Artificial Intelligence Planning of Failure Recovery Strategies in Discrete Manufacturing Automation

Yumeng Lei, Jan Wilch, Bernhard Rupprecht, Birgit Vogel-Heuser

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

As discrete manufacturing tends to be small batch and customized, automated Production Systems (aPS) must be more flexible to adapt to the variety of products, which makes the aPS more complex and error-prone. To increase system efficiency and reduce downtime caused by manual intervention, strategies for automatic recovery are required. Currently, automatic recovery is fulfilled by portions of the control software that treat selected failures, which have been planned and implemented at design-time. To save engineering effort and treat unpredicted failures, recovery strategies should instead be generated automatically using established artificial intelligence planners. Consequently, this paper proposes a modularization of the functional control software into Control Primitives, from which generated strategies are composed. The same Control Primitives are the building blocks to manually implement the state machines of different operating modes of the aPS, Thus, no additional engineering effort is needed to prepare recoverability in the application development phase. In this paper, four approaches to model and implement PLC-executable Control Primitives are presented. Their viability is evaluated experimentally on a discrete manufacturing demonstrator machine by generating strategies for three use cases.

Original languageEnglish
Title of host publication2023 IEEE 19th International Conference on Automation Science and Engineering, CASE 2023
PublisherIEEE Computer Society
ISBN (Electronic)9798350320695
DOIs
StatePublished - 2023
Event19th IEEE International Conference on Automation Science and Engineering, CASE 2023 - Auckland, New Zealand
Duration: 26 Aug 202330 Aug 2023

Publication series

NameIEEE International Conference on Automation Science and Engineering
Volume2023-August
ISSN (Print)2161-8070
ISSN (Electronic)2161-8089

Conference

Conference19th IEEE International Conference on Automation Science and Engineering, CASE 2023
Country/TerritoryNew Zealand
CityAuckland
Period26/08/2330/08/23

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