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Ambient intelligence in self-organising assembly systems using the chemical reaction model

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Abstract

This article discusses self-organising assembly systems (SOAS), a type of assembly systems that (1) participate in their own design by spontaneously organising themselves in response to the arrival of a product order and (2) manage themselves during production. SOAS address the industry’s need for agile manufacturing systems to be highly responsive to market dynamics. Manufacturing systems need to be easily and rapidly changeable, but system re-engineering/reconfiguration and especially their (re-)programming are manual, work-intensive and error-prone procedures. With SOAS, we try to facilitate this by giving the systems gradually more self-* capabilities. SOAS eases the work of the SOAS designer and engineer when designing such as system for a specific product, and supports the work of the SOAS operator when supervising the system during production. SOAS represent an application domain of ambient intelligence and humanised computing which is not frequently considered, but therefore none the less important. This article explains how an SOAS produces its own design as the result of a self-organising process following the Chemical Abstract Machine (CHAM) paradigm: industrial robots self-assemble according to specific chemical rules in response to a product order. This paper reports on SOAS in general, the specification of the chemical reactions and their simulation in Maude.

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Notes

  1. http://www.hitech-projects.com/euprojects/eupass/index.htm

  2. With the exception of the feeders, which are part-specific.

  3. These are commercially available robot types; also a Scara robot, mentioned later, is an example.

  4. Refers to the indexing devices which assure that a carrier is at the correct position.

  5. The tasks are not addressed in any specific order, as the chemical reaction model works in parallel on all “molecules”.

  6. http://www.jessrules.com

  7. As the next step of our ongoing work, a rule to dissolve coalitions must be added to the current CHAM.

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Acknowledgments

The authors also thank the EU-funded coordination action PerAda, http://www.perada.org, for financially supporting travel exchange between authors’ institutions.

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Correspondence to Regina Frei.

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This work was developed while Regina Frei received a PhD grant from the Portuguese Foundation for Science and Technology (SFRH/BD/38608/2007); she currently receives a post-doc grant from the Swiss National Science Foundation.

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Frei, R., Di Marzo Serugendo, G. & Șerbănuță, T.F. Ambient intelligence in self-organising assembly systems using the chemical reaction model. J Ambient Intell Human Comput 1, 163–184 (2010). https://doi.org/10.1007/s12652-010-0016-0

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