A Digital Twin system of reconfigurable tooling for monitoring and evaluating in aerospace assembly

Jin, Jie; Hu, Junshan; Li, Chengyu; Shi, Zhanghu; Lei, Pei; Tian, Wei

doi:10.1016/j.jmsy.2023.03.004

Cited by 18 publications

(8 citation statements)

References 17 publications

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“…As the key technology and important guarantee of intelligent factory construction, digital twin technology can digitally create virtual entities of physical objects, and then use historical data, real-time data, and algorithm models to simulate, verify, predict, and control the life cycle process of physical entities [113][114][115]. At present, digital twin technology has been widely applied in fields such as aviation and aerospace [116], electricity [117], ships [118], urban management [119], construction [120], manufacturing [121], oil and gas [122], etc. Therefore, in the wave of Industry 4.0, ASM in chemical processes based on digital twins is also an important research direction for intelligence and industrial applications.…”

Section: Asm In Chemical Processes Based On Digital Twinsmentioning

confidence: 99%

Abnormal Situation Management in Chemical Processes: Recent Research Progress and Future Prospects

et al. 2023

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In the chemical process, abnormal situations are precursor events of incidents and accidents. Abnormal situation management (ASM) can effectively identify abnormalities and prevent them from evolving into incidents or accidents, ensuring the safe and smooth operation of chemical plants. In recent years, ASM has attracted extensive attention from the process industry and from academia, and a lot of research work has been conducted. However, the intelligence level of ASM in actual chemical plants is still relatively low, and industrial applications still face many difficulties and challenges. This review first summarizes the concepts and involved in the contents of ASM. Then, the latest research progress in various aspects of ASM is systematically reviewed. Finally, the challenges and future research directions of ASM are analyzed based on the perspective of industrial application. This review aims to provide the most cutting-edge reference for follow-up research on ASM, and to promote the intelligent development and practical industrial application of ASM in the chemical process.

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Section: Asm In Chemical Processes Based On Digital Twinsmentioning

confidence: 99%

Abnormal Situation Management in Chemical Processes: Recent Research Progress and Future Prospects

et al. 2023

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“…Figure 1 represents the total number of published articles in these databases regarding these periods. Reference Aerospace [10,11] Marine [13] Automotive and Autonomous Vehicular Systems [12] Healthcare [15,16,17] Agriculture [18] Electronics [14] Manufacturing Processes [19,20,21,22,23] Predictive Maintenance [24] The advent of Industry 4.0 and the digital revolution have opened up new avenues for technological advancements in various fields. One such innovation is the concept of digital twins, which holds great potential to redefine the landscape of materials engineering.…”

Section: Literature Reviewmentioning

confidence: 99%

“…This research aims to investigate the capabilities of digital twins in predicting material behavior and optimizing manufacturing processes, ultimately contributing to the evolution of advanced materials manufacturing. Materials engineering plays a pivotal role in various industries, ranging from aerospace [10,11], automotive and autonomous vehicular systems [12], marine [13], and from electronics [14] to healthcare [15,16,17] and agriculture [18], also can be implemented to many manufacturing processes such as cutting [19,20], milling [21] and other processes [22,23] and predictive maintenance systems [24] as depicted in Table 1. The demand for advanced materials with superior performance has led to the exploration of novel techniques to enhance material behavior and optimize manufacturing processes.…”

Section: Literature Reviewmentioning

confidence: 99%

Malzeme Mühendisliğinde Gelişmiş Malzeme Davranışı Tahmini ve Üretim Süreci Optimizasyonu için Dijital İkizler ve Uygulamaları

TUR

2023

Bayburt Üniversitesi Fen Bilimleri Dergisi

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The advent of Industry 4.0 and the digital revolution have brought forth innovative technologies such as digital twins, which have the potential to redefine the landscape of materials engineering. Digital twins, virtual representations of physical entities, can model and predict material behavior, enabling enhanced design, testing, and manufacturing of materials. However, the comprehensive utilization of digital twins for predictive analysis and process optimization in materials engineering remains largely uncharted. This research intends to delve into this intriguing intersection, investigating the capabilities of digital twins in predicting material behavior and optimizing manufacturing processes, thereby contributing to the evolution of advanced materials manufacturing. Our study will commence with a detailed exploration of the concept of digital twins and their specific applications in materials engineering, emphasizing their ability to simulate intricate material behaviors and processes in a virtual environment. Subsequently, we will focus on exploiting digital twins for predicting diverse material behaviors such as mechanical properties, failure modes, and phase transformations, demonstrating how digital twins can utilize a combination of historical data, real-time monitoring, and sophisticated algorithms to predict outcomes accurately. Furthermore, we will delve into the role of digital twins in optimizing materials manufacturing processes, including casting, machining, and additive manufacturing, illustrating how digital twins can model these processes, identify potential issues, and suggest optimal parameters. We will present detailed case studies to provide practical insights into the implementation of digital twins in materials engineering, including the advantages and challenges. The final segment of our research will address the current challenges in implementing digital twins, such as data quality, model validation, and computational demands, proposing potential solutions and outlining future directions. This research aims to underline the transformative potential of digital twins in materials engineering, thereby paving the way for more efficient, sustainable, and intelligent material design and manufacturing processes.

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“…Overhanging structures such as beam and plate are widely used in the reconfigurable toolings to provide openness and flexibility but have less rigidity under the mechanical and thermal loads than traditional rigid fixtures. Due to the structural deformations of the toolings, the aircraft parts are forcefully positioned and clamped, which results in high level of residual stress in assembled structures and shortens service lifespan of the aviation products [4].…”

Section: Introductionmentioning

confidence: 99%

Structural deformation and clamping force monitoring of reconfigurable tooling motivated by strain data in aircraft assembly

Li,

Hu,

Kang

et al. 2024

Smart Mater. Struct.

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The quality of aircraft assembly is mainly guaranteed by toolings which are vital to the geometrical accuracy and service performance of aviation products. In this research, a real-time monitoring system that determines the structural deformation and clamping force of reconfigurable toolings using strain data is developed to perceive the service state of the toolings. By laying fiber Bragg gratings on positioning beam and baseplate of the reconfigurable tooling, strain data of the tooling structures are gauged and transferred to curvatures. The beam and baseplate are modeled as one and two-dimensional objects respectively and shape reconstruction algorithms are established to obtain their deflection curve and surface using curvature information. Distribution of fibers is optimized to minimize the conversion error from strain to curvature. An estimation that reveals the mathematical relationship between the shape reconstruction error and measurement interval is implemented, and a mapping model from strains to clamping force of the beam is established. These algorithms are integrated into the self-developed monitoring software and undergo simulating and experimental tests. The maximum relative errors of deformation and force are 4.53% and 4.12% respectively in simulation, and 9.21% and 7.29% individually in experiment, which validates the efficiencies of the method. Tests of the monitoring system suggest that it can provide a timely and accurate sensing of the deformation and force of the tooling.

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A Digital Twin system of reconfigurable tooling for monitoring and evaluating in aerospace assembly

Cited by 18 publications

References 17 publications

Abnormal Situation Management in Chemical Processes: Recent Research Progress and Future Prospects

Abnormal Situation Management in Chemical Processes: Recent Research Progress and Future Prospects

Malzeme Mühendisliğinde Gelişmiş Malzeme Davranışı Tahmini ve Üretim Süreci Optimizasyonu için Dijital İkizler ve Uygulamaları

Structural deformation and clamping force monitoring of reconfigurable tooling motivated by strain data in aircraft assembly

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