Digital twin-driven rapid reconfiguration of the automated manufacturing system via an open architecture model

Leng, Jiewu; Liu, Qiang; Ye, Shide; Jing, Jianbo; Wang, Yan; Zhang, Chaoyang; Ding, Zhizhong; Chen, Xin

doi:10.1016/j.rcim.2019.101895

Cited by 247 publications

(85 citation statements)

References 39 publications

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“…Moreover, many students have designed and built simulations of cyber-physical systems, following the IEC 61131-3 standard [ 43 ], focusing on solutions supporting industrial and general public customers during the pandemic. During the pandemic, the development of simulated systems by the students introduced them the concept of “digital twins” [ 44 ], which allows, e.g., designing of the configuration, motion, control, and optimization model of a flow-type smart manufacturing system [ 45 ] and then a possibly rapid reconfiguration of an automated manufacturing system via an open architecture model [ 46 ].…”

Section: Resultsmentioning

confidence: 99%

Training the Next Industrial Engineers and Managers about Industry 4.0: A Case Study about Challenges and Opportunities in the COVID-19 Era

Benis

Nelke

Winokur

2021

Sensors

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Training the next generation of industrial engineers and managers is a constant challenge for academia, given the fast changes of industrial technology. The current and predicted development trends in applied technologies affecting industry worldwide as formulated in the Industry 4.0 initiative have clearly emphasized the needs for constantly adapting curricula. The sensible socioeconomic changes generated by the COVID-19 pandemic have induced significant challenges to society in general and industry. Higher education, specifically when dealing with Industry 4.0, must take these new challenges rapidly into account. Modernization of the industrial engineering curriculum combined with its migration to a blended teaching landscape must be updated in real-time with real-world cases. The COVID-19 crisis provides, paradoxically, an opportunity for dealing with the challenges of training industrial engineers to confront a virtual dematerialized work model which has accelerated during and will remain for the foreseeable future after the pandemic. The paper describes the methodology used for adapting, enhancing, and evaluating the learning and teaching experience under the urgent and unexpected challenges to move from face-to-face university courses distant and online teaching. The methodology we describe is built on a process that started before the onset of the pandemic, hence in the paper we start by describing the pre-COVID-19 status in comparison to published initiatives followed by the real time modifications we introduced in the faculty to adapt to the post-COVID-19 teaching/learning era. The focus presented is on Industry 4.0. subjects at the leading edge of the technology changes affecting the industrial engineering and technology management field. The manuscript addresses the flow from system design subjects to implementation areas of the curriculum, including practical examples and the rapid decisions and changes made to encompass the effects of the COVID-19 pandemic on content and teaching methods including feedback received from participants.

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Section: Resultsmentioning

confidence: 99%

Training the Next Industrial Engineers and Managers about Industry 4.0: A Case Study about Challenges and Opportunities in the COVID-19 Era

Benis

Nelke

Winokur

2021

Sensors

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“…Developing and implementing DT solutions builds a foundation to realize SM. For instance, DTs are used for rapid individualized design of automated flow-shop manufacturing systems (see, e.g., [16]); automatic reconfiguration in the case of design deficiencies (see, e.g., [17]) or disruptions during production (see, e.g., [7]); and predictive maintenance to monitor and predict the performance and condition of equipment during operation (see, e.g., [18]). A literature search of DT definitions and use-cases could be found in [19]- [21].…”

Section: A Digital Twinmentioning

confidence: 99%

A Methodology to Develop and Implement Digital Twin Solutions for Manufacturing Systems

et al. 2021

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Digital Twin (DT) is an emerging technology that has recently been cited as an underpinning element of the digital transformation. DTs are commonly defined as digital replicas of components, systems, products, and services that receive data from the field to support intelligent decision-making. Although several frameworks for DT application in manufacturing have been proposed, there is no systematic methodology in the literature that supports the development of scalable, reusable, interoperable, interchangeable, and extensible DT solutions, while taking into account specific manufacturing environment needs and conditions. This paper introduces a DT solution development methodology as a generic procedure for analyzing and developing DTs for manufacturing systems. The methodology is based on the well-known System Development Life Cycle (SDLC) process and takes into consideration: (1) the specificity of DT characteristics and requirements, (2) an understanding of the manufacturing context in which the DTs will operate, and (3) the object-oriented aspects required to achieve DT capabilities of scalability, reusability, interoperability, interchangeability, and extensibility. A case study illustrates the advantages of the proposed methodology in supporting manufacturing DT solutions.

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“…Figure 6 compares the linearized natural frequencies of the 3D and 1D models. These natural frequencies have been computed as f = |λ| 2π (19) where λ are the eigenvalues corresponding to second order systems of the process matrix linearized at each time step. These natural frequencies are plotted against the cable's length, as this is the main cause for their change.…”

Section: A Model Reductionmentioning

confidence: 99%

“…This information may thus provide a significant added value in the management of different assets. For instance, aiding in the rapid qualification of manufactured parts [17], providing maintenance suggestions [18], or suggesting manufacturing plant reconfiguration to ramp-up or to improve manufacturing quality [19]. Although the DT is a promising concept for several fields, there are many conceptual ideas, but few practical application examples.…”

Section: Introductionmentioning

confidence: 99%

A Digital Twin for Operational Evaluation of Vertical Transportation Systems

et al. 2020

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Digital twin-driven rapid reconfiguration of the automated manufacturing system via an open architecture model

Cited by 247 publications

References 39 publications

Training the Next Industrial Engineers and Managers about Industry 4.0: A Case Study about Challenges and Opportunities in the COVID-19 Era

Training the Next Industrial Engineers and Managers about Industry 4.0: A Case Study about Challenges and Opportunities in the COVID-19 Era

A Methodology to Develop and Implement Digital Twin Solutions for Manufacturing Systems

A Digital Twin for Operational Evaluation of Vertical Transportation Systems

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