Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/166161
Title: | Performance analysis and deadlock avoidance for automated guided vehicle systems | Authors: | Aks, Tayal | Keywords: | Engineering::Computer science and engineering::Computer systems organization::Performance of systems | Issue Date: | 2023 | Publisher: | Nanyang Technological University | Source: | Aks, T. (2023). Performance analysis and deadlock avoidance for automated guided vehicle systems. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/166161 | Project: | SCSE21-0920 | Abstract: | The utilisation of Automated Guided Vehicles (AGVs) in the transport and shipment industry is currently an actively explored area. However, there are still various questions raised regarding the optimality of their performance and their ability to avoid deadlock occurrence. This paper focusses on addressing these issues by first introducing a discrete-event based zone-control paradigm to model AGV operation. The paper then also propose a traffic-control strategy and routing algorithm to ensure optimal system performance and guaranteed collision-free and deadlock-free operation. Finally, the performance of the proposed system is evaluated using a Finite State Machine-based simulation platform that compares various performance metrics from this model against those obtained from past studies running models in the same environmental conditions, thereby ensuring fair comparison benchmarks. The paper finally concludes with a comprehensive comparison of the studies, along with some possible areas of improvement for future studies to focus on. | URI: | https://hdl.handle.net/10356/166161 | Schools: | School of Computer Science and Engineering | Fulltext Permission: | restricted | Fulltext Availability: | With Fulltext |
Appears in Collections: | SCSE Student Reports (FYP/IA/PA/PI) |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
TayalAks_Final_Report.pdf Restricted Access | 834.21 kB | Adobe PDF | View/Open |
Page view(s)
145
Updated on May 7, 2025
Download(s)
12
Updated on May 7, 2025
Google ScholarTM
Check
Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.