Artikel in Tagungsband INPROC-2020-17

Bibliograph.
Daten
Hirsch, Vitali; Reimann, Peter; Mitschang, Bernhard: Incorporating Economic Aspects into Recommendation Ranking to Reduce Failure Costs.
In: Procedia CIRP: Proceedings of the 53rd CIRP Conference on Manufacturing Systems (CIRP CMS 2020).
Universität Stuttgart, Fakultät Informatik, Elektrotechnik und Informationstechnik.
englisch.
Elsevier, Juli 2020.
Artikel in Tagungsband (Konferenz-Beitrag).
CR-Klassif.H.2.8 (Database Applications)
Keywordsdecision support; predictive analytics; quality control; End-of-Line testing; classification; fault isolation; failure costs
Kurzfassung

Machine learning approaches for manufacturing usually o er recommendation lists, e.g., to support humans in fault diagnosis. For instance, if a product does not pass the final check after the assembly, a recommendation list may contain likely faulty product components to be replaced. Thereby, the list ranks these components using their probabilities. However, these probabilities often di er marginally, while economic impacts, e.g., the costs for replacing components, di er significantly. We address this issue by proposing an approach that incorporates costs to re-rank a list. Our evaluation shows that this approach reduces fault-related costs when using recommendation lists to support human labor.

Abteilung(en)Universität Stuttgart, Institut für Parallele und Verteilte Systeme, Anwendersoftware
Projekt(e)GSaME-NFG
Eingabedatum5. Mai 2020
   Publ. Institut   Publ. Informatik