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Achiche, S., Balazinski, M., Baron, L., & Jemielniak, K. (2002). Tool wear monitoring using genetically-generated fuzzy knowledge bases. Engineering Applications of Artificial Intelligence, 15(3-4), 303-314. External link
Jemielniak, K., & Balazinski, M. (2000). Laboratory versus industrial cutting force sensor in tool condition monitoring. Journal for Manufacturing Science and Production, 3(1), 41-47. External link
Ren, Q., Achiche, S., Jemielniak, K., & Bigras, P. (2016, July). An Enhanced Adaptive Neural Fuzzy Tool Condition Monitoring for Turning Process [Paper]. IEEE International Conference on Fuzzy Systems (FUZZ 2016), Vancouver, B.C.. External link
Ren, Q., Balazinski, M., Baron, L., Jemielniak, K., Botez, R., & Achiche, S. (2014). Type-2 fuzzy tool condition monitoring system based on acoustic emission in micromilling. Information Sciences, 255, 121-134. External link
Ren, Q., Baron, L., Balazinski, M., & Jemielniak, K. (2013). Reliable Tool Life Estimation with Multiple Acoustic Emission Signal Feature Selection and Integration Based on Type-2 Fuzzy Logic. In Sadeghian, A., Mendel, J. M., & Tahayori, H. (eds.), Advances in Type-2 Fuzzy Sets and Systems (pp. 203-217). External link
Ren, Q., Balazinski, M., Jemielniak, K., Baron, L., & Achiche, S. (2013). Experimental and fuzzy modelling analysis on dynamic cutting force in micro milling. Soft Computing, 17(9), 1687-1697. External link
Ren, Q., Baron, L., Balazinski, M., & Jemielniak, K. (2013). Fuzzy cutting force modelling in micro-milling. Journal of Intelligent and Fuzzy Systems, 25(4), 1027-1035. External link
Ren, Q., Balazinski, M., Baron, L., & Jemielniak, K. (2008, June). Tool condition monitoring using the TSK fuzzy approach based on subtractive clustering method [Paper]. 21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, (IEA/AIE 2008), Wroclaw, Poland. External link
Shaban, Y., Yacout, S., Balazinski, M., & Jemielniak, K. (2017). Cutting tool wear detection using multiclass logical analysis of data. Machining Science and Technology, 21(4), 526-541. External link
