Smart Manufacturing Standardization: Reference Model and Standards Framework

Li, Qing; Jiang, Hongzhen; Tang, Qianlin; Chen, Yaotang; Li, Jun; Zhou, Jian

doi:10.1007/978-3-319-55961-2_2

Cited by 21 publications

(14 citation statements)

References 1 publication

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“…Second, financial availability and uncertainty issues should be addressed, as Horvat (2018) recommends. Finally, standardisation appears as a fundamental aspect to overcoming the challenges of Industry 4.0 implementation is the standardisation of industrialisation resulting in a network connection and information integration between different companies (Li et al, 2007;Feng et al, 2018;Gausemeier and Klocke, 2016;Vasin et al, 2018).…”

Section: Resultsmentioning

confidence: 99%

Catching the wave: Industry 4.0 in BRICS

Erro‐Garcés

Aranaz-Núñez

2020

JMTM

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PurposeThis research aims to conduct, to the best of our knowledge, the first systematic review of the implementation of Industry 4.0 in BRICS. This review facilitates the identification of main factors that affect the readiness to adopt Industry 4.0 in BRICS and the role of different agents, such as multinationals, the public sector or educative institutions.Design/methodology/approachKey publications published from 2010 to 2019 have been analysed. A total of 61 papers have been selected from the systematic review.FindingsThree factors of convergence of BRICS to developed economies in terms of Industry 4.0 are identified: (1) the public initiatives that can also result in the attraction of talent from developed countries to BRICS; (2) the role of multinationals and (3) the implication of educational institutions.Research limitations/implicationsThis review has some limitations. First, some grey literature, such as reports from non-governmental organisations and front-line practitioners' reflections, were not included. Second, only research studies in English were reviewedPractical implicationsThe heterogeneity of BRICS amongst themselves affects the implementation of Industry 4.0 policies. Therefore, public policies should differ among countries to achieve the different readiness of companies within each country. Industry 4.0 cannot be understood as a manufacturing strategy against delocalisation, as emerging countries, such as BRICS, are also aware of the potential of automation.Originality/valueBased on a systematic review, this article shows that the strategy created by Germany to increase industrial productivity has been also introduced in BRICS countries as a critical factor to improve their competitiveness.

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Section: Resultsmentioning

confidence: 99%

Catching the wave: Industry 4.0 in BRICS

Erro‐Garcés

Aranaz-Núñez

2020

JMTM

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“…On the one hand, SMIS customization helps enterprises to obtain relevant information in all aspects in time, including requirements, functions, technologies and strategies, so as to identify related activities and reduce waste of resources [8] [9]. On the other hand, the customized information system is to make overall planning and design integration of the information system according to the actual operating conditions of the enterprise and the whole supply chain [5] [47], which means that the customized information system may affect its system flexibility.…”

Section: Smis Customizationmentioning

confidence: 99%

“…The technical core of "China's intellectual manufacturing" is information technology, which is applied information technology to all links of industrial production by means of deep integration of industrialization and informationization (IOII), so as to change the traditional industrial production mode. As a big industrial country in the world with a large scale of equipment manufacturing industry, China has its own advantages [5]. With the largest number of researchers in the world, China has great potential for developing resources.…”

Section: Introductionmentioning

confidence: 99%

Customization and Performance of Service-Oriented Manufacturing Information System: The Mediating Effect of Information System Flexibility

Niu¹

2021

IIM

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The purpose of this paper is to provide empirical evidence for the validity of the relationship between service-oriented manufacturing information system (SMIS) customization and performance from three aspects: data flexibility, process flexibility and system flexibility. We select some questionnaires from the third round of High-performance manufacturing (HPM) data to construct the construct, verify the reliability and validity of the construct, extract principal components, and analyze the mediating effect by using multiple chain linear regression and structural equation model. The results show that SMIS customization has a significant impact on its performance, and this effect works through its flexibility. More specifically, it is the multiple chain mediation effect composed of data flexibility, process flexibility and system flexibility. The importance of SMIS customization and flexibility to the organization is made clear, which helps practitioners understand the internal mechanism that affects SMIS performance, so as to use limited resources to improve system performance.

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“…Here, sensors have the capability of measuring a multitude of parameters frequently and collecting plenty of data. Analysis of big data, both historical and real time, can facilitate predictions on the basis of which proactive maintenance decision making can be performed [39,40]. The e-maintenance concept can significantly address these challenges.…”

Section: Related Workmentioning

confidence: 99%

IoT meets BPM: a bidirectional communication architecture for IoT-aware process execution

et al. 2020

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Business processes are frequently executed within application systems that involve humans, computer systems as well as objects of the Internet of Things (IoT). Nevertheless, the usage of IoT technology for system supported process execution is still constrained by the absence of a common system architecture that manages the communication between both worlds. In this paper, we introduce an integrated approach for IoT-aware business process execution that exploits IoT for BPM by providing IoT data in a process-compatible way, providing an IoT data provenance framework, considering IoT data for interaction in a pre-defined process model, and providing wearable user interfaces with context-specific IoT data provision. The approach has been implemented on top of contemporary BPM modeling concepts and system technology. The introduced technique has evaluated extensively in different use cases in industry.

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Smart Manufacturing Standardization: Reference Model and Standards Framework

Cited by 21 publications

References 1 publication

Catching the wave: Industry 4.0 in BRICS

Catching the wave: Industry 4.0 in BRICS

Customization and Performance of Service-Oriented Manufacturing Information System: The Mediating Effect of Information System Flexibility

IoT meets BPM: a bidirectional communication architecture for IoT-aware process execution

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