TU Darmstadt / ULB / TUbiblio

Knowledge Management on the Shop Floor Through Recommender Engines

Müller, Marvin and Terziev, Georgi and Metternich, Joachim and Landmann, Nils (2020):
Knowledge Management on the Shop Floor Through Recommender Engines.
In: Procedia Manufacturing, (52), pp. 344-349. Elsevier B.V., ISSN 23519789,
DOI: 10.1016/j.promfg.2020.11.057,
[Article]

Abstract

Even with digital shop floor management systems on the rise the knowledge about previously solved problems in production is not shared and used valuably. This paper aims to evaluate if recommender engines can be utilized in digital shop floor management systems to overcome this gap. Therefore, in a first step interviews are conducted to identify requirements from an industry perspective. Based on those, a system for problem solving management with an integrated content-based recommender engine to enhance knowledge management on the shop floor is designed, implemented and tested for its functionality. The evaluation of the quality of the recommendations as well as the quantified industry feedback give promising results and indicate future research and development steps.

Item Type: Article
Erschienen: 2020
Creators: Müller, Marvin and Terziev, Georgi and Metternich, Joachim and Landmann, Nils
Title: Knowledge Management on the Shop Floor Through Recommender Engines
Language: English
Abstract:

Even with digital shop floor management systems on the rise the knowledge about previously solved problems in production is not shared and used valuably. This paper aims to evaluate if recommender engines can be utilized in digital shop floor management systems to overcome this gap. Therefore, in a first step interviews are conducted to identify requirements from an industry perspective. Based on those, a system for problem solving management with an integrated content-based recommender engine to enhance knowledge management on the shop floor is designed, implemented and tested for its functionality. The evaluation of the quality of the recommendations as well as the quantified industry feedback give promising results and indicate future research and development steps.

Journal or Publication Title: Procedia Manufacturing
Number: 52
Publisher: Elsevier B.V.
Divisions: 16 Department of Mechanical Engineering
16 Department of Mechanical Engineering > Institute of Production Technology and Machine Tools (PTW)
16 Department of Mechanical Engineering > Institute of Production Technology and Machine Tools (PTW) > CiP Center for industrial Productivity
Date Deposited: 30 Dec 2020 06:30
DOI: 10.1016/j.promfg.2020.11.057
Export:
Suche nach Titel in: TUfind oder in Google
Send an inquiry Send an inquiry

Options (only for editors)
Show editorial Details Show editorial Details