Towards a Framework for Intelligent Cyber-Physical System (iCPS) Design
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-43126-5_19
Reference22 articles.
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2. Villalonga, A., et al.: A decision-making framework for dynamic scheduling of cyber-physical production systems based on digital twins. Annu. Rev. Control 51, 357–373 (2021). https://doi.org/10.1016/j.arcontrol.2021.04.008
3. Doltsinis, S., Ferreira, P., Mabkhot, M.M., Lohse, N.: A Decision Support System for rapid ramp-up of industry 4.0 enabled production systems. Comput. Ind. 116 (2020). https://doi.org/10.1016/j.compind.2020.103190
4. Attajer, A., Darmoul, S., Chaabane, S., Sallez, Y., Riane, F.: An analytic hierarchy process augmented with expert rules for product driven control in cyber-physical manufacturing systems. Comput. Ind. 143 (2022). https://doi.org/10.1016/j.compind.2022.103742
5. Cimini, C., Pirola, F., Pinto, R., Cavalieri, S.: A human-in-the-loop manufacturing control architecture for the next generation of production systems. J. Manuf. Syst. 54, 258–271 (2020). https://doi.org/10.1016/j.jmsy.2020.01.002
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