A Big Data Analytics Architecture for Industry 4.0

Santos, Maribel Yasmina; Sá, Jorge Oliveira e; Costa, Carlos A. Bana e; Galvão, João; Andrade, Carina; Martinho, Bruno; Lima, Francisca Vale; Costa, Eric

doi:10.1007/978-3-319-56538-5_19

Cited by 57 publications

(44 citation statements)

References 13 publications

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“…Secondly, Industry 4.0 has proliferated big data analytics [74]. This rapid increase in big data analytics has gifted firms the opportunity of turning information and knowledge into a competitive advantage at faster rates, even in real-time [75].…”

Section: Overview On the State Of Big Data Analytics And Eco-innovationmentioning

confidence: 99%

Big Data Analytics Capabilities and Eco-Innovation: A Study of Energy Companies

Munodawafa

Johl

2019

Sustainability

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Increased greenhouse gas (GHG) emissions in the past decades have created concerns about the environment. To stymie global warming and the deterioration of the natural environment, global CO2 emissions need to reach approximately 1.3 tons per capita by 2050. However, in Malaysia, CO2 output per capita—driven by fossil fuel consumption and energy production—is expected to reach approximately 12.1 tons by the year 2020. GHG mitigation strategies are needed to address these challenges. Cleaner production, through eco-innovation, has the potential to arrest CO2 emissions and buttress sustainable development. However, the cleaner production process has been hampered by lack of complete data to support decision making. Therefore, using the resource-based view, a preliminary study consisting of energy and utility firms is undertaken to understand the impact of big data analytics towards eco-innovation. Linear regression through SPSS Version 24 reveals that big data analytics could become a strong predictor of eco-innovation. This paper concludes that information and data are key inputs, and big data technology provides firms the opportunity to obtain information, which could influence its production process—and possibly help arrest increasing CO2 emissions.

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Section: Overview On the State Of Big Data Analytics And Eco-innovationmentioning

confidence: 99%

Big Data Analytics Capabilities and Eco-Innovation: A Study of Energy Companies

Munodawafa

Johl

2019

Sustainability

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“…Whilst big data is commonly recognised to have the potential of generating enormous benefits to organisations, the analytics of big data is still an ongoing issue that has yet been fully explored (Comuzzi & Patel, 2016). People's diverse information needs, misfit in organisational culture, resistance to change, and rapid development in technology and industrial facilities can create challenges in both analysis and usage of big data (Santos et al, 2017). Our review of literature showed that current research of big data and their application in the organisation context has three main focusses.…”

Section: Overview Of Literature On Big Datamentioning

confidence: 99%

Barriers of embedding big data solutions in smart factories: insights from SAP consultants

Peng

Xing

2019

IMDS

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Purpose Big data is a key component to realise the vision of smart factories, but the implementation and usage of big data analytical tools in the smart factory context can be fraught with challenges and difficulties. The purpose of this paper is to identify potential barriers that hinder organisations from applying big data solutions in their smart factory initiatives, as well as to explore causal relationships between these barriers. Design/methodology/approach The study followed an inductive and exploratory nature. Ten in-depth semi-structured interviews were conducted with a group of highly experienced SAP consultants and project managers. The qualitative data collected were then systematically analysed by using a thematic analysis approach. Findings A comprehensive set of barriers affecting the implementation of big data solutions in smart factories had been identified and divided into individual, organisational and technological categories. An empirical framework was also developed to highlight the emerged inter-relationships between these barriers. Originality/value This study built on and extended existing knowledge and theories on smart factory, big data and information systems research. Its findings can also raise awareness of business managers regarding the complexity and difficulties for embedding big data tools in smart factories, and so assist them in strategic planning and decision making.

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“…• em função do alto volume, variedade e velocidade de dados gerados por controladores, sensores e sistemas na Indústria 4.0, há necessidade de coleta, integração, armazenamento, processamento e análise de dados, que em conjunto denominam o fenômeno Big Data Analytics (SANTOS, et al, 2017);…”

Section: Indústria 40unclassified

Uma perspectiva colaborativa da cadeia de suprimentos para apoiar a indústria 4.0

Santana

Assumpção

Oliveira

2019

Revista PO: R. Eletr. de Eng. de Produção e Correlatas

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A necessidade de fornecimento de insumos para a Indústria 4.0, que está permeada pelo avanço tecnológico dos dispositivos sensoriais, virtualização de ativos, IoT, Big Data Analytics, CPS, Data Mining, RFID, IoS e computação em nuvem, requisita avaliação das iniciativas da cadeia de suprimentos que podem ser colaborativas para atender as demandas dos recursos. O artigo apresenta revisão da literatura sobre a Indústria 4.0 e a cadeia de suprimentos, e ainda uma análise bibliométrica para responder a seguinte questão: como a cadeia de suprimentos poder colaborar com a Indústria 4.0? Um questionário autoaplicável envolvendo liderança especializada em suas áreas é desenvolvido para obter informações sobre critérios estratégicos, organizacionais, tecnológicos e de segurança da informação, que posteriormente, é utilizado no método AHP para priorização das alternativas colaborativas. Os resultados demonstram que a falta de conhecimento tecnológico, segurança da informação e problemas de transparência na comunicação estão entre as ações prioritárias da cadeia de suprimentos para antever soluções colaborativas que possam reduzir ameaças futuras e acompanhar os avanços tecnológicos da quarta revolução industrial.

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A Big Data Analytics Architecture for Industry 4.0

Cited by 57 publications

References 13 publications

Big Data Analytics Capabilities and Eco-Innovation: A Study of Energy Companies

Big Data Analytics Capabilities and Eco-Innovation: A Study of Energy Companies

Barriers of embedding big data solutions in smart factories: insights from SAP consultants

Uma perspectiva colaborativa da cadeia de suprimentos para apoiar a indústria 4.0

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