Smart manufacturing and DVSM based on an Ontological approach

Huang, Zhuoyu; Jowers, Casey; Dehghan-Manshadi, Ali; Dargusch, Matthew S.

doi:10.1016/j.compind.2020.103189

Cited by 22 publications

(8 citation statements)

References 22 publications

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“…In a separate study, the use of VSM with simulation has helped increase work quality and reduce accidents by identifying a suitable supply policy between workstations (Dotoli et al, 2014). (Huang et al, 2020). Industry 4.0 tools release employees from tiring physical work, as automation and robotics are added to the systems to help employees perform repetitive and labour-intensive processes (Jing et al, 2013).…”

Section: Social Benefitsmentioning

confidence: 99%

Lean and industry 4.0: Mapping determinants and barriers from a social, environmental, and operational perspective

Yilmaz

Dora

Hezarkhani

et al. 2022

Technological Forecasting and Social Change

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Section: Social Benefitsmentioning

confidence: 99%

Lean and industry 4.0: Mapping determinants and barriers from a social, environmental, and operational perspective

Yilmaz

Dora

Hezarkhani

et al. 2022

Technological Forecasting and Social Change

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“…8. Based on the ability of the NeoSemantics plugin in the Neo4j database to support inference on RDF models (Huang et al, 2020), we subsequently demonstrate the ability of spatial inference and complex queries on the typhoon evolution data model built in this paper. We answer the following propositions, which are difficult to answer at once by traditional databases, to demonstrate the dynamic representation and spatial reasoning ability of our model.…”

Section: Application To Typhoon Eventmentioning

confidence: 98%

Dynamic Representations of Spatial Events – The Example of a Typhoon

Hofer

Sheng

et al. 2021

AGILE GIScience Ser.

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Abstract. The Geographic scene is a conceptual model that provides a holistic representation of the environment. This model has been developed in order to overcome limitations of geographic information systems (GIS) concerning interactions between features and the representation of dynamics. This contribution translates the theoretical model into an implementation of a dynamic data model in the graph database Neo4j and applies it to GIS data representing the dynamic information of a typhoon. The specific focus of the contribution is on choices made in the process of generation of the implementation of the example and the potential queries it supports.

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“…This submission triggers a chain of inputs and actions across the production stream, from the design file to the manufacturing processes. A former investigation [57,58] has identified the bending process as a bottleneck, with the sideboard part specifically consuming significant time. VSM was instrumental in making this determination.…”

Section: Product and Manufacturing Analysismentioning

confidence: 99%

The implementation of Industry 4.0 in manufacturing: from lean manufacturing to product design

Huang

Jowers

Kent

et al. 2022

Int J Adv Manuf Technol

Self Cite

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With the emergence of Industry 4.0, digitalization and intelligent manufacturing are vital to ensure competitivity, especially for manufacturers reliant on legacy machines. Upgrading legacy machines with cyber physical technology under Industry 4.0 frameworks can enable connection of these machines to existing IoT networks to allow the sharing and exchange of production information. In this paper, a legacy machine used in sheet metal folding operations is upgraded by integrating switch sensors which provide detailed data on the machine status to stakeholders, enabling in-depth analysis of the production activity before and after the implementation of lean manufacturing methods. Furthermore, it is shown that the data collected can be applied to conduct dynamic value stream mapping (DVSM) in near real time to provide deeper level insight into manufacturing processes. More detailed mapping enables identification of wastes involved with labour and design. Therefore, an innovative graphical technique is proposed to improve the flattened pattern to reduce manual handling and ease bottlenecks identified by VSM. From the collected VSM data, a leanness measure was established to provide objective and quantitative evaluation of the process performance.

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Smart manufacturing and DVSM based on an Ontological approach

Cited by 22 publications

References 22 publications

Lean and industry 4.0: Mapping determinants and barriers from a social, environmental, and operational perspective

Lean and industry 4.0: Mapping determinants and barriers from a social, environmental, and operational perspective

Dynamic Representations of Spatial Events – The Example of a Typhoon

The implementation of Industry 4.0 in manufacturing: from lean manufacturing to product design

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