Electronics in Advanced Research Industries. Alessandro Massaro

Electronics in Advanced Research Industries

integrationsManufacturing techniques and design methodsSensor technologies integrated on siliconSilicon photonics Informatic and telecommunications New information technologies (tools and technologies to manage processes, big data storage, human machine interfaces, etc.)Application platforms of information technologiesNew network and service architecturesMobile networks and servicesTechnologies for broadband networksTechnologies for information mobilityTechnologies for network securityAdvanced interfaces and robotsTechnologies for systems innovationOptical and wireless communicationTechnologies related to microelectronics, nanoelectronics, and photonics Advanced materials Technologies related to functional, multifunctional, and structural materials (self‐repairing materials, self‐adaptive materials, biocompatible materials)Development and transformation of materials (dynamic production)Techniques and new and innovative systems in assembly, self‐assembly, separation, and disassemblyTechnologies and materials for low production of carbon emissionsTechnologies related to materials for creative industriesMetrology, characterization, standardization, and quality controlTechnologies related to optimization of the use of materials Nanotechnologies Nanomaterials, nanodevices, and next generation nanosystemsScientific tools and platforms for evaluation and risk management throughout the lifecycle of nanomaterials and of nanosystemsNew production of nanomaterials in advanced devices as innovative productsSynthesis and fabrication of nanomaterialsDevelopment support technologies for nanomaterial characterization and productionModeling and design of devices in nanoscale

The enabling technologies of the application fields in the Industry 5.0 scenario are:

Nanotechnologies.

Micro‐ and nanoelectronics.

Biotechnologies.

Advanced functionalized materials.

Photonics.

Advanced materials.

Advanced production technologies.

AI and big data systems.

Biomaterials.

Virtual reality and AR.

Lab‐on‐chip.

Advanced electromagnetic sensors and compatibility.

Advanced high temperature materials.

Advanced software and hardware production technologies.

Diagnostic inspection technologies.

Innovative systems for diagnostics.

References

1 1 Vaidya, S., Prashant, A., and Bhosle, S. (2018). Industry 4.0 – a glimpse. Procedia Manufacturing 20 (1): 233–238.

2 2 Moon, S.H. (2018). Industry 4.0 for advanced manufacturing and its implementation. Eurasian Journal of Analytical Chemistry 13 (6): 491–497.

3 3 Ruppert, T., Jaskó, S., Holczinger, T., and Abonyi, J. (2018). Enabling technologies for operator 4.0: a survey. Applied Sciences 8 (1650): 1–19.

4 4 Lampropoulos, G., Siekas, K., and Anastasiadis, T. (2019). Internet of Things in the context of industry 4.0: an overview. International Journal of Entrepreneurial Knowledge 7 (1): 4–19.

5 5 Novak‐Marcincin, J., Barna, J., Janak, M., and Novakova‐Marcincinova, L. (2013). Augmented reality aided manufacturing. Procedia Computer Science 25 (1): 23–31.

6 6 Segovia, D., Mendoza, M., Mendoza, E., and González, E. (2015). Augmented reality as a tool for production and quality monitoring. Procedia Computer Science 75 (1): 291–300.

7 7 Bottani, E. and Vignali, G. (2019). Augmented reality technology in the manufacturing industry: a review of the last decade. IISE Transactions 51 (3): 284–310.

8 8 Cioffi, R., Travaglioni, M., Piscitelli, G. et al. (2020). Artificial intelligence and machine learning applications in smart production: progress, trends, and directions. Sustainability 12 (492): 1–26.

9 9 Lee, W.J., Wu, H., Yun, H. et al. (2019). Predictive maintenance of machine tool systems using artificial intelligence techniques applied to machine condition data. Procedia CIRP 80 (1): 506–511.

10 10 Pandarakone, S.E., Mizuno, Y., and Nakamura, H. (2019). A comparative study between machine learning algorithm and artificial intelligence neural network in detecting minor bearing fault of induction motors. Energies 12 (2105): 1–14.

11 11 Pérez, L., Rodríguez, Í., Rodríguez, N. et al. (2016). Robot guidance using machine vision techniques in industrial environments: a comparative review. Sensors 16 (335): 1–26.

12 12 Massaro, A. and Galiano, A. (2020). Image processing and post‐data mining processing for security in industrial applications: security in industry. In: Handbook of Research on Intelligent Data Processing and Information Security Systems (eds. S.M. Bilan and S.I. Al‐Zoubi), 117–146. Hershey, PA: IGI Global.

13 13 Massaro, A. and Galiano, A. (2020). Infrared thermography for intelligent robotic systems in research industry inspections: thermography in industry processes. In: Handbook of Research on Advanced Mechatronic Systems and Intelligent Robotics (ed. M.K. Habib), 98–125. Hershey, PA: IGI Global.

14 14 Tan, C.L. and Mohseni, H. (2018). Emerging technologies for high performance infrared detectors. Nanophotonics 7 (1): 167–197.

15 15 Kaufmann, R., Isella, G., Sanchez‐Amores, A. et al. (2011). Near infrared image sensor with integrated germanium photodiodes. Journal of Applied Physics 110 (2): 1–6.

16 16 Kumar, V., Hallqvist, C., and Ekwall, D. (2017). Developing a framework for traceability implementation in the textile supply chain. Systems 5 (33): 1–21.

17 17 Tzoulis, I. and Andreopoulou, Z. (2013). Emerging traceability technologies as a tool for quality wood trade. Procedia Technology 8 (1): 606–611.

18 18 Agrawal, T.K., Koehl, L., and Campagne, C. (2018). A secured tag for implementation of traceability in textile and clothing supply chain. The International Journal of Advanced Manufacturing Technology 99 (1): 2563–2577.

19 19 Chen, R.‐S., Chen, C.‐C., Yeh, K.C. et al. (2008). Using RFID technology in food produce traceability. WSEAS Transactions on Information Science and Applications 5 (11): 1551–1560.

20 20 Kelepouris, T., Pramatari, K., and Doukidis, G. (2007). RFID‐enabled traceability in the food supply chain. 107 (2): 183–200.

21 21 Sethi, P., Sarangi, S., and R. (2017). Internet of Things: architectures, protocols, and applications. Journal of Electrical and Computer Engineering 2017 (9324035): 1–25.

22 22 Ke, C.K., Wu, M.Y., Chan, Y.W., and Lu, K.C. (2018). Developing a BLE Beacon‐based location system using location fingerprint positioning for smart home power management. Energies 11 (3464): 1–18.

23 23 Lin, Y.‐W. and Lin, C.‐Y. (2018). An interactive real‐time locating system based on Bluetooth low‐energy beacon network. Sensors 18 (1637): 1–17.

24 24 Triantafyllou, A., Sarigiannidis, P., and Lagkas, T.D. (2018). Network protocols, schemes, and mechanisms for Internet of Things (IoT): features, open challenges, and trends. Wireless Communications and Mobile Computing https://doi.org/10.1155/2018/5349894.

25 25 Cilfone, A., Davoli, L., Belli, L., and Ferrari, G. (2019). Wireless mesh networking: an IoT‐oriented perspective survey on relevant technologies. Future Internet 11 (99): 1–35.

26 26 Froiz‐Míguez, I., Fernández‐Caramés, T.M., Fraga‐Lamas, P., and Castedo, L. (2018). Design, implementation

Скачать книгу