FMSG: Internet of People and Things Bridging manual to semiautomated processes through Cybermanufacturing Collaborative Intelligence

Abstract

This project supports fundamental research in understanding how human roles in manufacturing will evolve with the introduction of increasingly intelligent autonomous agents and what characteristics of assistive technology are important to provide the most effective collaborative relationship between humans and artificial intelligence systems. Application of this research will not only help reduce costs and improve quality for parts designed and manufactured in technical environments but will also explore the sociology of human interaction with artificial systems in ways that further human purposefulness and fulfillment in work.

This project promotes the progress of interdependent science and advances national prosperity and welfare through facilitating value creating in future manufacturing systems. Additionally, this work includes a plan for broadening participation of underrepresented groups in scientific research by a targeted set of recruiting activities toward minority and female candidates through social media and peer-to-peer networks, as well as formal programs such as the National GEM consortium and Clemson's Women in Science and Engineering (WISE) programs.

The objectives of this project are to model collaboration strength in manufacturing among systems of people and artificial intelligence agents and to measure assistive technologies’ influence on manufacturing collaboration. As the manufacturing supply chain has grown from a progression of sequential parts creating an assembly to more modern networks of specialized module builders, the role of interorganizational and intraorganizational collaboration has grown immensely in its influence on productivity and profitability.

Considering the advent of new intelligent planning, automation, and production systems, the proposing team conjectures that the strength of collaboration will retain its influence on positive manufacturing outcomes and can be affected significantly by assistive technologies for human participation. The project outcomes have important implications for future manufacturing in regard to the transition to artificial intelligence implementation throughout the supply chain, and lasting human presence in manufacturing; both of which must work in harmony.

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.