A Quality-Oriented Decision Support Framework: Cyber-Physical Systems and Model-Based Design to Develop Design for Additive Manufacturing Features
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-62578-7_4
Reference10 articles.
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2. Baijens, J., Helms, R., Bollen, L.: Data analytics and SMEs: how maturity improves performance. In: Proceedings - 2022 IEEE 24th Conference on Business Informatics, CBI 2022, vol. 1, pp. 31–39 (2022). https://doi.org/10.1109/CBI54897.2022.00011
3. Frazier, W.E.: Metal additive manufacturing: a review. J. Mater. Eng. Perform. 23, 1917–1928 (2014). https://doi.org/10.1007/s11665-014-0958-z
4. Lamperti, S., Cavallo, A., Sassanelli, C.: Digital servitization and business model innovation in SMEs: a model to escape from market disruption. IEEE Trans. Eng. Manag., 1–15 (2023). https://doi.org/10.1109/TEM.2022.3233132
5. McMillan, M., Leary, M., Brandt, M.: Computationally efficient finite difference method for metal additive manufacturing: a reduced-order DFAM tool applied to SLM. Mater. Des. 132, 226–243 (2017). https://doi.org/10.1016/J.MATDES.2017.06.058
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