Industry 4.0 framework for management and operations: a review

Saucedo-Martínez, Jania Astrid; Pérez-Lara, Magdiel; Marmolejo-Saucedo, José Antonio; Salais-Fierro, Tomás Eloy; Vasant, Pandian

doi:10.1007/s12652-017-0533-1

Cited by 219 publications

(165 citation statements)

References 80 publications

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“…1) The authors of the concept state that data would attain a higher importance in the economy than hydrocarbons. They use the term a «data-driven» economy when describing this new stage of economic development [7,8,9].…”

Section: Literature Overviewmentioning

confidence: 99%

Industry 4.0: Theoretical Foundations and the Strategic Priorities of Russian Regions

Kurnikova¹,

Болгова²,

Bolgov³

et al. 2020

Proceedings of the “New Silk Road: Business Cooperation and Prospective of Economic Development” (NSRBCPED 2019)

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The Industry 4.0 concept acts as a theoretical foundation for introducing digital technologies into production and management processes which leads to the digital transformation of economy including the one at the level of territories. The efficiency of digital transformation in developed and developing countries is achieved through public administrationthe development of government programmes, national and local strategies, the plans and projects of a certain region. The current practices for strategic planning need a scientifically-based justification of development priorities and their overarching presence in a comprehensive system of strategic documents. The difficulty of developing digital transformation priorities arises from the ongoing research into Industry 4.0 concept deriving from the dynamically changing trends of digitalization, its diversity and complexity for the development of Russian regions. The prepared Russian documents fail to reflect the priority of universities in creating Industry 4.0, with a "digital university" being the only model in working out, implementing and using digital technologies in regional economies. Due to the incomplete Industry 4.0 concept and the urgency of the digital transformation of the economy, the paper is aimed at developing theoretical foundations of the «datadriven» economy. The research conducted by the authors involved the dialectic method, the methods of summarization, analysis and synthesis, deduction and induction. The study resulted in some certain suggestions on strategic priorities for the development of Russian regions in view of key digital technologies, the role of universities in their creation and implementation. The authors have shown that Industry 4.0 has a huge potential in setting priorities of digital economy and management at the level of regions.

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Section: Literature Overviewmentioning

confidence: 99%

Industry 4.0: Theoretical Foundations and the Strategic Priorities of Russian Regions

Kurnikova¹,

Болгова²,

Bolgov³

et al. 2020

Proceedings of the “New Silk Road: Business Cooperation and Prospective of Economic Development” (NSRBCPED 2019)

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“…Germany focuses on creating new values that have not been seen before and resolving various social problems by linking the things inside and outside the manufacturing environments, but also on construction of a new business models for predictive manufacturing systems [29]. In the USA the research and development programs are related to predictive manufacturing with accent on key technology assignments, including data mining, big data analytics, intelligent systems along with IoT and CPS [3].…”

Section: Trendsmentioning

confidence: 99%

“…The entire present manufacturing systems is transformed into predictive manufacturing systems with the "self-aware", "self-predict", "self-maintain" and "self-learning" abilities which allow that decisions are going to be made autonomously [29]. According to Lee et al [5] and Ferreiro et al [30], in contrary to the conventional systems which are in use today, predictive manufacturing systems improve the performance of the equipment and strengthen the business model of industry, with the help of a set of intelligent sensing, predictive analytics and network techniques.…”

Section: Benefitsmentioning

confidence: 99%

“…According to [13,17,29], the major challenge that has an effect in machine's abilities of sensoring, monitoring and gathering the big data from the manufacturing environments in order to achieve "self-aware", "self-predict", "self-maintain" and "selflearning" machines by adopting algorithms of the PHM. The development of the algorithms that are able to learn from and to handle different situations is still a great issue which can be considered as a general challenge not only for the PMS, but for entire Industry 4.0 [3,13].…”

Section: Challengesmentioning

confidence: 99%

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Predictive Manufacturing Systems in Industry 4.0: Trends, Benefits and Challenges

Nikolić¹,

Ignjatic²,

Suzić³

et al. 2017

DAAAM Proceedings

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The fourth industrial revolution, known as Industry 4.0, has tendency to push the boundaries of science and technology. This is especially true for the manufacturing industry. One of the biggest challenges facing the manufacturing industry today is how to make intelligent systems for production with "self-aware", "self-predict and "self-maintain" abilities. Predictive manufacturing systems (PMS) are new intelligent systems that provide these abilities in the production, processes and machines. The PMS combines different technologies and techniques: statistics, data mining, modelling and artificial intelligence methods. These technologies and techniques are used to convert data into information and make predictions about the observed system. This paper provides an overview of the various challenges, existing solutions and benefits of PMS, with a focus on success factors in Industry 4.0.

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“…From the point of view related to managerial implications (Piccarozzi, Aquilani and Gatti, 2018), the concept and strategy of Industry 4.0 should be implemented regarding to sustainability issues and the application of such strategies could improve sustainable social welfare growth. In another review conducted by Saucedo-Martínez et al (2018), it was stated that Industry 4.0 environment should be included in company in two areas, both socio-technical area and physical objects virtualization. Industry 4.0 is still emerging in research field, but the results from past research are strongly encouraging the incorporation of selected methods in managerial practice (Schneider, 2018).…”

Section: Introductionmentioning

confidence: 99%

Using Industry 4.0 Concept – Digital Twin – to Improve the Efficiency of Leather Cutting in Automotive Industry

2019

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Purpose: The aim of this study is to propose alternatives of increasing the efficiency of material selection and processing in the selected company and reduce costs and leather sustainability as a result.Methodology/Approach: In this case study, an automotive company processing a natural leather material that enters the process of a large-scale production was explored. For this purpose, the internal documents of the firm selected including its internal database and know-how of its employees were used. The ways of improving the efficiency of the material processing were proposed and tested in a digital environment. In the proposed solutions, Industry 4.0 principles were implemented.Findings: By the use of Digital twin and other Industry 4.0 principles and solutions in the process of material selection and processing in the company selected, the increased efficiency and cost savings were achieved.Research Limitation/implication: The solutions proposed in this paper were based on exploration of the chosen data set of the selected company. For the future research, testing of the given proposals in other companies should be conducted.Originality/Value of paper: Although there is an increasing number of publications describing the concept Industry 4.0, the research providing evidence of its benefits for business entities is still scarce. This paper offers such a research in the enterprise selected.

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Industry 4.0 framework for management and operations: a review

Cited by 219 publications

References 80 publications

Industry 4.0: Theoretical Foundations and the Strategic Priorities of Russian Regions

Industry 4.0: Theoretical Foundations and the Strategic Priorities of Russian Regions

Predictive Manufacturing Systems in Industry 4.0: Trends, Benefits and Challenges

Using Industry 4.0 Concept – Digital Twin – to Improve the Efficiency of Leather Cutting in Automotive Industry

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