Summary
This study addresses the integration of Industry 4.0 technologies within intermodal transport terminals through application of a hybrid Multiple Criteria Decision Making methodology combining the Best-Worst Method and Axial Distance based Aggregated Measurement. The research identifies Internet of Things, Artificial and Ambient Intelligence, and Autonomous and Automated Guided Vehicles as critical technologies for modernising terminal operations and enhancing supply chain efficiency. The framework provides logistics stakeholders with pragmatic guidance for technology selection and investment decisions in terminal modernisation.
UK applicability
The findings may be applicable to UK port and intermodal terminal operators seeking to modernise operations through selective Industry 4.0 adoption. However, the abstract does not specify the geographic context or whether the recommendations account for UK-specific regulatory, infrastructure, or operational constraints.
Key measures
Technology prioritisation scores derived from Best-Worst Method (BWM) and Axial Distance based Aggregated Measurement (ADAM) hybrid methodology; operational efficiency metrics for intermodal terminals
Outcomes reported
The study identified and prioritised key Industry 4.0 technologies for intermodal terminals using a hybrid MCDM methodology, finding that IoT, Artificial and Ambient Intelligence, and Autonomous and Automated Guided Vehicles are paramount for enhancing terminal operational efficiency.
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