Interoperability in Smart Manufacturing: Research Challenges

Zeid, Abe; Sundaram, Sarvesh; Moghaddam, Mohsen; Kamarthi, Sagar; Marion, Tucker J.

doi:10.3390/machines7020021

Cited by 105 publications

(49 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Finally, one of the main challenges towards the implementation and adoption of AI concepts in IT manufacturing systems is the increased need for interoperability at different levels of the manufacturing ecosystem [ 29 ]. In this context, the application of existing standards for service-oriented industrial communication infrastructure by Open Platform Communications United Architecture (OPC-UA) and for semantic data exchange by Automation Markup Language (AutomationML) provides existing means for realizing the required connectivity and interoperability for intelligent co-operation in smart factories [ 30 ].…”

Section: Contributionmentioning

confidence: 99%

An Artificial Intelligence-Based Collaboration Approach in Industrial IoT Manufacturing: Key Concepts, Architectural Extensions and Potential Applications

Trakadas

Simoens

Gkonis

et al. 2020

Sensors

View full text Add to dashboard Cite

The digitization of manufacturing industry has led to leaner and more efficient production, under the Industry 4.0 concept. Nowadays, datasets collected from shop floor assets and information technology (IT) systems are used in data-driven analytics efforts to support more informed business intelligence decisions. However, these results are currently only used in isolated and dispersed parts of the production process. At the same time, full integration of artificial intelligence (AI) in all parts of manufacturing systems is currently lacking. In this context, the goal of this manuscript is to present a more holistic integration of AI by promoting collaboration. To this end, collaboration is understood as a multi-dimensional conceptual term that covers all important enablers for AI adoption in manufacturing contexts and is promoted in terms of business intelligence optimization, human-in-the-loop and secure federation across manufacturing sites. To address these challenges, the proposed architectural approach builds on three technical pillars: (1) components that extend the functionality of the existing layers in the Reference Architectural Model for Industry 4.0; (2) definition of new layers for collaboration by means of human-in-the-loop and federation; (3) security concerns with AI-powered mechanisms. In addition, system implementation aspects are discussed and potential applications in industrial environments, as well as business impacts, are presented.

show abstract

Section: Contributionmentioning

confidence: 99%

An Artificial Intelligence-Based Collaboration Approach in Industrial IoT Manufacturing: Key Concepts, Architectural Extensions and Potential Applications

Trakadas

Simoens

Gkonis

et al. 2020

Sensors

View full text Add to dashboard Cite

show abstract

“…If this is not possible, proper collaboration between human and machine is needed [6]. Solutions so far focus on limited applications and do not provide a complete system [7]. Smart factories, as also presented in this article, do not exit yet [8] due to the social impact [9].…”

Section: Introductionmentioning

confidence: 98%

Trends in Smart Manufacturing: Role of Humans and Industrial Robots in Smart Factories

et al. 2020

View full text Add to dashboard Cite

Purpose of Review This paper provides an overview of the role of humans and robots in smart factories, their connection to Industry 4.0, and which progress they make when it comes to related technologies. Recent Findings The current study shows that a decade was not enough to provide a reference implementation or application of Industry 4.0, like smart factories. In 2011, Industry 4.0 was mentioned for the first time in the scientific community. Industry 4.0 arrived with many new enabling technologies and buzzwords, e.g., Internet of Things (IoT), Cyber-Physical Systems (CPS), and Digital Twins (DT). Summary This paper first defines smart factories and smart manufacturing in relation to the role of humans and robots. Followed by an overview of selected technologies in smart factories. Concluded by future prospects and its' relation to smart manufacturing.

show abstract

“…Interoperability among heterogeneous devices is an imperative requirement for the realization of interworking solutions. In particular, semantic interoperability represents the highest level of interoperability, aiming to provide a common meaning of the data exchanged by heterogeneous devices, even if they belong to different domains [ 16 ]. Among the main initiatives to achieve semantic interoperability, there is that provided by the European Telecommunications Standard Institute (ETSI).…”

Section: Introductionmentioning

confidence: 99%

Semantic Interoperability between IEC 61850 and oneM2M for IoT-Enabled Smart Grids

Cavalieri

2021

Sensors

View full text Add to dashboard Cite

In the era of Industry 4.0, pervasive adoption of communication technologies based on the Internet of Things represents a very strong requirement in several domains. In the smart grid domain, there is the need to overcome one of the main limitations of the current electric grid, allowing the use of heterogeneous devices capable of measuring, monitoring and exchanging information about grid components. For this reason, current literature often presents research activities about enabling internet of things (IoT) in smart grids; in particular, several proposals aim to realize interworking between IoT and smart grid communication standards, allowing exchange of information between IoT devices and the electrical grid components. Semantic interoperability should be achieved in an interworking solution in order to provide a common meaning of the data exchanged by heterogeneous devices, even if they belong to different domains. Until now, semantic interoperability remains an open challenge in the smart grid field. The paper aims to propose a novel solution of interworking between two of the most used communication systems in smart grids and IoT domains, i.e., IEC 61850 and oneM2M, respectively. A semantic interoperability solution is also proposed to be used in the interworking scheme here presented.

show abstract

Interoperability in Smart Manufacturing: Research Challenges

Cited by 105 publications

References 35 publications

An Artificial Intelligence-Based Collaboration Approach in Industrial IoT Manufacturing: Key Concepts, Architectural Extensions and Potential Applications

An Artificial Intelligence-Based Collaboration Approach in Industrial IoT Manufacturing: Key Concepts, Architectural Extensions and Potential Applications

Trends in Smart Manufacturing: Role of Humans and Industrial Robots in Smart Factories

Semantic Interoperability between IEC 61850 and oneM2M for IoT-Enabled Smart Grids

Contact Info

Product

Resources

About