English
Bibtex
Cite as text
@Select Types{,
Journal = "Band-2",
Title= "Risks and Opportunities of Industry 4.0 for Corporate Sustainability",
Author= "Grischa Beier",
Doi= "https://doi.org/10.30844/wi_2020_x4-beier",
Abstract= "Industry 4.0: digital technologies are changing the way industrial production works. This digital informatization of industrial production opens up opportunities for business informatics to develop sociotechnical solutions that support companies in their transformation towards more sustainability. The main contribution of this paper is the presentation, contextualization and controversial discussion of approaches identified in the literature, where digital technologies might offer an opportunity to support corporate sustainability. As a result the paper presents approaches where Industry 4.0 technologies support corporate sustainability management on a general level, and more specifically improve resource efficiency or enable Big Data approaches in order support corporate environmental management.
",
Keywords= "Industry 4.0, Corporate Sustainability, CSR, resource efficiency, Big Data",
}
Grischa Beier: Risks and Opportunities of Industry 4.0 for Corporate Sustainability. Online: https://doi.org/10.30844/wi_2020_x4-beier (Abgerufen 26.12.24)
Open Access
Abstract
Abstract
Industry 4.0: digital technologies are changing the way industrial production works. This digital informatization of industrial production opens up opportunities for business informatics to develop sociotechnical solutions that support companies in their transformation towards more sustainability. The main contribution of this paper is the presentation, contextualization and controversial discussion of approaches identified in the literature, where digital technologies might offer an opportunity to support corporate sustainability. As a result the paper presents approaches where Industry 4.0 technologies support corporate sustainability management on a general level, and more specifically improve resource efficiency or enable Big Data approaches in order support corporate environmental management.
Keywords
Schlüsselwörter
Industry 4.0, Corporate Sustainability, CSR, resource efficiency, Big Data
References
Referenzen
1. Malmodin, J., Lundén, D.: The electricity consumption and operational carbon emissions of ICT network operators 2010-2015 (2018)
2. Efou-Hess, M.: Climate Crisis: The Unsustainable Use of Online Video. The practical case study of online video (2019)
3. Lasi, H., Fettke, P., Kemper, H.-G., Feld, T., Hoffmann, M.: Industry 4.0. Bus Inf Syst Eng 6, 239–242 (2014)
4. Schuh, G., Potente, T., Wesch-Potente, C., Weber, A.R., Prote, J.-P.: Collaboration Mechanisms to increase Productivity in the Context of Industrie
4.0. Procedia CIRP 19, 51–56 (2014)
5. Brettel, M., Friederichsen, N., Keller, M., Rosenberg, M.: How Virtualization, Decentralization and Network Building Change the Manufacturing Landscape: An Industry 4.0 Perspective. International Journal of Information and Communication Engineering 8, 37–44 (2014)
6. Stock, T., Seliger, G.: Opportunities of Sustainable Manufacturing in Industry
4.0. Procedia CIRP 40, 536–541 (2016)
7. Bangsa, A.B., Schlegelmilch, B.B.: Linking sustainable product attributes and consumer decision-making: Insights from a systematic review. Journal of Cleaner Production 245 (2020)
8. Klimkiewicz, K., Oltra, V.: Does CSR Enhance Employer Attractiveness? The Role of Millennial Job Seekers’ Attitudes. Corp. Soc. Responsib. Environ. Mgmt. 24, 449–463 (2017)
9. Fritzsche, K., Niehoff, S., Beier, G.: Industry 4.0 and Climate Change— Exploring the Science-Policy Gap. Sustainability 10, 4511 (2018)
10. Beier, G., Niehoff, S., Xue, B.: More Sustainability in Industry through Industrial Internet of Things? Applied Sciences 8, 219 (2018)
11. Niehoff, S., Beier, G.: Industrie 4.0 and a sustainable development. A short study on the perception and expectations of experts in Germany. IJISD 12, 360 (2018)
12. Shrouf, F., Miragliotta, G.: Energy management based on Internet of Things. Practices and framework for adoption in production management. Journal of Cleaner Production 100, 235–246 (2015)
13. Katchasuwanmanee, K., Bateman, R., Cheng, K.: Development of the Energysmart Production Management system (e-ProMan). A Big Data driven approach, analysis and optimisation. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 230, 972–978 (2015)
14. Bevilacqua, M., Ciarapica, F.E., Diamantini, C., Potena, D., Bardaki, C., Bertolini, M.: Big data analytics methodologies applied at energy management in industrial sector. A case study. RFT 8, 105–122 (2017)
15. Junker, H., Domann, Carsten: Towards Industry 4.0 In Corporate Energy Manangement. In: Gomar, D.A., Brebbia, C.A. (eds.) ECOSUD 2017, pp. 49–56. WIT PressSouthampton UK (2017)
16. Li, Y., Sun, Z., Han, L., Mei, N.: Fuzzy Comprehensive Evaluation Method for Energy Management Systems Based on an Internet of Things. IEEE Access 5, 21312–21322 (2017)
17. Heutmann, T., Schmitt, R.: Energieorientierte Produktionsplanung und – steuerung. ZWF 112, 563–566 (2017)
18. Wei, M., Hong, S.H., Alam, M.: An IoT-based energy-management platform for industrial facilities. Applied Energy 164, 607–619 (2016)
19. Pechmann, A., Shrouf, F., Chonin, M., Steenhusen, N.: Load-shifting potential at SMEs manufacturing sites. A methodology and case study. Renewable and Sustainable Energy Reviews 78, 431–438 (2017)
20. Ghani, U., Monfared, R.P., Harrison, R.: Energy optimisation in manufacturing systems using virtual engineering-driven discrete event simulation. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 226, 1914–1929 (2012)
21. Riazi, S., Bengtsson, K., Bischoff, R., Aurnhammer, A., Wigstrom, O., Lennartson, B.: Energy and peak-power optimization of existing time-optimal robot trajectories. In: 2016 IEEE International Conference on Automation Science and Engineering (CASE). 21-25 Aug. 2016, pp. 321–327. IEEE, Piscataway, NJ (2016)
22. Frazier, W.E.: Metal Additive Manufacturing. A Review. J. of Materi Eng and Perform 23, 1917–1928 (2014)
23. Chen, D., Heyer, S., Ibbotson, S., Salonitis, K., Steingrímsson, J.G., Thiede, S.: Direct digital manufacturing. Definition, evolution, and sustainability implications. Journal of Cleaner Production 107, 615–625 (2015)
24. Marscheider-Weidemann, F., Langkau, S., Hummen, T., Erdmann, L., Tercero Espinoza, L., Angerer, G., Marwede, M., Benecke, S.: Rohstoffe für Zukunftstechnologien 2016. Zusammenfassung. Berlin (2016)
25. Horner, N.C.: Powering the Information Age: Metrics, Social Cost Optimization Strategies, and Indirect Effects Related to Data Center Energy Use. Pittsburgh, PA (2016)
26. Khan, M., Wu, X., Xu, X., Dou, W.: Big data challenges and opportunities in the hype of Industry 4.0. In: Gesbert, D., Debbah, M., Mellouk, A. (eds.) 2017 IEEE International Conference on Communications (ICC). 2017 IEEE International Conference on Communications (ICC) took place 21-25 May 2017 in Paris, France, pp. 1–6. IEEE, Piscataway, NJ (2017)
27. Emmrich, V., Döbele, M., Bauernhansl, T., Paulus-Rohmer, D., Schatz, A., Weskamp, M.: Geschäftsmodell-Innovation durch Industrie 4.0. Chancen und Risiken für den Maschinen- und Anlagenbau. München (2015)
28. Gartner: What Is Big Data?, https://www.gartner.com/it-glossary/big-data
29. Förtsch, G., Meinholz, H.: Handbuch Betriebliches Umweltmanagement. Springer Fachmedien Wiesbaden, Wiesbaden (2014)
30. Keeso, A.: Big Data an Environmental Sustainability. A Conversation Starter (2014)
31. Song, M.-L., Fisher, R., Wang, J.-L., Cui, L.-B.: Environmental performance evaluation with big data. Theories and methods. Ann Oper Res 270, 459–472 (2018)
32. Zhang, Y., Ren, S., Liu, Y., Sakao, T., Huisingh, D.: A framework for Big Data driven product lifecycle management. Journal of Cleaner Production 159, 229– 240 (2017)
33. Xu, M., Cai, H., Liang, S.: Big Data and Industrial Ecology. Journal of Industrial Ecology 19, 205–210 (2015)
34. Cooper, J., Noon, M., Jones, C., Kahn, E., Arbuckle, P.: Big Data in Life Cycle Assessment. Journal of Industrial Ecology 17, 796–799 (2013)
35. Kiefer, J.: Big Data und Umweltmanagement (2019)