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  5. Improved Domain Modeling for Realistic Automated Planning and Scheduling in Discrete Manufacturing
 
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Improved Domain Modeling for Realistic Automated Planning and Scheduling in Discrete Manufacturing

Publication date
2018-10-22
Document type
Conference paper
Author
Rogalla, Antje
Fay, Alexander 
Niggemann, Oliver 
Organisational unit
Automatisierungstechnik 
DOI
10.1109/ETFA.2018.8502631
URI
https://openhsu.ub.hsu-hh.de/handle/10.24405/14928
Scopus ID
2-s2.0-85057238824
ISBN
9781538671085
ISSN
1946-0740
1946-0759
Conference
IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA), 04-07 September 2018, Turin, Italy
Book title
2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA)
First page
464
Last page
471
Peer-reviewed
✅
Part of the university bibliography
✅
  • Additional Information
Abstract
Current production planning and scheduling systems in automation do not meet the requirements of modern individualized production. Today's, static production processes impede customized manufacturing and small-scale production. A new way of thinking towards a dynamic control is required. This paper focuses on automated integrated process planning and scheduling on control level in discrete manufacturing. Existing algorithms in artificial intelligence planning are applied to solve process planning and scheduling problems. The challenge is to model the manufacturing system and products in a way that automated planners can generate efficiently process plans and schedules. Hence, based on a general classification of operations, different modeling options with regard to a successful automated process planning and scheduling are discussed. As a result, a domain modeling approach for discrete manufacturing is presented.
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