Design of a Digital Twin for Movement Simulation and Anomaly Analysis of a Forklift Lifting Mechanism Based on IoT

DOI

10.2991/978-94-6463-944-5_20How to use a DOI?

Keywords

Digital twin; forklift; hydraulic system; IoT

Abstract

In response to climate change and the urgent need to reduce greenhouse gas emissions, industries are under pressure to adopt advanced technologies that enhance operational efficiency while minimizing environmental impact. Industry 4.0 plays a pivotal role in this transition by leveraging technologies such as Artificial Intelligence (AI), Internet of Things (IoT), and Big Data Analytics to drive sustainability-driven digitalization. Among these technologies, the Digital Twin (DT) has emerged as a promising approach, enabling real-time simulation, monitoring, and decision-making through bidirectional data exchange. Previous studies have demonstrated that DT implementation can lead to energy savings, cost reduction, and improved predictive maintenance strategies. Building on this context, this study develops an IoT-based digital twin system to model the lifting motion of a forklift and analyze abnormal conditions, particularly hydraulic leaks. The system was designed in three stages: CAD modeling, IoT system development, and hydraulic system modeling. Validation was conducted by comparing the motion of the physical system and the virtual model using RMSE and the coefficient of determination (R²). The results show high accuracy, with R² values of 1 in the ascending phase and 0.996 in the descending phase. However, a higher RMSE during the descending phase indicates deviations caused by nonlinear effects such as friction and fluid compressibility. Furthermore, anomaly simulations demonstrated that internal valve leakage can be detected through reductions in piston speed and changes in pressure patterns. These findings confirm that the proposed digital twin system can accurately represent forklift dynamics and enable real-time anomaly detection in hydraulic systems.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Rian Miftahul Huda
AU  - Agustinus Winarno
AU  - Pagi Singgamata Bagaskara
AU  - Muhammad Irfan Anwari
AU  - Andhi Akhmad Ismail
AU  - Mohd Hatta Mohammed Ariff
AU  - Irfan Bahiuddin
PY  - 2025
DA  - 2025/12/26
TI  - Design of a Digital Twin for Movement Simulation and Anomaly Analysis of a Forklift Lifting Mechanism Based on IoT
BT  - Proceedings of the International Conference on Sustainable Energy: Toward Energy Transition and Net-Zero Emission (ICOSE 2025)
PB  - Atlantis Press
SP  - 290
EP  - 306
SN  - 3005-155X
UR  - https://doi.org/10.2991/978-94-6463-944-5_20
DO  - 10.2991/978-94-6463-944-5_20
ID  - Huda2025
ER  -