Big data driven Hierarchical Digital Twin Predictive Remanufacturing paradigm: Architecture, control mechanism, application scenario and benefits

Wang, Yankai; Wang, Shilong; Yang, Bo; Zhu, Lingzi; Liu, Feng

doi:10.1016/j.jclepro.2019.119299

Cited by 96 publications

(33 citation statements)

References 31 publications

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“…Surprisingly, the results demonstrated that both the concept of big data and its characteristics are known more widely within the industry (Section 5.1), which agrees with much of the literature indicating that in recent years there has been an exponential increase in the use of both the term and the technology (Wang et. al., 2020).…”

Section: Discussionsupporting

confidence: 81%

Awareness of Big Data concept in the Dominican Republic construction industry: an empirical study

Renukappa

Suresh

Reyes-Veras

2021

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Purpose The construction industry, being one of the main activities in the ever-demanding need for technology developments, sometimes falls short of other industries in terms of implementation. The adoption of Big Data (BD) in industries such as health and retail has had positive impacts in aspects such as decision-making processes and forecasting trends that allow planning some future business movements. Hence, the question of whether these results can be imitated in the construction industry. Therefore, this paper aims to address the level of awareness identified as a first step towards implementation of the BD concept within the construction industry in the Dominican Republic (DR). Design/methodology/approach As little to no information exist on the subject; the selected approach to perform this research was qualitative methodology; 21 semi-structured interviews were studied using situational awareness. Four levels of awareness were developed based on the Endsley’s Situation Awareness model. Findings The results showed that nearly 95% of the interviewees had either no knowledge or very basic awareness of the BD requirements or intermediate awareness, but only 5% had applied BD concepts in the construction industry. Originality/value This study shows the gaps that exist in the understanding and implementation of BD concepts in the DR construction industry. This paper establishes the need to develop continuous professional development programmes for construction professionals and a need to update curriculum in construction-related education.

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Section: Discussionsupporting

confidence: 81%

Awareness of Big Data concept in the Dominican Republic construction industry: an empirical study

Renukappa

Suresh

Reyes-Veras

2021

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“…However, the major problems in implementing a remanufacturing strategy result from the extreme uncertainty and variability of the remanufacturing environment (Ijomah et al, 1999). Wang et al (2020) also observe the lack of product multi-life-cycle remanufacturing process tracking management as particularly problematic. In this sub-cluster authors (Wang and Wang, 2019;Wang et al, 2020) approach solutions to the ongoing problems from a product lifecycle management perspective, discussing different permutations as to how this is achievable by employing disruptive technologies such as cyber-physical systems and digital twins.…”

Section: Alternative Manufacturingmentioning

confidence: 99%

The application of digital twin technology in operations and supply chain management: a bibliometric review

Bhandal

Meriton

Kavanagh³

et al. 2022

SCM

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Purpose The application of digital twins to optimise operations and supply chain management functions is a bourgeoning practice. Scholars have attempted to keep pace with this development initiating a fast-evolving research agenda. The purpose of this paper is to take stock of the emerging research stream identifying trends and capture the value potential of digital twins to the field of operations and supply chain management. Design/methodology/approach In this work we employ a bibliometric literature review supported by bibliographic coupling and keyword co-occurrence network analysis to examine current trends in the research field regarding the value-added potential of digital twin in operations and supply chain management. Findings The main findings of this work are the identification of four value clusters and one enabler cluster. Value clusters are comprised of articles that describe how the application of digital twin can enhance supply chain activities at the level of business processes as well as the level of supply chain capabilities. Value clusters of production flow management and product development operate at the business processes level and are maturing communities. The supply chain resilience and risk management value cluster operates at the capability level, it is just emerging, and is positioned at the periphery of the main network. Originality/value This is the first study that attempts to conceptualise digital twin as a dynamic capability and employs bibliometric and network analysis on the research stream of digital twin in operations and supply chain management to capture evolutionary trends, literature communities and value-creation dynamics in a digital-twin-enabled supply chain.

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“…Following these technical advancements, manufacturing industry has broadly implemented Digital Twins in the past few years for specific tasks, for example, the monitoring and the predictive maintenance of long-lasting goods in service [5]. In this sense, the twinning of the existing physical environment has got a particular importance.…”

Section: Introductionmentioning

confidence: 99%

Automated Generation of a Digital Twin of a Process Plant by Using 3D Scan and Artificial Intelligence

Grau¹,

Korol²,

Lützenberger³

et al. 2021

Advances in Transdisciplinary Engineering

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The simulation of production processes using a Digital Twin is a promising tool for predictive planning, analysis of existing systems or process-parallel monitoring. In the process industry, the concept of Digital Twin provides significant support for process optimization. The generation of the Digital Twin of an already existing plant is a major challenge – in particular for small and medium-sized enterprises. In this sense, the twinning of the existing physical environment has got a particular importance due to high effort. Shape segmentation from unstructured (e.g. point cloud data) is a core step of the digital twinning process for industrial facilities. This is an inherent issue of Product Lifecycle Management how to acquire data of existing goods. The practice of Digital Twin is described based on object recognition by using methods of Machine Learning. The exploration of the pipeline semantics presents a particular challenge. The highly automated procedure for the generation of Digital Twin is described based on a use case of a biogas plant. Commercial deployment, pitfalls, drawbacks and potential for further developments are further explored.

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Big data driven Hierarchical Digital Twin Predictive Remanufacturing paradigm: Architecture, control mechanism, application scenario and benefits

Cited by 96 publications

References 31 publications

Awareness of Big Data concept in the Dominican Republic construction industry: an empirical study

Awareness of Big Data concept in the Dominican Republic construction industry: an empirical study

The application of digital twin technology in operations and supply chain management: a bibliometric review

Automated Generation of a Digital Twin of a Process Plant by Using 3D Scan and Artificial Intelligence

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