Quality Improvement in Investment Castings Using Genetic Algorithm
Author:
Publisher
International Journal of Engineering Technologies
Subject
General Medicine
Reference16 articles.
1. Sata, A., & Ravi, B. (2019). Foundry data analytics to identify critical parameters affecting quality of investment castings. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering. 5(1): 011010.
2. Sata, A., & Ravi, B. (2017). Bayesian inference-based investment-casting defect analysis system for industrial application. The International Journal of Advanced Manufacturing Technology, 90(9), 3301-3315.
3. Kumar, M., Husain, M., Upreti, N., & Gupta, D. (2010). Genetic algorithm: Review and application. International Journal of Information Technology and Knowledge Management. Volume 2, No. 2, pp. 451-454.
4. Tranmer, M., & Elliot, M. (2008). Multiple linear regression. The Cathie Marsh Centre for Census and Survey Research (CCSR), 5(5), 1-5.
5. Yen, Y. S., Chan, Y. K., Chao, H. C., & Park, J. H. (2008). A genetic algorithm for energy-efficient based multicast routing on MANETs. Computer Communications, 31(10), 2632-2641.
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