PyMES: Distributed Manufacturing Execution System for Flexible Industry 4.0 Cyber-Physical Production Systems

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F22%3A00364328" target="_blank" >RIV/68407700:21730/22:00364328 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1109/SMC53654.2022.9945350" target="_blank" >https://doi.org/10.1109/SMC53654.2022.9945350</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/SMC53654.2022.9945350" target="_blank" >10.1109/SMC53654.2022.9945350</a>

Jazyk výsledku

angličtina

Název v původním jazyce

PyMES: Distributed Manufacturing Execution System for Flexible Industry 4.0 Cyber-Physical Production Systems

Popis výsledku v původním jazyce

Industry 4.0 production systems have to support flexibility in products, processes, and production resources. To meet the required level of flexibility, Industry 4.0 production systems have to be capable of interpreting and executing production plans, which consist of generic actions (such as robotic manipulations or transport of material and prod ucts). In industrial practice, Manufacturing Execution Systems (MES) together with Supervisory Control and Data Acquisition (SCADA) systems are usually responsible for such tasks. This paper proposes a new architecture of MES implemented in Python that is able to verify, interpret, and execute production plans automatically generated by an AI planner. Moreover, the proposed MES supports running in a distributed way in several instances, where each instance is able to interpret a location specific part of a production plan. All MES instances are syn chronized and the current global or partial (per each instance) production progress can be observed via HTTP/REST API. The proposed approach is demonstrated in practice on the Industry 4.0 Testbed use-case, utilized for evaluation.

Název v anglickém jazyce

PyMES: Distributed Manufacturing Execution System for Flexible Industry 4.0 Cyber-Physical Production Systems

Popis výsledku anglicky

Industry 4.0 production systems have to support flexibility in products, processes, and production resources. To meet the required level of flexibility, Industry 4.0 production systems have to be capable of interpreting and executing production plans, which consist of generic actions (such as robotic manipulations or transport of material and prod ucts). In industrial practice, Manufacturing Execution Systems (MES) together with Supervisory Control and Data Acquisition (SCADA) systems are usually responsible for such tasks. This paper proposes a new architecture of MES implemented in Python that is able to verify, interpret, and execute production plans automatically generated by an AI planner. Moreover, the proposed MES supports running in a distributed way in several instances, where each instance is able to interpret a location specific part of a production plan. All MES instances are syn chronized and the current global or partial (per each instance) production progress can be observed via HTTP/REST API. The proposed approach is demonstrated in practice on the Industry 4.0 Testbed use-case, utilized for evaluation.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/EF16_026%2F0008432" target="_blank" >EF16_026/0008432: Klastr 4.0 - Metodologie systémové integrace</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

2022 IEEE International Conference on Systems, Man and Cybernetics (SMC)

ISBN

978-1-6654-5258-8

ISSN

1062-922X

e-ISSN

2577-1655

Počet stran výsledku

7

Strana od-do

235-241

Název nakladatele

IEEE

Místo vydání

Piscataway

Místo konání akce

Prague

Datum konání akce

9. 10. 2022

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—