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@inproceedings{1654881,
author = {Alechina, Natasha and Brázdil, Tomáš and De Giacomo, Giuseppe and Felli, Paolo and Logan, Brian and Vardi, Moshe},
address = {Palo Alto},
booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
doi = {http://dx.doi.org/10.1609/aaai.v33i01.33012646},
keywords = {manufacturing processes modeling; orchestration},
howpublished = {tištěná verze "print"},
language = {eng},
location = {Palo Alto},
isbn = {978-1-57735-809-1},
pages = {2646-2653},
publisher = {AAAI},
title = {Unbounded Orchestrations of Transducers for Manufacturing},
year = {2019}
}
TY - JOUR
ID - 1654881
AU - Alechina, Natasha - Brázdil, Tomáš - De Giacomo, Giuseppe - Felli, Paolo - Logan, Brian - Vardi, Moshe
PY - 2019
TI - Unbounded Orchestrations of Transducers for Manufacturing
PB - AAAI
CY - Palo Alto
SN - 9781577358091
KW - manufacturing processes modeling
KW - orchestration
N2 - There has recently been increasing interest in using reactive synthesis techniques to automate the production of manufacturing process plans. Previous work has assumed that the set of manufacturing resources is known and fixed in advance. In this paper, we consider the more general problem of whether a controller can be synthesized given sufficient resources. In the unbounded setting, only the types of available manufacturing resources are given, and we want to know whether it is possible to manufacture a product using only resources of those type(s), and, if so, how many resources of each type are needed. We model manufacturing processes and facilities as transducers (automata with output), and show that the unbounded orchestration problem is decidable and the (Pareto) optimal set of resources necessary to manufacture a product is computable for uni-transducers. However, for multi-transducers, the problem is undecidable.
ER -
ALECHINA, Natasha, Tomáš BRÁZDIL, Giuseppe DE GIACOMO, Paolo FELLI, Brian LOGAN and Moshe VARDI. Unbounded Orchestrations of Transducers for Manufacturing. In \textit{Proceedings of the AAAI Conference on Artificial Intelligence}. Palo Alto: AAAI, 2019, p.~2646-2653. ISBN~978-1-57735-809-1. Available from: https://dx.doi.org/10.1609/aaai.v33i01.33012646.
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