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An Approach to Supporting the Selection of Maintenance Experts in the Context of Industry 4.0.

Authors :
Patalas-Maliszewska, Justyna
Kłos, Sławomir
Source :
Applied Sciences (2076-3417); 5/15/2019, Vol. 9 Issue 9, p1848, 16p
Publication Year :
2019

Abstract

(1) Background: In recent years, many studies regarding the issues of improving the management and effectiveness of the maintenance department of manufacturing companies, in the context Industry 4.0, have been published. This makes it necessary to establish a research gap in the approach to obtaining support in realising management tasks in the maintenance area in the selection of appropriate employees to perform the given activities. (2) Methods: This article uses literature studies and empirical research results from manufacturing companies, in order to determine the approach in supporting the selection of maintenance experts. In the approach, the method used—which is based on rules should there be future any formalisation of the data—is also the Fuzzy Analytic Hierarchy Process (FAHP), which analyses the importance of a given competence, within a manufacturing resource, to undertake repairs. (3) Results: The innovative approach towards the selection of expert workers in a maintenance department is created, in part, in the form of an implemented web-application. The novelty of the "maintenance expert selection map", so-called, is the provision of formal procedures for describing the competence of each maintenance worker and defining the best "state of nature". (4) Conclusions: In the research that is presented here, the practicality for maintenance managers in the "maintenance expert selection map" was established. This map describes the competence of workers for selecting them for repair work within a given manufacturing resource; the scope of employee training was also determined in this research. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20763417
Volume :
9
Issue :
9
Database :
Complementary Index
Journal :
Applied Sciences (2076-3417)
Publication Type :
Academic Journal
Accession number :
137307120
Full Text :
https://doi.org/10.3390/app9091848