A data-driven reversible framework for achieving Sustainable Smart product-service systems

Li, Xinyu; Wang, Zuoxu; Chen, Chun‐Hsien; Zheng, Pai

doi:10.1016/j.jclepro.2020.123618

Cited by 91 publications

(61 citation statements)

References 45 publications

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“…The trend from the analysis of this study reveals that most of the servitisation literature discusses this from a functional perspective (see Table 6) [14,56]. Servitisation is seen as a path that enhances the downstream opportunities by providing autonomous services to their customers [1,62]…”

mentioning

confidence: 88%

“…The most common understanding of servitisation is that it brings competitive and strategic aids for implementing this innovated BM [61]. Several research papers have deliberated a relationship of servitisation within the manufacturing industry [1,18,62], and further researches in this domain have significantly increased in the past two decades [18,61]. There are different definitions for the term servitisation; we have picked the one more relevant to our research studies given in Table 2.…”

Section: Servitisationmentioning

confidence: 99%

“…For example, 3D printers are frequently presented as additive manufacturing (as one of the I4.0 technologies). This technology supports servitisation because firms take them on lease from a third party instead of buying them, maximising the value of exploiting and reallocating cyber-physical resources [62,65].…”

Section: Linking I40 and Servitisationmentioning

confidence: 99%

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Towards a Conceptual Development of Industry 4.0, Servitisation, and Circular Economy: A Systematic Literature Review

et al. 2021

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Industry 4.0 (I4.0) technologies have been highlighted in recent literature as enablers of servitisation. Simultaneously, businesses are advised to implement a circular economy (CE) to bring new opportunities. However, it is pertinent to mention that little attention has been given to assess the role of I4.0 in adopting the CE and servitisation in a fully integrated manner. This research fills this gap by developing a conceptual framework through a systematic literature review of 139 studies investigating the relationship between the I4.0, CE, and servitisation. This study identifies the impact of these variables on a firm’s operational and financial performance (revenue stream, growth, and profitability). Our research findings advocate that adopting I4.0 technologies to the business and manufacturing model enables sustainability, energy and resource efficiency while enhancing performance and offering innovative products through smart services. Thus, firms must systematically adopt I4.0 technologies to support a CE model that creates value through servitisation. This study identifies the research gaps that are unexplored for practitioners and future researchers while providing insight into the role of I4.0 in implementing CE in the servitisation business model.

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confidence: 88%

Section: Servitisationmentioning

confidence: 99%

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Towards a Conceptual Development of Industry 4.0, Servitisation, and Circular Economy: A Systematic Literature Review

et al. 2021

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“…To retain the competitiveness in the fierce market, not only pursuing cost-effective design schemes in the design of AAL but also comprehensively considering the human-machine relationship, flexibility and other indicators in the design scheme. Therefore, as the check phase, design scheme evaluation aims to balance the cost and performance by measuring and optimizing the proposed design schemes (Li et al , 2021). Based on the full consideration of customer preferences, 5 criteria are first proposed for solution evaluation, namely, minimize the economic for operation ( E ); maximize the flexible of AAL ( F ); maximize the effectiveness of station ( SE ); maximize the advancement for assembly resource ( RA ); and maximize the worker satisfaction in human–machine relationship ( WS ).…”

Section: Framework Of Knowledge-enabled Digital Twin For Smart Design For Aircraft Assembly Linementioning

confidence: 99%

Knowledge-enabled digital twin for smart designing of aircraft assembly line

Chang

Jia

et al. 2021

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Purpose The purpose of this paper is to provide a knowledge-enabled digital twin for smart design (KDT-SD) of aircraft assembly line (AAL) to enhance the AAL efficiency, performance and visibility. Modern AALs usually need to have capabilities such as digital-physical interaction and self-evaluation that brings significant challenges to traditional design method for AAL. The digital twin (DT) combining with reusable knowledge, as the key technologies in this framework, is introduced to promote the design process by configuring, understanding and evaluating design scheme. Design/methodology/approach The proposed KDT-SD framework is designed with the introduction of DT and knowledge. First, dynamic design knowledge library (DDK-Lib) is established which could support the various activities of DT in the entire design process. Then, the knowledge-driven digital AAL modeling method is proposed. At last, knowledge-based smart evaluation is used to understand and identify the design flaws, which could further improvement of the design scheme. Findings By means of the KDT-SD framework proposed, it is possible to apply DT to reduce the complexity and discover design flaws in AAL design. Moreover, the knowledge equips DT with the capacities of rapid modeling and smart evaluation that improve design efficiency and quality. Originality/value The proposed KDT-SD framework can provide efficient design of AAL and evaluate the design performance in advance so that the feasibility of design scheme can be improved as much as possible.

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“…Engineers constantly review previous knowledge and learn new skills while engineering problem-solving, usually accompanied by multiple knowledge transfers (John et al, 2019 ; Vieira et al, 2020 ). The efficiency of knowledge transfer usually depends on the individual cognitive level when engineers solve specific problems (Li et al, 2017 , 2021b ). The cognitive level is concerned with the mastery of knowledge, which is a concept in cognitive psychology based on the cognitive structure of the human brain.…”

Section: Introductionmentioning

confidence: 99%

Functional Brain Network Analysis of Knowledge Transfer While Engineering Problem-Solving

Wang

Jiang

et al. 2021

Front. Hum. Neurosci.

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As a complex cognitive activity, knowledge transfer is mostly correlated to cognitive processes such as working memory, behavior control, and decision-making in the human brain while engineering problem-solving. It is crucial to explain how the alteration of the functional brain network occurs and how to express it, which causes the alteration of the cognitive structure of knowledge transfer. However, the neurophysiological mechanisms of knowledge transfer are rarely considered in existing studies. Thus, this study proposed functional connectivity (FC) to describe and evaluate the dynamic brain network of knowledge transfer while engineering problem-solving. In this study, we adopted the modified Wisconsin Card-Sorting Test (M-WCST) reported in the literature. The neural activation of the prefrontal cortex was continuously recorded for 31 participants using functional near-infrared spectroscopy (fNIRS). Concretely, we discussed the prior cognitive level, knowledge transfer distance, and transfer performance impacting the wavelet amplitude and wavelet phase coherence. The paired t-test results showed that the prior cognitive level and transfer distance significantly impact FC. The Pearson correlation coefficient showed that both wavelet amplitude and phase coherence are significantly correlated to the cognitive function of the prefrontal cortex. Therefore, brain FC is an available method to evaluate cognitive structure alteration in knowledge transfer. We also discussed why the dorsolateral prefrontal cortex (DLPFC) and occipital face area (OFA) distinguish themselves from the other brain areas in the M-WCST experiment. As an exploratory study in NeuroManagement, these findings may provide neurophysiological evidence about the functional brain network of knowledge transfer while engineering problem-solving.

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A data-driven reversible framework for achieving Sustainable Smart product-service systems

Cited by 91 publications

References 45 publications

Towards a Conceptual Development of Industry 4.0, Servitisation, and Circular Economy: A Systematic Literature Review

Towards a Conceptual Development of Industry 4.0, Servitisation, and Circular Economy: A Systematic Literature Review

Knowledge-enabled digital twin for smart designing of aircraft assembly line

Functional Brain Network Analysis of Knowledge Transfer While Engineering Problem-Solving

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