Digital twin-driven multi-dimensional assembly error modeling and control for complex assembly process in Industry 4.0

Zhang, Chao; Zhou, Guanghui; Ma, Dongxu; Wang, Zenghui; Zou, Yongcheng

doi:10.1016/j.aei.2024.102390

Cited by 5 publications

(1 citation statement)

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“…The results showed that the proposed system provides an implementation method and approach for collaborative interaction and iterative operation problems caused by complex coupling in the process industry. In [24], they propose an online modeling and control method for complex assembly processes based on a DT in conjunction with a particle swarm optimization algorithm to dynamically adjust the pro-cess parameters. The framework consists of three layers: a physical layer, a DT layer, and an optimal control layer.…”

Section: Related Workmentioning

confidence: 99%

An Immersive Digital Twin Applied to a Manufacturing Execution System for the Monitoring and Control of Industry 4.0 Processes

Caiza,

Sanz

2024

Applied Sciences

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The present research proposes the implementation of an architecture for industrial process monitoring and control for a manufacturing execution system (MES) using an immersive digital twin (DT). For the design of the proposal, cyber–physical systems (CPS), MES, robotics, the Internet of Things, augmented reality, virtual reality, and open platform communication-unified architecture (OPC UA) communication protocols were used to integrate these technologies and enhance the functionalities of the DT by providing greater performance. The proposed work is implemented in an Industry 4.0 laboratory that is composed of Festo Cyber–Physical Factory and CP-Lab stations. The implementation of the architecture is based on ISO 23247, where the following requirements were considered for the design of DTs: (1) observable attributes and 3D design and visualization of all physical production lines in all of their stages, (2) a communication entity through the OPC UA protocol for the collection of state changes of manufacturing elements, (3) a DT entity where digital models are modeled and updated based on the collected data, and (4) user entities through the use of AR and VR to make manufacturing more efficient. The experimental results showed that the architecture enables interoperability between different platforms and control subsystems. It allows for the detection and diagnosis of problems during the execution of the production line; in addition, the high-fidelity simulation and AR and VR environments provided by the DT with data obtained in real time can improve the accuracy and efficiency of manufacturing through a more detailed analysis of the process, providing advantages such as interactive creation for customized products and continuous innovation.

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Section: Related Workmentioning

confidence: 99%