How to cite this paper
Bachy, B & Franke, J. (2015). Modeling and optimization of laser direct structuring process using artificial neural network and response surface methodology.International Journal of Industrial Engineering Computations , 6(4), 553-564.
Refrences
Abdoul-Fatah, K., Ghislain, M., Marie-Pierre, P., & Christian, C. (2009). Artificial neural networks implementation in plasma spray process: Prediction of power parameters and in-flight particle characteristics vs. desired coating structural attributes. Surface & Coatings Technology, 203, 3361–3369.
Andre´, K., & Siuli, M. (2010). Response surface methodology. WIREs Computational Statistics. 2, March/April, 128-149.
Arun, P. & Avanish, D. (2011). Intelligent modeling of laser cutting of thin sheet. International Journal of Modeling and Optimization, 1(2), 107-112.
Bassim, B. & J?rg, F. (2014). Simulation of laser structuring by three dimensional heat transfer model. World Academy of Science, Engineering and Technology, International Journal of Mechanical, Aerospace, Industrial and Mechatronics Engineering, 8(10), 1654- 1660.
Bassim, B. & J?rg, F. (2015). Experimental investigation and optimization for the effective parameters in the laser direct structuring process. Accepted in JLMN-Journal of Laser Micro/Nanoengineering,10(2).
Butt, H. J., Cappella, B., & Kappl, M. (2005). Force measurements with the atomic force microscope: Technique, interpretation and applications. Surface science reports, 59(1), 1-152.
Evonik Industries (2014). Technical Information, VESTAMID® HTplus LDS 3031 black, Germany, February.
Horn, H., Beil, S., Wesner, D. A., Weichenhain, R., & Kreutz, E. W. (1999). Excimer laser pretreatment and metallization of polymers. Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms, 151(1), 279-284.
Ilyes, M., Abderrazak, El O. & Noureddine B. (2014). Prediction of 4340 steel hardness profile heat-treated by laser using artificial neural networks and multi regression approaches. International Journal of Engineering and Innovative Technology, 4(6), 14-22.
Kalaiselvan, K., Elango, A., & Nagarajan, N.M. (2014). Artificial neural network application on Ti/Al joint using laser beam welding. World Academy of Science, Engineering and Technology, International Journal of Mechanical, Aerospace, Industrial and Mechatronics Engineering, 8(8).
Kim, S. H., Cho, S. H., Lee, N. E., Kim, H. M., Nam, Y. W., & Kim, Y. H. (2005). Adhesion properties of Cu/Cr films on polyimide substrate treated by dielectric barrier discharge plasma. Surface and Coatings Technology, 193(1), 101-106.
Madi?a, M., Radovanovi?a, M., & Gostimirovi?b, M. (2014). ANN modeling of kerf taper angle in CO2 laser cutting and optimization of cutting parameters using Monte Carlo method. International Journal of Industrial Engineering Computations, 6, 33–42.
Margarita, S. ( 2002). Introduction to Neural Networks in Healthcare.
Milo?, M. & Gheorghe, B. & Miroslav, R., (2013). An Artificial Neural Network Approach for Analysis and Minimization of HAZ in CO2 laser cutting of stainless steel. UPB Scientific Bulletin, Series D: Mechanical Engineering,75(2), 85-96.
Mohd, I., Yasuhiro, O., & Akira, O. (2013). Neural network modeling for prediction of weld bead geometry in laser micro welding. Advances in Optical Technologies, ID 415837, 1-7.
Shandilya, P., Jain, P. K., & Jain, N. K. (2013). RSM and ANN modeling approaches for predicting average cutting speed during WEDM of SiC p/6061 Al MMC. Procedia Engineering, 64, 767-774.
Sofiane, G., Ghislain, M., & Christian C. (2004). Modeling of the APS plasma spray process using artificial neural networks: basis, requirements and an example. Computational Materials Science, 29, 315–333.
Thomas, K., & J?rg, F. (2014).Test methods and influencing factors for the adhesion strength measurement of metallized structures on thermoplastic substrates. 16th Electronics Packaging Technology Conference, Marina Bay Sands, Singapore, 255-260.
U?ur, H. (2004). Artificial Neural Networks. EE 543, Lecture Notes.
Ying L. (2011). Response Surface Methodology. Lecture Notes.
Andre´, K., & Siuli, M. (2010). Response surface methodology. WIREs Computational Statistics. 2, March/April, 128-149.
Arun, P. & Avanish, D. (2011). Intelligent modeling of laser cutting of thin sheet. International Journal of Modeling and Optimization, 1(2), 107-112.
Bassim, B. & J?rg, F. (2014). Simulation of laser structuring by three dimensional heat transfer model. World Academy of Science, Engineering and Technology, International Journal of Mechanical, Aerospace, Industrial and Mechatronics Engineering, 8(10), 1654- 1660.
Bassim, B. & J?rg, F. (2015). Experimental investigation and optimization for the effective parameters in the laser direct structuring process. Accepted in JLMN-Journal of Laser Micro/Nanoengineering,10(2).
Butt, H. J., Cappella, B., & Kappl, M. (2005). Force measurements with the atomic force microscope: Technique, interpretation and applications. Surface science reports, 59(1), 1-152.
Evonik Industries (2014). Technical Information, VESTAMID® HTplus LDS 3031 black, Germany, February.
Horn, H., Beil, S., Wesner, D. A., Weichenhain, R., & Kreutz, E. W. (1999). Excimer laser pretreatment and metallization of polymers. Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms, 151(1), 279-284.
Ilyes, M., Abderrazak, El O. & Noureddine B. (2014). Prediction of 4340 steel hardness profile heat-treated by laser using artificial neural networks and multi regression approaches. International Journal of Engineering and Innovative Technology, 4(6), 14-22.
Kalaiselvan, K., Elango, A., & Nagarajan, N.M. (2014). Artificial neural network application on Ti/Al joint using laser beam welding. World Academy of Science, Engineering and Technology, International Journal of Mechanical, Aerospace, Industrial and Mechatronics Engineering, 8(8).
Kim, S. H., Cho, S. H., Lee, N. E., Kim, H. M., Nam, Y. W., & Kim, Y. H. (2005). Adhesion properties of Cu/Cr films on polyimide substrate treated by dielectric barrier discharge plasma. Surface and Coatings Technology, 193(1), 101-106.
Madi?a, M., Radovanovi?a, M., & Gostimirovi?b, M. (2014). ANN modeling of kerf taper angle in CO2 laser cutting and optimization of cutting parameters using Monte Carlo method. International Journal of Industrial Engineering Computations, 6, 33–42.
Margarita, S. ( 2002). Introduction to Neural Networks in Healthcare.
Milo?, M. & Gheorghe, B. & Miroslav, R., (2013). An Artificial Neural Network Approach for Analysis and Minimization of HAZ in CO2 laser cutting of stainless steel. UPB Scientific Bulletin, Series D: Mechanical Engineering,75(2), 85-96.
Mohd, I., Yasuhiro, O., & Akira, O. (2013). Neural network modeling for prediction of weld bead geometry in laser micro welding. Advances in Optical Technologies, ID 415837, 1-7.
Shandilya, P., Jain, P. K., & Jain, N. K. (2013). RSM and ANN modeling approaches for predicting average cutting speed during WEDM of SiC p/6061 Al MMC. Procedia Engineering, 64, 767-774.
Sofiane, G., Ghislain, M., & Christian C. (2004). Modeling of the APS plasma spray process using artificial neural networks: basis, requirements and an example. Computational Materials Science, 29, 315–333.
Thomas, K., & J?rg, F. (2014).Test methods and influencing factors for the adhesion strength measurement of metallized structures on thermoplastic substrates. 16th Electronics Packaging Technology Conference, Marina Bay Sands, Singapore, 255-260.
U?ur, H. (2004). Artificial Neural Networks. EE 543, Lecture Notes.
Ying L. (2011). Response Surface Methodology. Lecture Notes.