A Novel Hybrid Model for the Evaluation of Industry 4.0 Technologies' Applicability in Logistics Centers
Journal of Mathematics
; 2023, 2023.
Article
in English
| ProQuest Central | ID: covidwho-2317282
ABSTRACT
The application of Industry 4.0 (I4.0) in the field of logistics leads to the emergence and development of the concept of logistics 4.0. Many I4.0 technologies have been applied in the field of logistics. The goal of this research is to analyze the applicability of nine key I4.0 technologies in logistics centers (LC). For this purpose, an integrated MEREC (MEthod based on the Removal Effects of Criteria)—fuzzy MARCOS (Measurement of Alternatives and Ranking according to COmpromise Solution) model was developed. The applicability of nine I4.0 technologies was evaluated based on 15 subcriteria within three main groups of criteria, namely, technological, social and political, and economic and operative. Using the MEREC method, the weight values of the criteria and subcriteria were determined, while the technologies were ranked using the fuzzy MARCOS method. Based on the results obtained by applying this integrated MCDM (multicriteria decision-making) model, CC was identified as the best alternative, i.e., the technology that is most applicable in logistics centers, followed by IoT and big data. An analysis of the sensitivity of the obtained results to the change in the importance of the criteria was carried out, which shows certain changes in the ranking when the importance of the most important criterion changes.
Mathematics; Multiple criterion; Industry 4.0; Productivity; Environmental impact; Enterprise resource planning; Automation; Ranking; Decision making; Economic growth; Horizontal integration; Evaluation; Internet of Things; Efficiency; Order processing; COVID-19; Big Data; Research methodology; Pandemics; Sustainability; Alliances; Flexibility; Industrial applications; Supply chains; Gross Domestic Product--GDP; Logistics; Coronaviruses
Full text:
Available
Collection:
Databases of international organizations
Database:
ProQuest Central
Type of study:
Experimental Studies
Language:
English
Journal:
Journal of Mathematics
Year:
2023
Document Type:
Article
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