necessary to pave the way for this nascent area of research and to understand its feasibility. In addition to the technical aspects of this work, this research could lead to a new area of manufacturing with beneficial economic and workforce implications. In conjunction with mid-sized and large manufacturing firms the researchers will therefore seek insight about how this new manufacturing paradigm would require changes to manufacturing curricula for the training and retraining of future manufacturing workers. This project will lead to the training of diverse graduate and undergraduate students and to outreach to K-12 students and the general public.
The objective of this seed grant is to provide the framework and foundation for a new paradigm for future manufacturing in which multiple simple agents operate based on local information (e.g., temperature, light, pre-existing structure) to modify or manufacture complex structures based on simple local design rules. The feasibility of this new approach will be examined, and suitable vocabulary, processing formalization, design rules, etc., will be developed to establish this paradigm as a new, transformational area of research. The work will address the following key questions: How do local design rules map to different structural features, and ultimately to global mechanical properties (e.g., stiffness, strength, mass, Poisson's ratio) and combinations of properties (e.g., maximal specific toughness for a structure of minimal mass)? How do different design rules affect the rate of convergence toward optimal properties? The answers to these questions will also be incorporated in an inverse design framework, allowing local rules to be generated based on the desired properties. This grant is co-funded by the division of Civil, Mechanical and Manufacturing Innovation (CMMI) and the division of Industrial Innovation and Partnerships (IIP).
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
