Standards-based semantic integration of manufacturing information: Past, present, and future

Kulvatunyou, Boonserm; Oh, Hakju; Ivezic, Nenad; Nieman, Scott

doi:10.1016/j.jmsy.2019.07.003

Cited by 19 publications

(4 citation statements)

References 21 publications

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“…Manufacturing paradigms are enabled by the available technologies, particularly information technologies in the digital era. Kulvatunyou et al [42] analysed the development of the standards for the integration of semantic data and concluded that the standards for digital manufacturing must be advanced to maintain, represent, and present data in the form of knowledge and insight for collaborative decision making support. It is well known that the digital transformation from Industry 3.0 to 4.0 was enabled by some critical ITs, such as IoT, CC, BDA, and AI [16].…”

Section: Technological Driversmentioning

confidence: 99%

Generic Design Methodology for Smart Manufacturing Systems from a Practical Perspective, Part I—Digital Triad Concept and Its Application as a System Reference Model

Zhang

et al. 2021

Machines

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Rapidly developed information technologies (IT) have continuously empowered manufacturing systems and accelerated the evolution of manufacturing system paradigms, and smart manufacturing (SM) has become one of the most promising paradigms. The study of SM has attracted a great deal of attention for researchers in academia and practitioners in industry. However, an obvious fact is that people with different backgrounds have different expectations for SM, and this has led to high diversity, ambiguity, and inconsistency in terms of definitions, reference models, performance matrices, and system design methodologies. It has been found that the state of the art SM research is limited in two aspects: (1) the highly diversified understandings of SM may lead to overlapped, missed, and non-systematic research efforts in advancing the theory and methodologies in the field of SM; (2) few works have been found that focus on the development of generic design methodologies for smart manufacturing systems from the practice perspective. The novelty of this paper consists of two main aspects which are reported in two parts respectively. In the first part, a simplified definition of SM is proposed to unify the existing diversified expectations, and a newly developed concept named digital triad (DT-II) is adopted to define a reference model for SM. The common features of smart manufacturing systems in various applications are identified as functional requirements (FRs) in systems design. To model a system that is capable of reconfiguring itself to adapt to changes, the concept of IoDTT is proposed as a reference model for smart manufacturing systems. In the second part, these two concepts are used to formulate a system design problem, and a generic methodology, based on axiomatic design theory (ADT), is proposed for the design of smart manufacturing systems.

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Section: Technological Driversmentioning

confidence: 99%

Generic Design Methodology for Smart Manufacturing Systems from a Practical Perspective, Part I—Digital Triad Concept and Its Application as a System Reference Model

Zhang

et al. 2021

Machines

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“…From them, the data flows to other collaborating, intelligent processes and assets. Hence, data-flow standards can facilitate such collaborations [44]. Open-source, bigdata-management systems promise to enable the same kinds of collaborations -even among SMEs [45].…”

Section: Enabling Technologiesmentioning

confidence: 99%

Advances in Production Management Systems: Issues, Trends, and Vision Towards 2030

Romero

Cieminski

Wuest

et al. 2021

IFIP Advances in Information and Communication Technology

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Since its inception in 1978, the IFIP Working Group (WG) 5.7 on Advances in Production Management Systems (APMS) has played an active role in the fields of production and production management. The Working Group has focused on the conception, development, strategies, frameworks, architectures, processes, methods, and tools needed for the advancement of both fields. The associated standards created by the IFIP WG5.7 have always been impacted by

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“…AM helps in orchestrating not just maintenance and operation phases of the assets but also the design and commissioning, thus the entire life cycle (Institute of Asset Management, 2015). The growth of technological complexity is another reason to better coordinate asset-related decisions through their life cycle in manufacturing facilities (Kulvatunyou et al , 2019).…”

Section: Introductionmentioning

confidence: 99%

Information as a key dimension to develop industrial asset management in manufacturing

Polenghi

Roda

Macchi

et al. 2021

JQME

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PurposeThe purpose of this work is to investigate industrial asset management (AM) in manufacturing. After depicting gaps for AM in this sector, the role of information as a key dimension is considered to realise a summary of challenges and advices for future development.Design/methodology/approachThe work is grounded on an extensive systematic literature review. Considering the eligible documents, descriptive statistics are provided and a content analysis is performed, both based on a sector-independent normative-based framework of analysis.FindingsAM principles, organisation and information are the dimensions defined to group ten areas of interest for AM in manufacturing. Information is the major concern for an effective AM implementation. Moreover, Internet of Things and big data management and analytics, as well as data modelling and ontology engineering, are the major technologies envisioned to advance the implementation of AM in manufacturing.Research limitations/implicationsThe identified challenges and advices for future development may serve to stimulate further research on AM in manufacturing, with special focus on information and data management. The sector-independent normative-based framework may also enable to analyse AM in different contexts of application, thus favouring cross-sectorial comparisons.Originality/valueIndustries with higher operational risk, like Oil&Gas and infrastructure, are advanced in AM, while others, like some in manufacturing, are laggard in this respect. This literature review is the first of a kind addressing AM in manufacturing and depicts the state-of-the-art to pave the way for future research and development.

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Standards-based semantic integration of manufacturing information: Past, present, and future

Cited by 19 publications

References 21 publications

Generic Design Methodology for Smart Manufacturing Systems from a Practical Perspective, Part I—Digital Triad Concept and Its Application as a System Reference Model

Generic Design Methodology for Smart Manufacturing Systems from a Practical Perspective, Part I—Digital Triad Concept and Its Application as a System Reference Model

Advances in Production Management Systems: Issues, Trends, and Vision Towards 2030

Information as a key dimension to develop industrial asset management in manufacturing

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