scholarly journals Application framework of digital twin-driven product smart manufacturing system: A case study of aeroengine blade manufacturing

2019 ◽  
Vol 16 (5) ◽  
pp. 172988141988066
Author(s):  
Xuqian Zhang ◽  
Wenhua Zhu

In the wake of the continuous deepening of the application of new generation information technology in the manufacturing field, digital twin, as a most new active factors for smart manufacturing, has become a new research hot spot. Based on such a background, the article proposes a novel application framework of digital twin-driven product smart manufacturing system and analyzes its operation mechanism. Key enabling technologies such as digital twin mapping technology with manufacturing entity, twinning of cyber and physical manufacturing system, as well as twining data-driven machining parameter optimization are also illustrated in detail. Finally, a case of the aeroengine fan blade manufacturing is given to demonstrate the feasibility and effectiveness of the implementation method mentioned above. Meanwhile, potential industrial applications and limitations are discussed as well to provide valuable insights to aeroengine blade manufacturers.

Author(s):  
Wesley Ellgass ◽  
Nathan Holt ◽  
Hector Saldana-Lemus ◽  
Julian Richmond ◽  
Ali Vatankhah Barenji ◽  
...  

With the developments and applications of the advanced information technologies such as cloud computing, internet of thing, artificial intelligence and virtual reality, industry 4.0 and smart manufacturing era are coming. In this respect, one of the specific challenges is to achieve a connection of physical resources on the shop floor with virtual resources, for real-time response, real time process optimization, and simulation, which is merged by big data problem. In this respect, Digital Twins (DT) concept is introduced as a key technology, which includes physical resources, virtual resources, service system, and digital twin data. DT considers current condition of physical resource and prediction of future events to make a responsive decision. However, due to the complexity of building a digital equivalent in virtual space to its physical counterpart, very little applications have been developed with this purpose, especially in the industrial manufacturing area. Therefore, the types of data and technology required to build the DT for a manufacturing system are presented in this work, trying to develop a framework of DT based manufacturing system, which is supported by the virtual reality for virtualization of physical resources.


2021 ◽  
Vol 11 (8) ◽  
pp. 3568
Author(s):  
Amr T. Sufian ◽  
Badr M. Abdullah ◽  
Muhammad Ateeq ◽  
Roderick Wah ◽  
David Clements

The fourth industrial revolution is the transformation of industrial manufacturing into smart manufacturing. The advancement of digital technologies that make the trend Industry 4.0 are considered as the transforming force that will enable this transformation. However, Industry 4.0 digital technologies need to be connected, integrated and used effectively to create value and to provide insightful information for data driven manufacturing. Smart manufacturing is a journey and requires a roadmap to guide manufacturing organizations for its adoption. The objective of this paper is to review different methodologies and strategies for smart manufacturing implementation to propose a simple and a holistic roadmap that will support the transition into smart factories and achieve resilience, flexibility and sustainability. A comprehensive review of academic and industrial literature was preformed based on multiple stage approach and chosen criteria to establish existing knowledge in the field and to evaluate latest trends and ideas of Industry 4.0 and smart manufacturing technologies, techniques and applications in the manufacturing industry. These criteria are sub-grouped to fit within various stages of the proposed roadmap and attempts to bridge the gap between academia and industry and contributes to a new knowledge in the literature. This paper presents a conceptual approach based on six stages. In each stage, key enabling technologies and strategies are introduced, the common challenges, implementation tips and case studies of industrial applications are discussed to potentially assist in a successful adoption. The significance of the proposed roadmap serve as a strategic practical tool for rapid adoption of Industry 4.0 technologies for smart manufacturing and to bridge the gap between the advanced technologies and their application in manufacturing industry, especially for SMEs.


2021 ◽  
Vol 9 (3) ◽  
pp. 338
Author(s):  
Qingcai Wu ◽  
Yunsheng Mao ◽  
Jianxun Chen ◽  
Chong Wang

Digital twin has aroused extensive attention of international academia and industry to support future interaction with the physical and virtual world. Although the research and application of digital twin spring up continuously, the concept in the manufacturing domain remains in its infancy. In this context, this paper first reviews the applications of digital twins for intelligent manufacturing. Then it presents an innovative application framework of a digital twin-driven ship intelligent manufacturing system and analyzes its operation mechanism. The application framework of a digital twin-driven ship intelligent manufacturing system mainly includes five parts: the physical layer, model layer, data layer, system layer, and application layer. Finally, key enabling techniques, as well as a case study in a pipe machining production line, are constructed and studied to validate the proposed approach. Meanwhile, system design and implementation, the twin modeling construction, application process, and implementation effect of the pipe machining production line are described in detail to provide a reference for enterprises.


Author(s):  
Sihan Huang ◽  
Guoxin Wang ◽  
Dong Lei ◽  
Yan Yan

AbstractProduct development should cover product design, validation, and manufacturing. In traditional product development, physical validation based on physical trial manufacturing is the key step to confirm the design scheme before physical manufacturing. However, physical validation is costly and inefficient, which could be the main obstacle to achieving rapid product development. The emergence of digital twin provides an opportunity to accelerate product development by eliminating physical validation toward digital validation in the smart manufacturing era. Therefore, a framework of rapid product development based on digital twin is proposed in this paper. During product development, the new product is designed according to the new requirements in the virtual space, in which the existing digital twins of products can be referenced. Then, an ultrahigh-fidelity virtual manufacturing system is constructed for digital trial manufacturing based on the digital twin of the manufacturing system and the design scheme of the new product. An ultrahigh-fidelity digital prototype can be obtained from digital trial manufacturing for digital validation. The new product validation is executed on the digital prototype to test its performance. The digital validation results can be used to improve the design scheme of the new product and boost the corresponding manufacturing processes. In addition, the core characteristics and key technologies of rapid product development based on digital twin are discussed. Finally, a case study is presented to implement the proposed framework and to show the effectiveness of accelerating product development.


Author(s):  
Yan Douxi ◽  
Liu Qiang ◽  
Jiewu Leng ◽  
Zhang Ding ◽  
Rongli Zhao ◽  
...  

Abstract The mass personalization paradigm requires manufacturing enterprises to adapt to market changes quickly to meet customer demands. It also imposes higher requirements for designing intelligent production lines. Based on the digital twin (DT) technology, a rapid customized design method is proposed for developing new board-type furniture production lines. The DT has the characteristics of interactive virtual-reality mapping and fusion. It could provide design guidance and decision-support services in the design phase, yield the engineering analyzing ability to solve coupled problems, and finally generate the authoritative design scheme of the manufacturing system. A production line design platform is developed based on the DT model, which can parallelize the design process and reduce the design cycle. The parallel control between the physical world and digital space is achieved by establishing the DT network and perceiving the status of the physical equipment. Five key enabling technologies are introduced to provide the theoretical fundamentals for implementing the DT-based manufacturing system design approach. A board-type furniture production line is presented as a case study to verify the effectiveness of the method.


Author(s):  
Fei Tao ◽  
Yongping Zhang ◽  
Ying Cheng ◽  
Jiawei Ren ◽  
Dongxu Wang ◽  
...  

2021 ◽  
Vol 60 ◽  
pp. 176-201
Author(s):  
Yepeng Fan ◽  
Jianzhong Yang ◽  
Jihong Chen ◽  
Pengcheng Hu ◽  
Xiaoyu Wang ◽  
...  

2021 ◽  
Vol 13 (10) ◽  
pp. 5495
Author(s):  
Mihai Andronie ◽  
George Lăzăroiu ◽  
Roxana Ștefănescu ◽  
Cristian Uță ◽  
Irina Dijmărescu

With growing evidence of the operational performance of cyber-physical manufacturing systems, there is a pivotal need for comprehending sustainable, smart, and sensing technologies underpinning data-driven decision-making processes. In this research, previous findings were cumulated showing that cyber-physical production networks operate automatically and smoothly with artificial intelligence-based decision-making algorithms in a sustainable manner and contribute to the literature by indicating that sustainable Internet of Things-based manufacturing systems function in an automated, robust, and flexible manner. Throughout October 2020 and April 2021, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “Internet of Things-based real-time production logistics”, “sustainable smart manufacturing”, “cyber-physical production system”, “industrial big data”, “sustainable organizational performance”, “cyber-physical smart manufacturing system”, and “sustainable Internet of Things-based manufacturing system”. As research published between 2018 and 2021 was inspected, and only 426 articles satisfied the eligibility criteria. By taking out controversial or ambiguous findings (insufficient/irrelevant data), outcomes unsubstantiated by replication, too general material, or studies with nearly identical titles, we selected 174 mainly empirical sources. Further developments should entail how cyber-physical production networks and Internet of Things-based real-time production logistics, by use of cognitive decision-making algorithms, enable the advancement of data-driven sustainable smart manufacturing.


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