Digital twin–based cyber-physical system for automotive body production lines

Son, Yoo Ho; Park, Kyu Tae; Lee, Donggun; Jeon, Seungwoo; Noh, Sang Do

doi:10.1007/s00170-021-07183-3

Cited by 47 publications

(20 citation statements)

References 46 publications

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“…This opens up the possibility of collecting data on vehicle usage as well as degradation over time. Through the use of simulations and digital twins, this research proposes the use of data present on ECUs to track the conditions of vehicle usage and offer insights into which of its components might be appropriate for reuse, repair or re manufacture (Magargle et al, 2017;Merkle et al, 2021;Son et al, 2021). This combination of sensors, network communication technology and analytic simulations will be informative in the implementation of circular economy behaviour within the automotive industry.…”

Section: Framework For Circular Production Of Automotive Partsmentioning

confidence: 99%

Circular production and maintenance of automotive parts: An Internet of Things (IoT) data framework and practice review

Turner

Okorie

Emmanouilidis

et al. 2022

Computers in Industry

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Section: Framework For Circular Production Of Automotive Partsmentioning

confidence: 99%

Circular production and maintenance of automotive parts: An Internet of Things (IoT) data framework and practice review

Turner

Okorie

Emmanouilidis

et al. 2022

Computers in Industry

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“…Dou et al 22 used digital twin technology in a panel furniture production line personalized custom design to shorten the design cycle. Son et al 23 designed a digital twin-based CPS system to predict the body line's capacity and determine the scheduling plan's feasibility. To sum up, digital twin technology has been applied in the design or operation of workshops and production lines, which significantly affects production efficiency and the intellectual level of workshops or production lines.…”

Section: Related Workmentioning

confidence: 99%

A detection and configuration method for welding completeness in the automotive body-in-white panel based on digital twin

Liu

et al. 2022

Sci Rep

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To address the problems of poor welding completeness and inefficient configuration for defective automotive body-in-white panels, we propose a method for detecting and configuring the welding completeness of automotive body-in-white panels based on digital twin (DT) and mixed reality (MR). The method uses DT to build an MR-oriented DT framework for the detections and configuration of body-in-white panel welding completeness. We propose a method to build a DT knowledge base for panels, a Yolov4-based welding completeness detection method, and a MR-based configuration method for the welding completeness in panels. Our team develop a panel welding completeness detection and configuration system to fully validate the effectiveness of the method.

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“…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]. Zhang et al presented an information modeling method for a CPPS based on DT and AutomationML, which integrated various physical resources into CPPS to support information interaction between resources [31].…”

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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Digital twin–based cyber-physical system for automotive body production lines

Cited by 47 publications

References 46 publications

Circular production and maintenance of automotive parts: An Internet of Things (IoT) data framework and practice review

Circular production and maintenance of automotive parts: An Internet of Things (IoT) data framework and practice review

A detection and configuration method for welding completeness in the automotive body-in-white panel based on digital twin

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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