On the use of predictive models for improving the quality of industrial maintenance: an analytical literature review of maintenance strategies

Merkt, Oana

doi:10.15439/2019F101

Artykuł - szczegóły

Tytuł artykułu

On the use of predictive models for improving the quality of industrial maintenance: an analytical literature review of maintenance strategies

Autorzy

Merkt Oana

Wybrane pełne teksty z tego czasopisma

http://annals-csis.org

Identyfikatory

DOI

10.15439/2019F101

Warianty tytułu

Konferencja

Federated Conference on Computer Science and Information Systems (14 ; 01-04.09.2019 ; Leipzig, Germany)

Języki publikacji

Abstrakty

Due to advances in machine learning techniques and sensor technology, the data driven perspective is nowadays the preferred approach for improving the quality of maintenance for machines and processes in industrial environments. Our study reviews existing maintenance works by highlighting the main challenges and benefits and consequently, it shares recommendations and good practices for the appropriate usage of data analysis tools and techniques. Moreover, we argue that in any industrial setup the quality of maintenance improves when the applied data driven techniques and technologies: (i) have economical justifications; and (ii) take into consideration the conformity with the industry standards. In order to classify the existing maintenance strategies, we explore the entire data driven model development life cycle: data acquisition and analysis, data modeling, data fusion and model evaluation. Based on the surveyed literature we introduce taxonomies that cover relevant predictive models and their corresponding data driven maintenance techniques.

Słowa kluczowe

data acquisition data analysis artificial intelligence maintenance engineering production engineering standard

pozyskiwanie danych analiza danych sztuczna inteligencja inżynieria utrzymania ruchu Inżynieria produkcji standard

Wydawca

Polskie Towarzystwo Informatyczne

Czasopismo

Annals of Computer Science and Information Systems

Rocznik

2019

Tom

Vol. 18

Strony

693--704

Opis fizyczny

Bibliogr. 47 poz., tab., rys.

Twórcy

autor

Merkt Oana

Oana.Merkt@uni-hohenheim.de

Hohenheim University, Chair of Business Informatics II (530D), Schwerzstrasse 35, Stuttgart 70599, Germany

Bibliografia

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Uwagi

1. Track 4: Information Systems and Technology

2. Technical Session: 14th Conference on Information Systems Management

3. Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).

Typ dokumentu

Bibliografia

Identyfikator YADDA

bwmeta1.element.baztech-8cb7a5db-d3a5-42c9-a328-62654f9df466