|Title:||Improved Domain Modeling for Realistic Automated Planning and Scheduling in Discrete Manufacturing||Authors:||Rogalla, Antje
|Language:||eng||Subject (DDC):||620 Ingenieurwissenschaften||Issue Date:||22-Oct-2018||Publisher:||IEEE||Document Type:||Conference Object||Page Start:||464||Page End:||471||Published in (Book):||2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA)||Publisher Place:||Piscataway||Conference:||IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA), 04-07 September 2018, Turin, Italy||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.
|Organization Units (connected with the publication):||Automatisierungstechnik||ISBN:||9781538671085||ISSN:||19460740||Publisher DOI:||10.1109/ETFA.2018.8502631|
|Appears in Collections:||3 - Reported Publications|
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