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Concept of Reconfigurability in Interoperation Manufacturing Buffers for Smart Factory

-6, Yang, H.L., Chang, T.W., Choi, Y., 2018. Exploring the Research Trend of Smart Factory with Topic Modeling. Sustainability 10(8: 2779), https://doi.org/10.3390/su10082779

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The Influence of Critical Factors on Business Model at a Smart Factory: A Case Study

”, Journal of Management Development, Vol. 36, No. 1, pp. 14-36. 40. Wang, S., Wan, J., Zhang, D., Li, D., Zhang, C. (2016), “Towards smart factory for industry 4.0: a self-organized multi-agent system with big data based feedback and coordination”, Computer Networks, Vol. 101, pp. 158–168. 41. Yin, R. K. (2014), Case study research design and methods, Sage, Thousand Oaks, CA.

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Design of a Communication Scheme in a Modern Factory in Accordance with the Standard of Industry 4.0

Future. In: Conference on ENTERprise Information Systems / International Conference on Project MANagement / Conference on Health and Social Care Information Systems and Technologies, CENTERIS / ProjMAN / HCist, pp. 721 – 728. 4. Yongrui QIN, Quan Z SHENG, Nickolas J.G FALKNER, Schahram DUSTDAR, Hua WANG, Athanasios V. VASILAKOS. When things matter: A survey on data-centric internet of things. Journal of Network and Computer Applications , vol. 64 , pp. 137–153. ISSN: 1084-8045 5. Defang LI, 2016. Perspective for Smart Factory in Petrochemical Industry

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The Challenges of Industry 4.0 for Small and Medium Enterprises in Poland and Slovakia

Abstract

In the paper an analysis of the state of preparation of small and medium-sized enterprises in the metal industry in Poland and Slovakia was presented. Based on the conducted surveys, the challenges of industry 4.0, which will have to be met by small and medium enterprises, have been identified. Opportunities and threats for enterprises from the SME sector have been also defined. It was found that the biggest threats was lack of capital and lack of appropriate specialists, as well as high costs of staff preparation. Opportunities for enterprises are increased productivity and productivity, faster response to changes to customer requirements.

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Industry 4.0 and the digital society: concepts, dimensions and envisioned benefits

Abstract

There is a considerable amount of interest in Industry 4.0, the so-called 4fh industrial revolution, however, the concept is not clear in the literature. This research by performing a literature review on Industry 4.0, aims to present an overview of the several industrial revolutions with emphasis on Industry 4.0 and its underlined dimensions. Industry 4.0 is characterized by the advanced digitalization and integration of industrial manufacturing and logistics processes, and the use of internet and “smart” objects (machines and products) and merging the physical and the virtual worlds by the adoption of information and communications technology (ICT). Industry 4.0 fosters novel human and production organization systems and new organizational business models, impacting the overall value chain, society and the environment. Contributions for such new business models that can support Industry 4.0 are proposed with envisioned potential benefits such as shorter operations cycle times, quick delivery times, faster time to market of new products and services, improved quality, and product/service customization, stronger consumer involvement and loyalty. Industry 4.0 can help organizations to address new and emerging markets by a differentiation strategy, or even create new disruptive business models. However, it is still in the early stages for most companies and the digital transformation will require a strong leadership, the right human competences and to overcome several barriers, for its successful implementation. And while this will lead to a significant improvement in job creation, there will be also considerable job losses for Employees with low skill levels. Considering that in 2015, only 14% of Small and Medium Enterprises were using internet channel and 40% of the European Union companies still had not adopted any of the new advanced digital technologies, there is a great need to further research Industry 4.0 drivers and success factors.

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Industry 4.0, M2m, Iot&S – All Equal?

, Wolfgang, 2012 Industry 4.0: From Smart Factories to Smart Products, availabale at http://www.business-meetsresearch.lu/bmr/content/download/4929/41471/version/1/file/Industry_4_0From_Smart_Factories_to_Smart_Products.pdf. http://m2m-summit.com/files/m2m_summit_2013_vatm_e_030913.pdf http://www.internet-of-things.no/iot.html http://hutgrip.com/blogs/market-opportunity-for-the-next-big-thing/

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Internet of Things in the Context of Industry 4.0: An Overview

., Wan, J., Shu, L., Li, P., Mukherjee, M., & Yin, B. (2017). Smart factory of industry 4.0: Key technologies, application case, and challenges. IEEE Access , 6 , 6505-6519. Cook, D., & Das, S. K. (2004). Smart environments: Technology, protocols and applications (Vol. 43). John Wiley & Sons. Da Xu, L., He, W., & Li, S. (2014). Internet of things in industries: A survey. IEEE Transactions on industrial informatics , 10 (4), 2233-2243. Davis, J., Edgar, T., Porter, J., Bernaden, J., & Sarli, M. (2012). Smart manufacturing, manufacturing

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Engineer 4.0 in a metallurgical enterprise

Abstract

Along with the growing dynamics of technological changes in production in the perspective of the development of 4.0 industry, there are changes in the structure of employment and professional qualifications of employees. The development of cyber-physical production systems (CPPS) entails an increase in the demand for engineers. Industry 4.0 is a new megatrend in production. In the second decade of this century, the concept of Industry 4.0 gained importance thanks to the policy of the German government and gradually penetrated into other countries. Enterprises, in addition to traditional production organization, started realizing of cyberphysical production lines as well as smart factories. New production solutions based on IT and robotics technologies using IoT the need for new employee competencies. On the market there is still a growing demand for IT specialists, and there is a demand for engineers 4.0, that is employees with new technical competences, able to control and service CPPS.This publication attempts to present the scope of changes in employment and presents the profile of professional qualifications of engineer 4.0 in a metallurgical enterprise. The list of new skills for an engineer 4.0 employed in an metallurgical enterprise is presented in this article by authors.

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The importance of prediction methods in industry 4.0 on the example of steel industry

Abstract

This paper presents the importance of the prediction of steel production in industry 4.0 along with forecasts for steel production in the world until 2022. In the last two decades, the virtual world has been increasingly entering production. Today’s manufacturing systems are becoming faster and more flexible – easily adaptable to new products. Steel is the basic structural material (base material) for many industrial sectors. Industries such as automotive, mechanical engineering, construction and transport use steel in their production processes. Prediction methods in cyber-physical production systems are gaining in importance. The task of prediction is to reduce risk in the decision-making process. In autonomous manufacturing systems in industry 4.0 the role of prediction is more active than passive. Forecasts have the following functions: warning, reaction, prevention, normative, etc. The growing number of customized solutions in industry 4.0 translates into new challenges in the production process. Manufacturers must respond to individual customer needs more quickly, be able to personalize products while reducing energy and resource costs (saving energy and resources can increase the product competitiveness). The modern market becomes increasingly unpredictable. Production prediction under such conditions should be carried out continuously, which is possible because there is more empirical data and access to data. Information from the ongoing monitoring of the company’s production is directly transferred to the prospective evaluation. In view of the contemporary reciprocal use of automation, data processing, data exchange and manufacturing techniques, there is greater access to external data, e.g. on production in different target markets and with global, international, national, regional coverage. Companies can forecast in real time, and the forecasts obtained give the possibility to quickly change their production. Industry 4.0 (from the business objective point of view) aims to provide companies with concrete economic benefits – primarily by reducing manufacturing costs, standardizing and stabilizing quality, increasing productivity. Industry 4.0 aims to create a given autonomous smart factory system in which machines, factory components and services communicate and cooperate with each other, producing a personalized product. The aim of this paper is to present new challenges in the production processes in relation to steel production, as well as to prepare and present forecasts of (quantitative) steel production of territorial, global and temporary range until 2022, taking into account the applied production technologies (BOF and EAF). For forecasting purposes, classic trend models and adaptive trend models were used. This methodology was used to build separate forecasts for: total steel production, BOF steel and EAF steel. Empirical data is world steel production in 2000-2017 (annual production volume in Mt).

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The Predictive Maintenance Concept in the Maintenance Department of the “Industry 4.0” Production Enterprise

., Koronios, A., 2006. E-Prognostics: A Step Towards E-Maintenance of Engineering Assets. Journal of Theoretical and Applied Electronic Commerce Research, 1(1), pp.42-55. [11] Henke, M., Kuhn, A., 2015. Smart Factories for Smart Factories - Mit intelligenter Instandhaltung die Industrie 4.0 vorantreiben. Red Paper - Acatech POSITION. [12] Kopetz, H., 2011. Internet of Things. In Real-time Systems. Springer, Boston, MA. [13] Lasi H., Kemper H.G., Fettke P., Feld T., Hoffmann M., 2014. Industry 4.0. Business & Information

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