Kott, Matthäus ; Echler, Daniel ; Groche, Peter (2024)
Methodological approach for the development of an operator assistance system for the press shop.
In: The International Journal of Advanced Manufacturing Technology, 2022, 119 (3-4)
doi: 10.26083/tuprints-00023457
Artikel, Zweitveröffentlichung, Verlagsversion
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Kurzbeschreibung (Abstract)
The productivity of a deep drawing process strongly relies on its robustness as well as the experience of the machine operator. Steadily increasing requirements regarding weight, design and efficiency lead to a production operating increasingly closer to the process limits, making it more challenging to ensure a high robustness of the process. Minimal process fluctuations caused by disturbances such as varying material properties or changing tribological conditions may negatively affect the process due to deteriorated product properties as well as an increased risk of scrap. Thus, a target-oriented adjustment of available parameters by the machine operator becomes more difficult, and an increased knowledge about the causes of defects is more important. In the past, several approaches with different combinations of sensors and actuators have been investigated to enable a stable process window based on a control system. This paper presents a method to address the need for a more robust process by developing an operator assistance system that enables the identification of the component state and provides decision support to the machine operator. The methodological approach includes a thorough process analysis to evaluate the expediency of such a system and to make a reasonable preselection of sensors in order to avoid unnecessary costs.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2024 |
| Autor(en): | Kott, Matthäus ; Echler, Daniel ; Groche, Peter |
| Art des Eintrags: | Zweitveröffentlichung |
| Titel: | Methodological approach for the development of an operator assistance system for the press shop |
| Sprache: | Englisch |
| Publikationsjahr: | 5 März 2024 |
| Ort: | Darmstadt |
| Publikationsdatum der Erstveröffentlichung: | 2022 |
| Ort der Erstveröffentlichung: | London |
| Verlag: | Springer London |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | The International Journal of Advanced Manufacturing Technology |
| Jahrgang/Volume einer Zeitschrift: | 119 |
| (Heft-)Nummer: | 3-4 |
| DOI: | 10.26083/tuprints-00023457 |
| URL / URN: | https://tuprints.ulb.tu-darmstadt.de/23457 |
| Zugehörige Links: | |
| Herkunft: | Zweitveröffentlichung DeepGreen |
| Kurzbeschreibung (Abstract): | The productivity of a deep drawing process strongly relies on its robustness as well as the experience of the machine operator. Steadily increasing requirements regarding weight, design and efficiency lead to a production operating increasingly closer to the process limits, making it more challenging to ensure a high robustness of the process. Minimal process fluctuations caused by disturbances such as varying material properties or changing tribological conditions may negatively affect the process due to deteriorated product properties as well as an increased risk of scrap. Thus, a target-oriented adjustment of available parameters by the machine operator becomes more difficult, and an increased knowledge about the causes of defects is more important. In the past, several approaches with different combinations of sensors and actuators have been investigated to enable a stable process window based on a control system. This paper presents a method to address the need for a more robust process by developing an operator assistance system that enables the identification of the component state and provides decision support to the machine operator. The methodological approach includes a thorough process analysis to evaluate the expediency of such a system and to make a reasonable preselection of sensors in order to avoid unnecessary costs. |
| Freie Schlagworte: | Variant simulations, Sensitivity analysis, Neural networks, Decision-making, Assistance system |
| Status: | Verlagsversion |
| URN: | urn:nbn:de:tuda-tuprints-234572 |
| Sachgruppe der Dewey Dezimalklassifikatin (DDC): | 600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften und Maschinenbau |
| Fachbereich(e)/-gebiet(e): | 16 Fachbereich Maschinenbau 16 Fachbereich Maschinenbau > Institut für Produktionstechnik und Umformmaschinen (PtU) |
| Hinterlegungsdatum: | 05 Mär 2024 12:59 |
| Letzte Änderung: | 06 Mär 2024 06:55 |
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| Suche nach Titel in: | TUfind oder in Google |
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- Methodological approach for the development of an operator assistance system for the press shop. (deposited 05 Mär 2024 12:59) [Gegenwärtig angezeigt]
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