Challenges and Potentials of Digital Twins and Industry 4.0 in Product Design and Production for High Performance Products

Wagner, Raphael; Schleich, Benjamin; Haefner, Benjamin; Kuhnle, Andreas; Wartzack, Sandro; Lanza, Gisela

doi:10.1016/j.procir.2019.04.219

Cited by 116 publications

(43 citation statements)

References 24 publications

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“…As there are a plethora of DT models and architectures available in the literature, there is a need for defining a consistent framework for DT throughout the industry that includes shared and mutual understanding of interfaces and standardization for uniformity together with efficient design of data flow to make accessibility of data easier without compromising its security [100]. Standardizing models, interfaces, protocols, and data is essential for efficient third-party communication, product and human safety, data security, and integrity, especially in industries such as aerospace, automobile, healthcare, etc.…”

Section: Lack Of Standards and Regulationsmentioning

confidence: 99%

Digital Twin: Origin to Future

Singh

Fuenmayor

Hinchy

et al. 2021

ASI

423

114

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Digital Twin (DT) refers to the virtual copy or model of any physical entity (physical twin) both of which are interconnected via exchange of data in real time. Conceptually, a DT mimics the state of its physical twin in real time and vice versa. Application of DT includes real-time monitoring, designing/planning, optimization, maintenance, remote access, etc. Its implementation is expected to grow exponentially in the coming decades. The advent of Industry 4.0 has brought complex industrial systems that are more autonomous, smart, and highly interconnected. These systems generate considerable amounts of data useful for several applications such as improving performance, predictive maintenance, training, etc. A sudden influx in the number of publications related to ‘Digital Twin’ has led to confusion between different terminologies related to the digitalization of industries. Another problem that has arisen due to the growing popularity of DT is a lack of consensus on the description of DT as well as so many different types of DT, which adds to the confusion. This paper intends to consolidate the different types of DT and different definitions of DT throughout the literature for easy identification of DT from the rest of the complimentary terms such as ‘product avatar’, ‘digital thread’, ‘digital model’, and ‘digital shadow’. The paper looks at the concept of DT since its inception to its predicted future to realize the value it can bring to certain sectors. Understanding the characteristics and types of DT while weighing its pros and cons is essential for any researcher, business, or sector before investing in the technology.

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Section: Lack Of Standards and Regulationsmentioning

confidence: 99%

Digital Twin: Origin to Future

Singh

Fuenmayor

Hinchy

et al. 2021

ASI

423

114

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“…I followed the recently consolidated conceptualization of digital twins proposed by Wagner et al [ 11 ]. It reflects the nature of CPS as a digital twin that consists of respective parts physical and digital product and “connected data that tie and indissolubly connect the physical and virtual product”.…”

Section: Digital Twins As Behavioral Design Encapsulationsmentioning

confidence: 99%

“…Linking product and production twins into digital production twins affects the product engineering process, even addressing human control and interaction issues. Wagner et al [ 11 ] envision enriched use of digital twins along product engineering to ensure the coherent and efficient flow of information. They also recognize the lack of a consistent framework for holistic application scenarios, particularly addressing the integration of product designers’ work and production planner concepts.…”

Section: Digital Twins As Behavioral Design Encapsulationsmentioning

confidence: 99%

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Digital Twin Generation: Re-Conceptualizing Agent Systems for Behavior-Centered Cyber-Physical System Development

Stary

2021

Sensors

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Cyber-Physical Systems (CPS) form the new backbone of digital ecosystems. Upcoming CPS will be operated on a unifying basis, the Internet of Behaviors (IoB). It features autonomous while federated CPS architectures and requires corresponding behavior modeling for design and control. CPS design and control involves stakeholders in different roles with different expertise accessing behavior models, termed Digital twins. They mirror the physical CPS part and integrate it with the digital part. Representing role-specific behaviors and provided with automated execution capabilities Digital twins facilitate dynamic adaptation and (re-)configuration. This paper proposes to conceptualize agent-based design for behavior-based Digital twins through subject-oriented models. These models can be executed and, thus, increase the transparency at design and runtime. Patterns recognizing environmental factors and operation details facilitate the configuration of CPS. Subject-oriented runtime support enables dynamic adaptation and the federated use of CPS components.

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“…Wagner et.al. [14] tried to determine a consistent structure for the holistic use of digital twins in the whole process of product development. Zakoldaev et.al.…”

Section: Product Design In Industry 40mentioning

confidence: 99%

Prioritizing the Factors for Customer-Oriented New Product Design in Industry 4.0

Erdoğan

Bilişik

2020

Sakarya University Journal of Science

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Customer-oriented new product design is one of the most important processes in the production environment to improve product quality and reliability and maximize their productivity. It is also necessary to consider customer expectations in this process for an effective design. In this paper, we present a methodology which is called Pythagorean Fuzzy Analytic Hierarchy Process (PF-AHP) for prioritizing criteria which should be considered for an efficient customer-oriented new product design in Industry 4.0 transition primarily. We use Pythagorean Fuzzy Sets (PFSs) to allow experts to make more flexible evaluations and handle the uncertain and vague information in a wider way. We determine five main and eighteen sub-criteria that affect the new product design process and after applying PF-AHP, we find that the most important main-criterion determined as "Production" and sub-criterion determined as "Return on Investment".

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Challenges and Potentials of Digital Twins and Industry 4.0 in Product Design and Production for High Performance Products

Cited by 116 publications

References 24 publications

Digital Twin: Origin to Future

Digital Twin: Origin to Future

Digital Twin Generation: Re-Conceptualizing Agent Systems for Behavior-Centered Cyber-Physical System Development

Prioritizing the Factors for Customer-Oriented New Product Design in Industry 4.0

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