A Spherical Fuzzy Multi-Criteria Decision-Making Model for Industry 4.0 Performance Measurement

In recent years, efficient processes have become increasingly important because of high-level competition in the production industry. The concept of Industry 4.0 is a relatively new and effective method for managing production processes. Because the Industry 4.0 implementation process includes conne...

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Bibliographic Details
Published inAxioms Vol. 11; no. 7; p. 325
Main Author Ozdemir, Yavuz Selim
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.07.2022
Subjects
Analytic hierarchy process
Business metrics
Cloud computing
Collaboration
Decision making
Fuzzy sets
Industrial applications
Industrial Revolution
Industry 4.0
Internet of Things
Literature reviews
Manufacturing
MCDM
Methods
Multiple criterion
Performance evaluation
Performance management
Performance measurement
Personnel selection
Preferences
Qualitative research
spherical fuzzy AHP
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Summary:In recent years, efficient processes have become increasingly important because of high-level competition in the production industry. The concept of Industry 4.0 is a relatively new and effective method for managing production processes. Because the Industry 4.0 implementation process includes connections between objects, humans, and systems, it is quite difficult to evaluate and measure the performance. At this stage, performance criteria can be applied. However, linguistic evaluation of criteria makes the problem too complicated to solve. The purpose of this paper is to present a novel fuzzy performance measurement model for Industry 4.0 in small and medium-sized manufacturing firms. A hybrid spherical fuzzy analytic hierarchy process (SF-AHP)—weighted score methodology (WSM) is proposed for the performance measurement and scoring process. In the application part of this paper, the propounded methodology was applied to five companies. The results of this study can be used as a reference for experts in the performance measurement of the Industry 4.0 process.
ISSN:2075-1680
2075-1680
DOI:10.3390/axioms11070325