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RESEARCH PAPER
Reliability and efficiency in technology selection in logistics facilities – multi-criteria decision support using the AHP method
 
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Faculty of Transport, Warsaw University of Technology, Poland
 
 
Submission date: 2024-12-05
 
 
Final revision date: 2024-12-23
 
 
Acceptance date: 2025-01-31
 
 
Online publication date: 2025-02-09
 
 
Publication date: 2025-02-09
 
 
Corresponding author
Aleksandra Panek   

Faculty of Transport, Warsaw University of Technology, 75 Koszykowa Street, 00-662, Warsaw, Poland
 
 
 
HIGHLIGHTS
  • A Bayesian-based reliability analysis method by fusing prior and test data is proposed.
  • The prior data are expanded using neural network in combination with simulation data.
  • The mechanism kinematic accuracy reliability is quantified under small-sample condition.
  • The key variables affecting the retraction mechanism reliability are identified.
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ABSTRACT
Reliability, including on-time delivery, is a key indicator of supply chain efficiency. Logistics facilities like warehouses and terminals play a crucial role in meeting service deadlines. Choosing the right technology, such as equipment for goods flow, is essential to ensuring process efficiency and reliability. This paper highlights the usefulness of multi-criteria decision-making methods, particularly the AHP method, in selecting optimal technological solutions based on efficiency and reliability indicators. The study analyzes modern warehouse technologies, evaluating their impact on cargo flow and operational reliability. Using the AHP method, solutions were compared based on factors like efficiency, reliability, access time, security, and costs. Technologies assessed include advanced high-rack systems, AGVs, and drones. The findings demonstrate the AHP method's value in aiding decision-makers and its contribution to enhancing efficiency and reliability in supply chains.
FUNDING
The article was written as part of a research grant awarded by the Scientific Council of the Discipline of Civil Engineering, Geodesy and Transport in 2024.
eISSN:2956-3860
ISSN:1507-2711
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