Situation calculus for controller synthesis in manufacturing systems with first-order state representation

Giuseppe De Giacomo; Paolo Felli; Brian Logan; Fabio Patrizi; Sebastian Sardina

doi:10.1016/j.artint.2021.103598

Situation calculus for controller synthesis in manufacturing systems with first-order state representation

Giuseppe De Giacomo, Paolo Felli, Brian Logan, Fabio Patrizi, Sebastian Sardina

Research output: Contribution to journal › Article › Academic › peer-review

Abstract

Manufacturing is transitioning from a mass production model to a service model in which facilities ‘bid’ to produce products. To decide whether to bid for a complex, previously unseen product, a facility must be able to synthesize, on the fly, a process plan controller that delegates abstract manufacturing tasks in a supplied process recipe to the available manufacturing resources. Often manufacturing processes depend on the data and objects (parts) they produce and consume. To formalize this aspect we need to adopt a first-order representation of the state of the processes. First-order representations of the state are commonly considered in reasoning about action in AI, and here we show that we can leverage the wide literature on the Situation Calculus and ConGolog programs to formalize this kind of manufacturing. With such a formalization available, we investigate how to synthesize process plan controllers in this first-order state setting. We also identify two important decidable cases—finite domains and bounded action theories—for which we provide techniques to actually synthesize the controller.

Original language	English
Article number	103598
Pages (from-to)	1-30
Number of pages	1
Journal	Artificial Intelligence
Volume	302
DOIs	https://doi.org/10.1016/j.artint.2021.103598
Publication status	Published - Jan 2022

Bibliographical note

Funding Information:
This work was supported by the Unibz CRC project “Data-aware controllers for Manufacturing” (DACoMan), by the Unibz ID project “Automated Process Planning in Cyber Physical Production Systems of Smart Factories” (SMART-APP), by the Unibz RTD project SYNCED, by the EPSRC grants “Evolvable Assembly Systems” ( EP/K018205/1 ) and “Cloud Manufacturing” ( EP/K014161/1 ), by the Sapienza project “Data-awaRe Automatic Process Execution” (DRAPE), by the ERC Advanced Grant WhiteMech (No. 834228 ) and by the EU ICT-48 2020 project TAILOR (No. 952215 ).

Publisher Copyright:
© 2021 Elsevier B.V.

Keywords

Automated synthesis
Reasoning about actions
Situation calculus
Smart manufacturing

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10.1016/j.artint.2021.103598

1-s2.0-S0004370221001491-mainFinal published version, 848 KBLicence: Taverne

Cite this

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title = "Situation calculus for controller synthesis in manufacturing systems with first-order state representation",

abstract = "Manufacturing is transitioning from a mass production model to a service model in which facilities {\textquoteleft}bid{\textquoteright} to produce products. To decide whether to bid for a complex, previously unseen product, a facility must be able to synthesize, on the fly, a process plan controller that delegates abstract manufacturing tasks in a supplied process recipe to the available manufacturing resources. Often manufacturing processes depend on the data and objects (parts) they produce and consume. To formalize this aspect we need to adopt a first-order representation of the state of the processes. First-order representations of the state are commonly considered in reasoning about action in AI, and here we show that we can leverage the wide literature on the Situation Calculus and ConGolog programs to formalize this kind of manufacturing. With such a formalization available, we investigate how to synthesize process plan controllers in this first-order state setting. We also identify two important decidable cases—finite domains and bounded action theories—for which we provide techniques to actually synthesize the controller.",

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Situation calculus for controller synthesis in manufacturing systems with first-order state representation

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Keywords

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