Towards an automated decision support system for the identification of additive manufacturing part candidates

Author:

Yang ShengORCID,Page Thomas,Zhang Ying,Zhao Yaoyao FionaORCID

Funder

Natural Sciences and Engineering Research Council of Canada

McGill University

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Industrial and Manufacturing Engineering,Software

Reference87 articles.

1. ADML (Additive Design and Manufacturing Laboratory) (2019a). ADML website app. GitHub. Retrieved September 9, 2019, from https://github.com/adml-mcgill/website/tree/master/app.

2. ADML (Additive Design and Manufacturing Laboratory) (2019b). Automated candidate detection for additive manufacturing (BETA). ADML. Retrieved September 9, 2019, from http://adml.lab.mcgill.ca/app/.

3. Aoyagi, K., Wang, H., Sudo, H., & Chiba, A. (2019). Simple method to construct process maps for additive manufacturing using a support vector machine. Additive Manufacturing, 27, 353–362.

4. ASTM International F42.91. (2015). Standard terminology for additive manufacturing—general principles—terminology. West Conshohocken: ASTM International.

5. Babic, B., Nesic, N., & Miljkovic, Z. (2008). A review of automated feature recognition with rule-based pattern recognition. Computers in Industry, 59(4), 321–337.

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