Year : 2020
Application of artificial neural network techniques in computer aided process planning – A review
Cite this Research Publication : Natarajan, K.K., Gokulachandran J, “Application of artificial neural network techniques in computer aided process planning - A review”, International Journal of Process Management and Benchmarking, Vol.11, Issue.1, pp: 80-100, DOI: 10.1504/IJPMB.2021.112257, August 2020.
Publisher : International Journal of Process Management and Benchmarking
Year : 2020
Artificial neural network based machining operation selection for prismatic components
Cite this Research Publication : K. K. Natarajan and Dr. Gokulachandran J., “Artificial Neural Network Based Machining Operation Selection for Prismatic Components”, International Journal of Advanced Science, Engineering and information Technology, vol. 10, no. 2, pp. 618–628, 2020.
Publisher : International Journal on Advanced Science, Engineering and Information Technology
Year : 2019
Effect of composition and aging time on hardness and wear behavior of Cu-Ni-Sn spinodal alloy
Cite this Research Publication : Dr. Ilangovan S., Vaira Vignesh R., Dr. Padmanaban R., and Dr. Gokulachandran J., “Effect of composition and aging time on hardness and wear behavior of Cu-Ni-Sn spinodal alloy”, Journal of Central South University, vol. 26, no. 10, pp. 2634-2642, 2019.
Publisher : Journal of Central South University, Central South University of Technology,
Year : 2019
The Engine Testing Work-flow Analysis through Value Stream Mapping and Simulation
Cite this Research Publication :
Sreejyothi, M. Thennarasu, and Dr. Gokulachandran J., “The Engine Testing Work-flow Analysis through Value Stream Mapping and Simulation”, International Journal of Mechanical and Production Engineering Research and Development (IJMPERD), vol. 9, no. 2, pp. 477-484, 2019.
Publisher : International Journal of Mechanical and Production Engineering Research and Development (IJMPERD)
Year : 2018
Prediction of remaining useful life of cutting tools: a comparative study using soft computing methods
Cite this Research Publication :
Dr. Gokulachandran J. and Dr. Padmanaban R., “Prediction of Remaining Useful life of Cutting Tools: A Comparative Study using Soft Computing Methods”, International Journal of Process Management and Benchmarking, vol. 8, no. 2, pp. 156-181, 2018.
Publisher : International Journal of Process Management and Benchmarking
Year : 2015
Risk assessment and management in a manufacturing industry
Cite this Research Publication : M. Nithin and Dr. Gokulachandran J., “Risk assessment and management in a manufacturing industry”, International Journal of Applied Engineering Research, vol. 10, pp. 17303-17314, 2015.
Publisher : International Journal of Applied Engineering Research
Year : 2015
Prediction of cutting tool life based on Taguchi approach with fuzzy logic and support vector regression techniques
Cite this Research Publication : Dr. Gokulachandran J. and Mohandas, K., “Prediction of cutting tool life based on Taguchi approach with fuzzy logic and support vector regression techniques”, International Journal of Quality & Reliability Management, vol. 32, pp. 270-290, 2015.
Publisher : International Journal of Quality Reliability Management
Year : 2015
Implementation of cleaner production strategies in a manufacturing industry
Cite this Research Publication : K. S. Sangeeth Kumar and Dr. Gokulachandran J., “Implementation of cleaner production strategies in a manufacturing industry”, International Journal of Applied Engineering Research, vol. 10, pp. 17291-17302, 2015.
Publisher : International Journal of Applied Engineering Research
Year : 2013
Comparative study of two soft computing techniques for the prediction of remaining useful life of cutting tools
Cite this Research Publication : Dr. Gokulachandran J., K. Mohandas, and Dr. Padmanaban R., “Comparative study of two soft computing techniques for the prediction of remaining useful life of cutting tools”, Journal of Intelligent Manufacturing, vol. 26, pp. 255-268, 2013.
Publisher : Journal of Intelligent Manufacturing
Year : 2013
Application of artificial neural network and fuzzy logic method for remaining useful life assessment of cutting tools
Cite this Research Publication : Dr. Gokulachandran J. and Mohandas, K., “Application of artificial neural network and fuzzy logic method for remaining useful life assessment of cutting tools”, International Journal of Logistics and Supply Chain management, vol. 5, pp. 9-19, 2013.
Publisher : International Journal of Logistics and Supply Chain management
Year : 2012
Tool life prediction model using regression and artificial neural network analysis
Cite this Research Publication : Dr. Gokulachandran J. and Mohandas, K., “Tool life prediction model using regression and artificial neural network analysis”, International Journal of Production and Quality Engineering, vol. 3, no. 1, pp. 9-16, 2012.
Publisher : International Journal of Production and Quality Engineering
Year : 2012
Predicting remaining useful life of cutting tools with regression and ANN analysis
Cite this Research Publication : Dr. Gokulachandran J. and K. Mohandas, “Predicting remaining useful life of cutting tools with regression and ANN analysis”, International Journal of Productivity and Quality Management, vol. 9, pp. 502-518, 2012.
Publisher : International Journal of Productivity and Quality Management
Year : 2012
Application of Regression and Fuzzy Logic Method for Prediction of Tool Life
Cite this Research Publication : Dr. Gokulachandran J. and Mohandas, K., “Application of Regression and Fuzzy Logic Method for Prediction of Tool Life”, Procedia Engineering, vol. 38, pp. 3900 - 3912, 2012.
Publisher : Procedia Engineering
Year : 2006
Optimum Scheduling/Cost Control Using Network Analysis
Cite this Research Publication : P. Raghuram and .Gokulachandran, J., “Optimum Scheduling/Cost Control Using Network Analysis”, Journal of Industrial Engineering, vol. XXXV , pp. 11-18., 2006.
Publisher : Journal of Industrial Engineering
Year : 2005
Design for quality in agile manufacturing environment through modified orthogonal array-based experimentation
Cite this Research Publication : Agile manufacturing systems, Agile Production, Arrays, Customer satisfaction, Delphi method, Experimentation, Mathematical models, Pumps, Quality control, Quality improvement, Societies and institutions, Taguchi methods
Publisher : Journal of Manufacturing Technology Management