TU Darmstadt / ULB / TUbiblio

Systematic Comparison of Analysis Methods to Identify Resource Efficiency Hotspots in Production Sites

Weyand, Astrid ; Lehnert, Sophie ; Alisch, Vincent ; Weigold, Matthias (2022)
Systematic Comparison of Analysis Methods to Identify Resource Efficiency Hotspots in Production Sites.
doi: 10.2139/ssrn.4079206
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

Several analysis methods exist to identify hotspots regarding resource efficiency in industrial environments and consecutively find measures to reduce environmental impact. Still, many companies do not use systematic methods to improve their resource efficiency, partly because they do not have the competences to apply them. In this context, learning factories support in providing the realistic environment to teach the methodological competences. Therefore, learning factory operators and trainers need to choose the most suitable hotspot method(s) for their target group. This paper systematically derives criteria to compare the most relevant hotspot analysis methods for the identification of resource efficiency hotspots. The methods range from simple ones like checklists or the ABC analysis applied to the connection power of machines to more complex ones like the Life Cycle Assessment (LCA). To evaluate these methods according to criteria like required time and costs, all methods are applied in the production environment of the ETA Learning Factory at TU Darmstadt. The gained rating of each method is then transferred towards general statements that apply as well in other production lines. Based on these results, a tool was developed that includes the general ratings of the methods as well as the possibility to weight the criteria so that the rating system can be adjusted according to user requirements. Learning factory operators and trainers can use this tool to identify the hotspot method(s) most suitable for their target audience.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2022
Autor(en): Weyand, Astrid ; Lehnert, Sophie ; Alisch, Vincent ; Weigold, Matthias
Art des Eintrags: Bibliographie
Titel: Systematic Comparison of Analysis Methods to Identify Resource Efficiency Hotspots in Production Sites
Sprache: Englisch
Publikationsjahr: 11 April 2022
Verlag: Elsevier B.V.
Buchtitel: Proceedings of the 12th Conference on Learning Factories (CLF 2022)
Reihe: SSRN elibrary
DOI: 10.2139/ssrn.4079206
Kurzbeschreibung (Abstract):

Several analysis methods exist to identify hotspots regarding resource efficiency in industrial environments and consecutively find measures to reduce environmental impact. Still, many companies do not use systematic methods to improve their resource efficiency, partly because they do not have the competences to apply them. In this context, learning factories support in providing the realistic environment to teach the methodological competences. Therefore, learning factory operators and trainers need to choose the most suitable hotspot method(s) for their target group. This paper systematically derives criteria to compare the most relevant hotspot analysis methods for the identification of resource efficiency hotspots. The methods range from simple ones like checklists or the ABC analysis applied to the connection power of machines to more complex ones like the Life Cycle Assessment (LCA). To evaluate these methods according to criteria like required time and costs, all methods are applied in the production environment of the ETA Learning Factory at TU Darmstadt. The gained rating of each method is then transferred towards general statements that apply as well in other production lines. Based on these results, a tool was developed that includes the general ratings of the methods as well as the possibility to weight the criteria so that the rating system can be adjusted according to user requirements. Learning factory operators and trainers can use this tool to identify the hotspot method(s) most suitable for their target audience.

Freie Schlagworte: Hotspot analysis methods, rating system, sustainability, extension of learning factories
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: 02 Jun 2022 12:23
Letzte Änderung: 02 Jun 2022 12:23
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