Paper Info
Title
Repurposing Manufacturing Lines On The Fly With Multi-Agent Systems For The Web Of Things
Abstract
Multi-agent systems (MAS) have long been envisioned as a key enabling technology in manufacturing, but this promise is yet to be realized: the lack of proper models, architectures, tooling, and the high level of expertise required for designing and programming agent-based manufacturing systems have hindered their large-scale acceptance. The emerging Web of Things (WoT), now being standardized at the W3C and IETF, provides new research opportunities that could help MAS enter the mainstream. In this paper, we present an approach to design scalable and flexible agent-based manufacturing systems that integrates automated planning with multi-agent oriented programming for the WoT: autonomous agents synthesize production plans using semantic descriptions of Web-based artifacts and coordinate with one another via multi-agent organizations; engineers can program and repurpose the systems on the fly via an intuitive Web user interface. The systems use the Web as an application architecture (and not just as a transport layer), which facilitates the seamless integration of geographically distributed production cells. To demonstrate our approach, we implemented a prototypical production cell that uses industry-grade robots and an augmented reality interface for human workers. Together, these contributions demonstrate a means to achieve an intriguing vision for the forthcoming fourth industrial revolution: a global collective intelligence for manufacturing.
Year
DOI
Venue
2018
10.5555/3237383.3237504
PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS AND MULTIAGENT SYSTEMS (AAMAS' 18)
Keywords
Field
DocType
Multi-agent Oriented Programming, Semantic Web, Web of Things, Industry 4.0
Autonomous agent,Web of Things,Applications architecture,Software engineering,Computer science,Semantic Web,Multi-agent system,Augmented reality,User interface,Industry 4.0,Distributed computing
Conference
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Andrei Ciortea124.44
Mayer, Simon225129.78
Florian Michahelles379193.75