Ioshchikhes, Borys ; Weigold, Matthias (2024)
Development of stationary expert systems for improving energy efficiency in manufacturing.
In: Procedia CIRP, 126
doi: 10.1016/j.procir.2024.08.351
Artikel, Bibliographie
Kurzbeschreibung (Abstract)
Increasing energy prices as well as the transition towards the goal of climate neutrality are major challenges for manufacturing companies. Expert systems offer the possibility to address these challenges by aggregating expert knowledge, processing energy data and thus identifying energy efficiency potentials to deduce energy efficiency measures. In this paper, approaches for mobile preliminary and stationary detailed energy analysis are compared. Additionally, a systematic development method for stationary expert systems is presented. The proposed method is demonstrated through the implementation for a chamber cleaning machine to quantify energy efficiency potentials.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2024 |
| Autor(en): | Ioshchikhes, Borys ; Weigold, Matthias |
| Art des Eintrags: | Bibliographie |
| Titel: | Development of stationary expert systems for improving energy efficiency in manufacturing |
| Sprache: | Englisch |
| Publikationsjahr: | 2024 |
| Verlag: | Elsevier B.V. |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Procedia CIRP |
| Jahrgang/Volume einer Zeitschrift: | 126 |
| DOI: | 10.1016/j.procir.2024.08.351 |
| Kurzbeschreibung (Abstract): | Increasing energy prices as well as the transition towards the goal of climate neutrality are major challenges for manufacturing companies. Expert systems offer the possibility to address these challenges by aggregating expert knowledge, processing energy data and thus identifying energy efficiency potentials to deduce energy efficiency measures. In this paper, approaches for mobile preliminary and stationary detailed energy analysis are compared. Additionally, a systematic development method for stationary expert systems is presented. The proposed method is demonstrated through the implementation for a chamber cleaning machine to quantify energy efficiency potentials. |
| Freie Schlagworte: | artificial intelligence, energy analysis, energy transparency, fuzzy systems, sustainable manufacturing |
| Fachbereich(e)/-gebiet(e): | 16 Fachbereich Maschinenbau 16 Fachbereich Maschinenbau > Institut für Produktionsmanagement und Werkzeugmaschinen (PTW) 16 Fachbereich Maschinenbau > Institut für Produktionsmanagement und Werkzeugmaschinen (PTW) > ETA Energietechnologien und Anwendungen in der Produktion |
| Hinterlegungsdatum: | 15 Okt 2024 05:34 |
| Letzte Änderung: | 15 Okt 2024 06:54 |
| PPN: | 522219055 |
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