A Review of Interoperability Standards for Industry 4.0.

Burns, Thomas; Cosgrove, John; Doyle, Frank

doi:10.1016/j.promfg.2020.01.083

Cited by 56 publications

(38 citation statements)

References 20 publications

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“…Besides a formal and machine-readable resource description created by a provider, they share the functionality for potential consumers to discover such resource descriptions and access the resources. As industry 4.0 is about optimization on a large scale, interoperability not only within a factory or organization but along the whole value chain is essential and should be addressed globally [20,21]. Achieving interoperability on a global level requires formal standardization.…”

Section: Introductionmentioning

confidence: 99%

“…Having multiple competing standards solving the same problem in different ways without aligning with each other massively hinders interoperability. As interoperability is the key requirement of industry 4.0 [21,22], this is an actual threat for the further development and success of industry 4.0. Previous work focuses on either the IoT or the DT domain or addresses the IoT only as a source of data for DTs, ignoring the fact that the domains actually overlap in functionality.…”

Section: Introductionmentioning

confidence: 99%

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Digital Twin and Internet of Things—Current Standards Landscape

2020

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Industry 4.0 is revolutionizing industrial production by bridging the physical and the virtual worlds and further improving digitalization. Two essential building blocks in industry 4.0 are digital twins (DT) and the internet of things (IoT). While IoT is about connecting resources and collecting data about the physical world, DTs are the virtual representations of resources organizing and managing information and being tightly integrated with artificial intelligence, machine learning and cognitive services to further optimize and automate production. The concepts of DTs and IoT are overlapping when it comes to describing, discovering and accessing resources. Currently, there are multiple DT and IoT standards covering these overlapping aspects created by different organizations with different backgrounds and perspectives. With regard to interoperability, which is presumably the most important aspect of industry 4.0, this barrier needs to be overcome by consolidation of standards. The objective of this paper is to investigate current DT and IoT standards and provide insights to stimulate this consolidation. Overlapping aspects are identified and a classification scheme is created and applied to the standards. The results are compared, aspects with high similarity or divergence are identified and a proposal for stimulating consolidation is presented. Consensus between standards are found regarding the elements a resource should consist of and which serialization format(s) and network protocols to use. Controversial topics include which query language to use for discovery as well as if geo-spatial, temporal and historical data should be explicitly supported.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Digital Twin and Internet of Things—Current Standards Landscape

2020

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“…Stakeholder management considering and external accountability, transparency and information sharing, and cooperation with other supply chain parts to enhance sustainability of the whole chain via shared strategies [48][49][50][51] Commitment to the transparency of the supply chain…”

Section: Governance Data Managementmentioning

confidence: 99%

Interval Type-2 Fuzzy Super SBM Network DEA for Assessing Sustainability Performance of Third-Party Logistics Service Providers Considering Circular Economy Strategies in the Era of Industry 4.0

et al. 2021

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Stakeholders are increasingly aware of the aspect of sustainability, and the fact that the circular economy facilitates the achievement of sustainable development goals. They place pressure on supply chains to become sustainable, and for this reason, third-party logistics (3PL) service providers, as specialized professionals, play a vital role in sustainable supply chain management. Although developments in technology in the era of Industry 4.0 have been effective at directing 3PLs along the path towards sustainability, integrated management of forward and reverse logistics systems in order to achieve a circular economy and to become sustainable remains a problem, even in developed countries. However, benchmarking and using the experiences of others can help to speed up this path at a minimal cost. An interval type-2 fuzzy super-slack-based measure network DEA was developed to make such benchmarking possible. Governance style, staff behavior, environmental management systems, and social elements are considered, alongside the principles of the circular economy, in order to compare the sustainability performance of 17 3PLs with respect to different aspects through the application of the developed DEA model. Proper benchmarking with respect to strategies and operations of the 3PLs that are recognized as efficient makes it possible for these 3PLs to overcome obstacles and progress at a lower cost. The results show that 3PLs do not have a comprehensive sustainability strategy that is coordinated with an overall vision of the total supply chain. An investigation into the development of a framework with multiple steps for the guidance of 3PLs, as well as the whole supply chain, towards sustainability in the Industry 4.0 era would be a fruitful next study.

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“…Despite efforts in Industry 4.0, smart manufacturing and related paradigms standardization [11], [12] the integration challenges have not been solved. The challenges are not only related to data interoperability produced by the heterogeneous devices and systems [13] but also to interoperability of system architectures [5] and dynamic compositions in their interplay [2] as well as whole ecosystems.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Edge and Cloud Service Integration for Industrial IoT and Production Monitoring Applications of Industrial Cyber-Physical Systems

Hästbacka

Halme

Barna

et al. 2022

IEEE Trans. Ind. Inf.

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Industrial cyber-physical systems rely increasingly on data from IoT devices and other systems as continuously emerging use cases implement new intelligent features. Edge computing can be seen as an extension of the cloud in close physical proximity, in which some of the typical cloud computing loads are beneficial to run. This paper studies data analytics application development for integration of industrial IoT data and composition of application services executed on edge and cloud. A solution is designed to support heterogeneous hardware and run-time platforms, and focuses on the service layer that enables flexible orchestration of data flows and dynamic service compositions. The unified model and system architecture implemented, using the open Arrowhead Framework model, is verified through two representative industrial use cases.

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A Review of Interoperability Standards for Industry 4.0.

Cited by 56 publications

References 20 publications

Digital Twin and Internet of Things—Current Standards Landscape

Digital Twin and Internet of Things—Current Standards Landscape

Interval Type-2 Fuzzy Super SBM Network DEA for Assessing Sustainability Performance of Third-Party Logistics Service Providers Considering Circular Economy Strategies in the Era of Industry 4.0

Dynamic Edge and Cloud Service Integration for Industrial IoT and Production Monitoring Applications of Industrial Cyber-Physical Systems

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