Fetch AI
Assembly Line
Fetch.ai x Festo x University of Cambridge
We are incredibly excited to announce that we are collaborating with Festo and the Manufacturing Analytics Group at the University of Cambridge, Institute of Manufacturing (IfM), to provide research and recommendations to successfully develop a multi-agent system architecture for distributed manufacturing. With the use of our Fetch.ai technology stack, including the Autonomous Economic Agents framework and blockchain in synchronized harmony, our goal is to transform the existing manufacturing control systems, delivering a scalable solution for the 21st century and beyond.
Despite advancements in technology, the manufacturing industry remains rife with challenges and inefficiencies, lowering productivity, utilization, production variety. Distributed Manufacturing is a relatively new paradigm proposed to overcome some of these challenges. In Distributed Manufacturing, producers lease excess capacity for customized, low volume high variety orders. Whilst a promising approach to improve productivity and reduce wasted capacity, the take up of Distributed Manufacturing itself has been difficult. One of the issues is a lack of automated mechanisms to match suppliers and buyers. Firms need to spend manual effort to orchestrate matches, which are unlikely to outweigh the cost benefits obtained from a Distributed Manufacturing approach. Another issue has been the monopolization of economic transactions by platform providers, which results in suppliers having to succumb to pressure for reducing prices.
For years, multi-agent systems (MAS) architecture has been considered a possible solution to reducing the above issues associated with the conventional, centralized manufacturing orchestration. MAS offers a way to automatically allocate suppliers of services to buyers, without the associated manual transaction costs. It also allows for decentralized matchmaking, reducing the power of platform providers in suppliers. MAS take up has been slow due to a lack of suitable infrastructure. Ultimately, the missing link has been the application of cutting-edge research in AI and the connection with the blockchain technology that helps us understand the benefits that multi-agent systems can provide within the distributed manufacturing sector.
This collaboration will bridge these gaps, shedding light on the lack of current industry applications available to act as benchmarks to capitalize on the solutions multi-agent systems can provide to the distributing manufacturing sector.