Treffer: A Hierarchical Modeling Approach to Improve Scheduling of Manufacturing Processes

Title:
A Hierarchical Modeling Approach to Improve Scheduling of Manufacturing Processes
Contributors:
Gaiardelli, Sebastiano, Spellini, Stefano, Lora, Michele, Fummi, Franco
Publication Year:
2022
Collection:
Università degli Studi di Verona: Catalogo dei Prodotti della Ricerca (IRIS)
Document Type:
Konferenz conference object
File Description:
ELETTRONICO
Language:
English
Relation:
info:eu-repo/semantics/altIdentifier/isbn/978-1-6654-8240-0; info:eu-repo/semantics/altIdentifier/wos/WOS:000946662000035; ispartofbook:Proc. 2022 IEEE 31st International Symposium on Industrial Electronics (ISIE); IEEE 31st International Symposium on Industrial Electronics (ISIE); firstpage:226; lastpage:232; numberofpages:7; https://hdl.handle.net/11562/1071766
DOI:
10.1109/ISIE51582.2022.9831468
Rights:
info:eu-repo/semantics/openAccess
Accession Number:
edsbas.84DDFDC3
Database:
BASE

Weitere Informationen

Timely response to sudden production events and requirements shifts is a key feature of Industry 4.0. It requires techniques to manipulate and optimize the production processes, and components providing an high degree of reconfigurability. To acknowledge to such demands, this paper presents a multi-level and hierarchical approach to manufacturing processes modeling. Models are structured to represent the production hierarchically: partitioning recipes in a set of tasks, allocated to machines' manufacturing services and expressed as a sequence of elementary actions. Then, we propose a run-time scheduling algorithm able to exploit the novel structure given to knowledge by the proposed modeling approach. The algorithm aims at minimizing the makes pan while maximizing machines utilization. We validate the contributions of this paper on a full-fledged production line. The modeling strategy has been implemented in SysML: a well-known systems modeling language. The experiments show the presented model and the proposed scheduling approach enabling a more precise and more performing control over the manufacturing process.