Open Access
Issue
E3S Web Conf.
Volume 552, 2024
16th International Conference on Materials Processing and Characterization (ICMPC 2024)
Article Number 01046
Number of page(s) 23
DOI https://doi.org/10.1051/e3sconf/202455201046
Published online 23 July 2024
  1. Nangia, S., Makkar, S., & Hassan, R. (2020). IoT based Predictive Maintenance in Manufacturing Sector. Social Science Research Network. [Google Scholar]
  2. Wang, J., Xu, C., Zhang, J., & Zhong, R. Y. (2021). Big data analytics for intelligent manufacturing systems: A review. Journal of Manufacturing Systems. [Google Scholar]
  3. Redelinghuys, A., Basson, A., & Kruger, K. (2020). A six-layer architecture for the digital twin: a manufacturing case study implementation. Journal of Intelligent Manufacturing, 31, 1383-1402. [CrossRef] [Google Scholar]
  4. Leivadaros, S., Kornaros, G., & Coppola, M. (2021). Secure Asset Tracking in Manufacturing through Employing IOTA Distributed Ledger Technology. 2021 IEEE/ACM 21st International Symposium on Cluster, Cloud and Internet Computing (CCGrid), 754-761. [CrossRef] [Google Scholar]
  5. Fang, P., Yang, J., Zheng, L., Zhong, R., & Jiang, Y. (2020). Data analytics-enable production visibility for Cyber-Physical Production Systems. Journal of Manufacturing Systems, 57, 242-253. [CrossRef] [Google Scholar]
  6. Nijhawan, M., Rana, A., Kumar, S., & Tanwar, S. (2021). Collaborating Technologies for Autonomous and Smart Trade in the Era of Industry 4.0: A Detail Review on Digital Factory. Advances in Intelligent Systems and Computing. [Google Scholar]
  7. Cheng, X., & Zhang, P. (2021). Service Innovation of Industrial Big Data Based on Industry 4.0 Architecture. Journal of Physics: Conference Series. [Google Scholar]
  8. Zeb, S., Mahmood, A., Hassan, S., Piran, M. J., Gidlund, M., & Guizani, M. (2021). Industrial Digital Twins at the Nexus of NextG Wireless Networks and Computational Intelligence: A Survey. J. Netw. Comput. Appl., 200, 103309. [Google Scholar]
  9. Lakshmi, S., Janet, J., Rani, P. K., Sujatha, K., Satyamoorthy, K., & Marichamy, S. (2021). Role and applications of IoT in materials and manufacturing industries - Review. Materials Today: Proceedings. [Google Scholar]
  10. Hee Song Ng. (2020). Opportunities, Challenges, and Solutions for Industry 4.0. Research Anthology on Cross-Industry Challenges of Industry 4.0. [Google Scholar]
  11. Ling Li. (2022). Blockchain technology in industry 4.0. Enterprise Information Systems. [Google Scholar]
  12. Munirathinam, S. (2020). Chapter Six - Industry 4.0: Industrial Internet of Things (IIOT). Adv. Comput. [Google Scholar]
  13. N. Santhosh, M. Srinivsan, & Ragupathy Karu. (2020). Internet of Things (IoT) in smart manufacturing. IOP Conference Series: Materials Science and Engineering. [Google Scholar]
  14. Priyashan, W. D. M., & Thilakarathne, N. N. (2020). IIoT Framework for SME level Injection Molding Industry in the Context of Industry 4.0. SSRN Electronic Journal. [Google Scholar]
  15. Gupta, S., Justy, T., Kamboj, S., Kumar, A., & Kristoffersen, E. (2021). Big data and firm marketing performance: Findings from knowledge-based view. Technological Forecasting and Social Change, 171, 120986. [CrossRef] [Google Scholar]
  16. Sahoo, S. (2021). Big data analytics in manufacturing: a bibliometric analysis of research in the field of business management. International Journal of Production Research, 60, 6793-6821. [Google Scholar]
  17. Chang, K.-H., Sun, Y.-J., Lai, C.-A., Chen, L.-D., Wang, C.-H., Chen, C.-J., & Lin, C.-M. (2021). Big data analytics energy-saving strategies for air compressors in the semiconductor industry - an empirical study. International Journal of Production Research, 60, 1782-1794. [Google Scholar]
  18. Li, C., Yaqiong, C., & Shang, Y. (2021). A review of industrial big data for decision making in intelligent manufacturing. Engineering Science and Technology, an International Journal. [Google Scholar]
  19. Amalina, F., Hashem, I. A. T., Azizul, Z., Tan Fong, A., Firdaus, A., Imran, M., & Anuar, N. B. (2020). Blending Big Data Analytics: Review on Challenges and a Recent Study. IEEE Access, 8, 3629-3645. [Google Scholar]
  20. Bag, S., Pretorius, J. H. C., Gupta, S., & Dwivedi, Y. K. (2020). Role of institutional pressures and resources in the adoption of big data analytics powered artificial intelligence, sustainable manufacturing practices and circular economy capabilities. Technological Forecasting and Social Change. [Google Scholar]
  21. Jaskó, S., Skrop, A., Holczinger, T., Chován, T., & Abonyi, J. (2020). Development of manufacturing execution systems in accordance with Industry 4.0 requirements: A review of standard- and ontology-based methodologies and tools. Comput. Ind., 123, 103300. [CrossRef] [Google Scholar]
  22. Kohl, L., Ansari, F., & Sihn, W. (2021). A Modular Federated Learning Architecture for Integration of AI-enhanced Assistance in Industrial Maintenance. Competence development and learning assistance systems for the data-driven future. [Google Scholar]
  23. Chen, G., Wang, P., Feng, B., Li, Y., & Liu, D. (2020). The framework design of smart factory in discrete manufacturing industry based on cyber-physical system. International Journal of Computer Integrated Manufacturing, 33, 79-101. [CrossRef] [Google Scholar]
  24. Leivadaros, S., Kornaros, G., & Coppola, M. (2021). Secure Asset Tracking in Manufacturing through Employing IOTA Distributed Ledger Technology. 2021 IEEE/ACM 21st International Symposium on Cluster, Cloud and Internet Computing (CCGrid), 754-761. [Google Scholar]
  25. Fang, P., Yang, J., Zheng, L., Zhong, R., & Jiang, Y. (2020). Data analytics-enable production visibility for Cyber-Physical Production Systems. Journal of Manufacturing Systems, 57, 242-253. [CrossRef] [Google Scholar]
  26. Cheng, X., & Zhang, P. (2021). Service Innovation of Industrial Big Data Based on Industry 4.0 Architecture. Journal of Physics: Conference Series. [Google Scholar]
  27. Mouha, R.A. (2021) Internet of Things (IoT). Journal of Data Analysis and Information Processing, 9, 77-101. https://doi.org/10.4236/jdaip.2021.92006 [CrossRef] [Google Scholar]
  28. Xu, L. D., He, W., & Li, S. (2014, November). Internet of Things in Industries: A Survey. IEEE Transactions on Industrial Informatics, 10(4), 2233-2243. https://doi.org/10.1109/tii.2014.2300753 [CrossRef] [Google Scholar]
  29. Atzori, L., Iera, A., & Morandi, G. (2010). The internet of things: A survey. Computer networks, 54(15), 2787-2805. [CrossRef] [Google Scholar]
  30. Miorandi, S., Siciliano, A., De Pellegrini, F., & Chlamtac, I. (2012). Internet of things: Vision, application challenges, and technology. Annual Reviews in Communications, 41(1), 99-129. [Google Scholar]
  31. Song, Z., Mishra, A. R., & Saeidi, S. P. (2023). Technological capabilities in the era of the digital economy for integration into cyber-physical systems and the IoT using decision-making approach. Journal of Innovation and Knowledge, 8(2), 100356. https://doi.org/10.1016/j.jik.2023.100356 [CrossRef] [Google Scholar]
  32. Strohmer, T. (2014). The internet of things: A survey of technologies and opportunities. IEEE Wireless Communications, 11(12), 10-19. [Google Scholar]
  33. Miorandi, S., Siciliano, A., & De Pellegrini, F. (2012). Internet of things: Vision, applications and challenges. ACM Transactions on Internet Technology, 12(2), 1-19. [Google Scholar]
  34. Chen, M., Mao, S. and Liu, Y. (2014) Big Data: A Survey. Mobile Networks and Applications, 19, 171-209. https://doi.org/10.1007/s11036-013-0489-0 [CrossRef] [Google Scholar]
  35. Deng, J., Yang, L., Zhou, Y., & Liu, W. (2015). A smart wearable device for real-time health monitoring. International Journal of Distributed Sensor Networks, 11(8), 738960. [Google Scholar]
  36. Khan, M. A., Islam, S. R., & Al-Madeed, N. A. (2014). Smart traffic light control system for intelligent transportation system (ITS). In 2014 International Conference on Advanced Mechatronics, Control & Communication (AMCC) (pp. 17-21). IEEE. [Google Scholar]
  37. Lee, J., & Kao, H. (2014). Big data analytics and intelligence for manufacturing: progress, challenges and opportunities. In Proceedings of the 2014 IEEE International Conference on Industrial Engineering and Engineering Management (pp. 1538-1543). IEEE. [Google Scholar]
  38. Dubey, A. K., Singh, U., & Chaudhary, S. (2015). Big data analytics in healthcare: A review. Journal of Gigadata, 1(1), 19-28. [Google Scholar]
  39. Abdul-Qawy, Antar & Magesh, E & Tadisetty, Srinivasulu. (2015). The Internet of Things (IoT): An Overview. 5. 71-82. [Google Scholar]
  40. Lee, J., & Lee, K. H. (2015). The industrial internet of things (IIoT): enabling industrial digitalization. Springer Verlag. [Google Scholar]
  41. Lee, J., Kao, H. Y., & Xiang, W. (2014). A smart preventive maintenance system for machine tools using data mining and support vector machines. International Journal of Production Research, 52(18), 5487-5500. [Google Scholar]
  42. Davis, J. R. (2017). Predictive maintenance: New technologies for increased productivity. Industrial Robot: An International Journal, 44(3), 263-270. [Google Scholar]
  43. Zheng, P., Dong, H., & Srinivasan, R. S. (2020). Industrial Internet of Things for agile manufacturing: A case study. International Journal of Production Research, 58(1-2), 101-118. [Google Scholar]
  44. Caesarendra, W., Pappachan, B., Wijaya, T., Lee, D., Tjahjowidodo, T., Then, D., & Manyar, O. (2018). An AWS Machine Learning-Based Indirect Monitoring Method for Deburring in Aerospace Industries Towards Industry 4.0. Applied Sciences, 8(11), 2165. https://doi.org/10.3390/app8112165 [CrossRef] [Google Scholar]
  45. Vidal, E., Barros, A. C., & Bassani, R. S. (2014). The impact of cyber-physical systems on industrial supply chains. International Journal of Production Research, 52(18), 5307-5322. [Google Scholar]
  46. Kusiak, A., & Tang, Y. (2017). Big data and industrial analytics: Opportunities and challenges for manufacturing. Computers & Industrial Engineering, 104, 15-20. [Google Scholar]
  47. Xu, X., Xu, M., & Li, D. (2018). A blockchain-based quality control system for the food supply chain. IEEE Access, 6, 55546-55553. [Google Scholar]
  48. Drouvin, M., de Chérisey, C., & Charenton, W. (2018). Blockchain for industrial supply chains: the case of traceability. In Proceedings of the 2018 IEEE International Conference on [Google Scholar]
  49. Wang, L., Zhang, Y., & Gunasekaran, A. (2020). A cyber-physical system framework for Industry 4.0 smart factory: A review of technologies, enabling factors, and challenges. Computers & Industrial Engineering, 149, 106979 [Google Scholar]
  50. Wang, L., Xu, Y., & Lu, W. (2018). Predictive maintenance for smart manufacturing in big data era. IEEE Access, 6, 70574-70587. [Google Scholar]
  51. Sarma, S. S., Gope, P., & Bhadra, S. (2015). Security and privacy in industrial internet of things (IIoT): A discussion. In 2015 International Conference on Security, Privacy and Computer Communication Systems (pp. 11-16). IEEE [Google Scholar]
  52. Chen, F., Dou, W., & Zhou, P. (2014). Big data mining for predicting the health condition of machine tool spindle. The International Journal of Advanced Manufacturing Technology, 70(5-8), 725-731. [CrossRef] [Google Scholar]
  53. Sama, A., Warnars, H. L. H. S., Prabowo, H., Meyliana, & Hidayanto, A.N. (2023). Acquiring Automation and Control Data in The Manufacturing Industry: A Systematic Review. Procedia Computer Science, 227, 214-222. https://doi.org/10.1016/j.procs.2023.10.519 [CrossRef] [Google Scholar]
  54. Fan, J., & Li, Y. (2019). Big data analytics for sustainable manufacturing. In Big data analytics for sustainable manufacturing and logistics (pp. 1-17). Springer, Singapore. [Google Scholar]
  55. Zaharia, M., Chowdhury, M., Das, T., Dave, A., Ma, J., McCauley, M., & Wawrzynek, J. (2011). Spark: Cluster computing with brevity and elegance. Proceedings of the 11th ACM Symposium on Operating Systems Principles, 59-78. [Google Scholar]
  56. Valdez, Alicia & Cortes, Griselda & Castaneda, Sergio & Vazquez, Laura & Zarate, Angel & Salas, Yadira & Haces Atondo, Gerardo. (2019). Big Data Strategy. International Journal of Advanced Computer Science and Applications. 10. https://10.14569/IJACSA.2019.0100434. [Google Scholar]
  57. Akhtar, P., Alhajj, R., & Ahsan, M. (2015). Real-time analytics for big data. In Big data analytics and intelligent discovery (pp. 387-402). Springer, Cham. [Google Scholar]
  58. Kiran, S., Ravi, V., & Sastry, C. S. (2019). Big data analytics in finance: A literature review. Journal of Management Analytics, 8(2), 329-346. [Google Scholar]
  59. Chen, M., Mao, S., & Liu, Y. (2020). Big data analytics: A survey. International Journal of Data Mining, Bioinformatics, Health, and Engineering, 11(5), 1263-1274. [Google Scholar]
  60. Thoben, Klaus-Dieter & Wiesner, Stefan & Wuest, Thorsten. (2017). "Industrie 4.0" and Smart Manufacturing - A Review of Research Issues and Application Examples. International Journal of Automation Technology. 11. 4-19. https://10.20965/ijat.2017.p0004. [CrossRef] [Google Scholar]
  61. Müller, P., Voigt, K.-I., & Kiel, D. (2018). Smart manufacturing in the context of industry 4.0: An empirical investigation of German and Austrian manufacturing firms. Sustainability, 10(12), 4605. [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.