The ontology-based modeling and evolution of digital twin for assembly workshop

Bao, Qiangwei; Zhao, Gang; Yu, Yi; Dai, Sheng; Wang, Wei

doi:10.1007/s00170-021-07773-1

Cited by 28 publications

(9 citation statements)

References 58 publications

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“…The challenge of AGV non-geometric information modeling lies in the consistent description of attributes and tasks, which consists of multivariate heterogeneous data. As a frequently-used semantic modeling method, ontology web language (OWL) is chosen to carry the non-geometric information of AGVs, participating in the digital twin modeling of workshops 48 together with other manufacturing resources. Compared with other information modeling approaches, OWL is characterized by strong expansibility, capable of complex relationship description, and vigoroso machine interpretation ability.…”

Section: Digital Twin Modeling Of Agv Dispatch Systemmentioning

confidence: 99%

A digital twin-driven dynamic path planning approach for multiple automatic guided vehicles based on deep reinforcement learning

Bao

Zheng

Dai

2023

Proceedings of the Institution of Mechanical Engineers, Part B:

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With the increasing demand for customization, the tendency of mechanical manufacturing has gradually shifted to flexible and mixed-line production, which brings new challenges to the existing scheduling pattern. As an indispensable part, logistics is responsible for establishing connections among various production equipment and processes. Meanwhile, the promotion of digital twin theory introduces an application schema for the logistics system. However, there is still a deficiency in the real-time dispatching and path planning of logistics equipment due to the uncontrollability of algorithm efficiency for complex scenes. To fill this gap, a digital twin-driven dynamic path planning approach for multiple automatic guided vehicles (AGVs) is proposed. Firstly, the AGVs are virtualized as the major component of logistics systems, while the ontology expression of logistics tasks is consistently accomplished as well. Secondly, the digital twin-driven application framework of multi-AGV dispatching is established. Moreover, a dynamic path planning method for AGVs relying on deep reinforcement learning is implemented. A segmented path planning method is illustrated considering potential route conflicts, which is regarded as the key contribution of the presented research. At last, a case study is illustrated to show the entire process of multiple vehicle path planning and conflict resolution.

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Section: Digital Twin Modeling Of Agv Dispatch Systemmentioning

confidence: 99%

A digital twin-driven dynamic path planning approach for multiple automatic guided vehicles based on deep reinforcement learning

Bao

Zheng

Dai

2023

Proceedings of the Institution of Mechanical Engineers, Part B:

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“…Literature indicates a scarcity in system-level applications of DTs in SC context, neglecting SC complexity in structural hierarchy. The focused areas of DT application are generally based on the individual SC structural levels in "blocks" (e.g., machine tools, turbomachinery, rotating machinery fault diagnosis) [19][20][21], "modules" (e.g., logistics and assembly) [18,22], and "members" (e.g., the manufacturer) [11,20]. For instance, Bao et al [22] examined the ontology of assembly workshops ("modules"), focusing on simulating assembly resources and tasks but without addressing the embeddedness of assembly "blocks" or extend to the SC level ("systems").…”

Section: Implementation Of Dts In Sc Contextmentioning

confidence: 99%

Expanding the Scope of Manufacturing Digital Twins to Supply Chain

Luo,

Ball

2023

Advances in Transdisciplinary Engineering

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The rapid emergence of digital technologies is revolutionising the manufacturing industry, with digital twins (DTs) emerging as a transformative innovation. DTs, virtual counterparts of physical entities or systems, hold immense potential for optimizing and overseeing manufacturing processes. By proposing a three-dimensional classification framework that considers DT integration levels, supply chain (SC) structural hierarchies, and SC processes, this study examines the evolution of manufacturing DTs to encompass the SC. An analysis of existing literature reveals a significant gap in extending manufacturing DTs to the SC system level without incorporating structural and process aspects of DT models. The paper also investigates the key performance objectives, including efficiency, resilience, and sustainability, as well as the challenges associated with DT implementation. The insights provided in this paper contribute to a better understanding and practical application of DTs in the dynamic contexts of manufacturing and the SC.

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“…Park et al built a DT-based CPPS architectural framework for personalized production [28]. Bao et al investigated an ontology-based modeling and evolution method of DT for the assembly shop-floor to deal with for the issues such as discreteness of assembly process, diversity of assembly resource, and complexity of dataflow in the assembly task execution [29]. Son et al presented a DT-based CPS for abnormal scenarios involving automotive body production lines, which can forecast whether a product can be manufactured where abnormal scenarios occur [30].…”

Section: Overview Of Dt Applications In the Production Phasementioning

confidence: 99%

Digital Twin-based Quality Management Method for the Assembly Process of Aerospace Products with the Grey-Markov Model and Apriori Algorithm

Zhuang

Liu

et al. 2022

Chin. J. Mech. Eng.

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The assembly process of aerospace products such as satellites and rockets has the characteristics of single- or small-batch production, a long development period, high reliability, and frequent disturbances. How to predict and avoid quality abnormalities, quickly locate their causes, and improve product assembly quality and efficiency are urgent engineering issues. As the core technology to realize the integration of virtual and physical space, digital twin (DT) technology can make full use of the low cost, high efficiency, and predictable advantages of digital space to provide a feasible solution to such problems. Hence, a quality management method for the assembly process of aerospace products based on DT is proposed. Given that traditional quality control methods for the assembly process of aerospace products are mostly post-inspection, the Grey-Markov model and T-K control chart are used with a small sample of assembly quality data to predict the value of quality data and the status of an assembly system. The Apriori algorithm is applied to mine the strong association rules related to quality data anomalies and uncontrolled assembly systems so as to solve the issue that the causes of abnormal quality are complicated and difficult to trace. The implementation of the proposed approach is described, taking the collected centroid data of an aerospace product’s cabin, one of the key quality data in the assembly process of aerospace products, as an example. A DT-based quality management system for the assembly process of aerospace products is developed, which can effectively improve the efficiency of quality management for the assembly process of aerospace products and reduce quality abnormalities.

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The ontology-based modeling and evolution of digital twin for assembly workshop

Abstract: dicating the feasibility and validity of the method proposed.

Cited by 28 publications

References 58 publications

A digital twin-driven dynamic path planning approach for multiple automatic guided vehicles based on deep reinforcement learning

A digital twin-driven dynamic path planning approach for multiple automatic guided vehicles based on deep reinforcement learning

Expanding the Scope of Manufacturing Digital Twins to Supply Chain

Digital Twin-based Quality Management Method for the Assembly Process of Aerospace Products with the Grey-Markov Model and Apriori Algorithm

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