Intelligent Maintenance of Complex Equipment Based on Blockchain and Digital Twin Technologies

Chen, Qiuan; Zhu, Zhenwei; Si, Shubin; Cai, Zhiqiang

doi:10.1109/ieem45057.2020.9309898

Cited by 12 publications

(10 citation statements)

References 7 publications

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“…Production equipment is expanding further into the realm of new digital and intelligent progress due to the improvement of present machinery systems and research and development (Chen et al, 2020). In natural industrial environments, modern equipment is frequently used to accomplish crucial jobs; when an accident occurs, the repercussions can be rather severe (Chen et al, 2020). Maintenance can potentially reduce the amount of time spent on non-value-adding activities in production by as much as 40% (Ahuja and Khamba, 2008).…”

Section: Introductionmentioning

confidence: 99%

“…In this line, significant possibilities for advancing maintenance to a new level have arisen due to Industry 4.0 technology and the fast evolution of Cyber-Physical Systems (Albano et al, 2019). Thus, it is essential to make the most of today's technical tools for implementing smart maintenance of complicated equipment to keep it running so it accomplishes its targets (Chen et al, 2020). However, owing to the rapid progress and use of the Internet and digital technology after 1995, product maintenance focused on the entire lifespan emerged (Si et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…The unique features of blockchain make it essential for data transparency, sharing and security in the system's data flow, for which it has become necessary (Javaid et al, 2021). BCT is used to build a life-cycle information management framework for advanced machinery (Chen et al, 2020). BCT helps to map physical equipment and virtual digital simulations and then carry out state monitoring, fault detection and life prediction of complex equipment, which allows more effective operations and maintenance of the machinery (Chen et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…BCT is used to build a life-cycle information management framework for advanced machinery (Chen et al, 2020). BCT helps to map physical equipment and virtual digital simulations and then carry out state monitoring, fault detection and life prediction of complex equipment, which allows more effective operations and maintenance of the machinery (Chen et al, 2020). Therefore, implementing BCT (especially at the shop floor level) may enhance the outcomes of maintenance management approaches, such as TPM practices.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Blockchain technology and circular economy in the environment of total productive maintenance: a natural resource-based view perspective

Samadhiya

Agrawal

Garza‐Reyes

2023

JMTM

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PurposeTotal Productive Maintenance (TPM) could act as a practical approach to offer sustainability deliverables in manufacturing firms aligning with the natural resource-based view (NRBV) theory's strategic capabilities: pollution prevention, product stewardship and sustainable development. Also, the emergence of Blockchain Technology (BCT) and Circular Economy (CE) are proven to deliver sustainable outcomes in the past literature. Therefore, the present research examines the relationship between BCT and CE and TPM's direct and mediation effect through the lens of NRBV theory.Design/methodology/approachThe current study proposes a conceptual framework to examine the relationship between BCT, CE and TPM and validates the framework through the Partial Least Squares Structural Equation Modeling. Responses from 316 Indian manufacturing firms were collected to conduct the analysis.FindingsThe investigation outcomes indicate that BCT positively influences CE and TPM and that TPM has a significant positive impact on CE under the premises of NRBV theory. The results also suggest that TPM partially mediates the relationship between BCT and CE.Research limitations/implicationsThis research fills a gap in the literature by investigating the effect of BCT and TPM on CE within the framework of the NRBV theory. It explores the link between BCT, TPM and CE under the NRBV theory's strategic capabilities and TPM mediation.Practical implicationsThe positive influence of TPM and BCT on CE could initiate the amalgamation of BCT-TPM, improving the longevity of production equipment and products and speeding up the implementation of CE practices.Originality/valueThis research fills a gap in the literature by investigating the effect of BCT and TPM on CE within the framework of the NRBV theory. It explores the link between BCT, TPM and CE under the NRBV theory's strategic capabilities along with TPM mediation.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Blockchain technology and circular economy in the environment of total productive maintenance: a natural resource-based view perspective

Samadhiya

Agrawal

Garza‐Reyes

2023

JMTM

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Digital Twins Model of Industrial Production Control Management Using Deep Learning Techniques

Venkatesan,

Karthika,

Bashir

2024

Digital Twins in Industrial Production and Smart Manufacturing

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Reviewing the Application of Data Driven Digital Twins in Manufacturing Systems: A Business and Management Perspective

Badakhshan

Ball

2021

Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems

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Simulation modelling has been a widely used tool for analyzing manufacturing systems and improving their performance. Although, little attention has been paid to the application of data-driven simulation modelling of the manufacturing systems. With the development of new-generation information and digitalization technologies, more data can be collected from the manufacturing shop floor. This has paved the way for employing data-driven simulation of manufacturing systems knowns as a digital twin. This paper reviews the literature and practice on digital twins in manufacturing systems from a business and management perspective to identify the gaps and recommend avenues for future research. The results show that 2018 has been a turning point in the literature with small scale case studies of digital twins emerging independent of commercial practice. Since 2018 the digital twin literature has moved on from descriptions and conceptual frameworks to focus on one product lifecycle phase with any reference to sustainability advance being confined to energy and resource efficiency. Practice has been advanced by manufacturers and IT vendors however the definition of digital twins lacks precision for ease comparison with the literature. Future avenues for research are identified in the areas of lifecycle phases and digital model fidelity.

show abstract

Intelligent Maintenance of Complex Equipment Based on Blockchain and Digital Twin Technologies

Cited by 12 publications

References 7 publications

Blockchain technology and circular economy in the environment of total productive maintenance: a natural resource-based view perspective

Blockchain technology and circular economy in the environment of total productive maintenance: a natural resource-based view perspective

Digital Twins Model of Industrial Production Control Management Using Deep Learning Techniques

Reviewing the Application of Data Driven Digital Twins in Manufacturing Systems: A Business and Management Perspective

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