Tamal Ghosh
Bakgrunn og aktiviteter
Tamal is a researcher of SFI Manufacturing at the IVB. He has a strong background and interest in the area of Machine Learning and Big Data Analysis, evolutionary and nature/inspired algorithms, designing-planning-optimization of smart manufacturing facilities in Industry 4.0. He is an expert in building mathematical models to aid Decision-Support Systems, Multi-Criteria Decision-Making tools. He is also an expert of soft-computing algorithms and Artificial Intelligent techniques. He is an avid computer programmer. He has many good publications in reputed journals and conferences.
Future Research Focus:
Data analysis using the combination of machine learning and optimization and scientific problem-solving
Research Theme:
Computational Intelligence, Data Analysis, Evolutionary and Nature-Inspired Optimization, Deep Learning, Mathematical Programming,
Education:
(2017) PhD (Production Engineering), Jadavpur University
(2011) M.Tech (Industrial Engineering), WBUT Kolkata
(2008) B.Tech (Computer Engineering), NIT Calicut
(2017) PhD (Production Engineering), Jadavpur University
(2011) M.Tech (Industrial Engineering), WBUT Kolkata
(2008) B.Tech (Computer Engineering), NIT Calicut
Vitenskapelig, faglig og kunstnerisk arbeid
Viser et utvalg av aktivitet. Se alle publikasjoner i databasen
2020
- (2020) Optimal Design of Manufacturing Cells Considering Machine Usage Percentage. Journal of Advanced Manufacturing Systems. vol. 19 (03).
- (2020) Deploying NSBA algorithm for bi-objective manufacturing cells considering percentage utilisation of machines. International Journal of Intelligent Systems Technologies and Applications. vol. 19 (3).
- (2020) Generalized approach for multi-response machining process optimization using machine learning and evolutionary algorithms. Engineering Science and Technology, an International Journal (JESTECH). vol. 23 (3).
- (2020) Machine Learning Based Heuristic Technique for Multi-response Machining Process. Lecture Notes in Mechanical Engineering.
- (2020) NSGA III for CNC End Milling Process Optimization. Communications in Computer and Information Science.
- (2020) A Surrogate-Assisted Optimization Approach for Multi-Response End Milling of Aluminium Alloy AA3105. The International Journal of Advanced Manufacturing Technology. vol. 111.
2019
- (2019) Data-driven surrogate assisted evolutionary optimization of hybrid powertrain for improved fuel economy and performance. Energy. vol. 183.
- (2019) Generalized utilization-based similarity coefficient for machine-part grouping problem in cellular manufacturing. Management and Production Engineering Review. vol. 10 (4).
- (2019) CFNN-PSO: An Iterative Predictive Model for Generic Parametric Design of Machining Processes. Applied Artificial Intelligence. vol. 33 (11).
- (2019) Data-Driven Beetle Antennae Search Algorithm for Electrical Power Modeling of a Combined Cycle Power Plant. Advances in Intelligent Systems and Computing.
- (2019) Development and correlation analysis of non-dominated sorting buffalo optimization NSBUF II using Taguchi’s design coupled gray relational analysis and ANN. Applied Soft Computing. vol. 85.
2018
2017
- (2017) Utilization-based grouping efficiency and multi-criteria decision approach in designing of manufacturing cells. Proceedings of the Institution of mechanical engineers. Part B, journal of engineering manufacture.
2016
- (2016) An Immune Genetic algorithm for inter-cell layout problem in cellular manufacturing system. Production Engineering. vol. 10 (2).
- (2016) Applying soft-computing techniques in solving dynamic multi-objective layout problems in cellular manufacturing system. The International Journal of Advanced Manufacturing Technology. vol. 86 (1-4).
2014
- (2014) AI-based techniques in cellular manufacturing systems: a chronological survey and analysis. International Journal of Industrial and Systems Engineering. vol. 17 (4).
2013
- (2013) Hybrid principal component analysis technique to machine-part grouping problem in cellular manufacturing system. International Journal of Advanced Operations Management (IJAOM). vol. 5 (3).
- (2013) Neuro-genetic impact on cell formation methods of Cellular Manufacturing System design: A quantitative review and analysis. Computers & industrial engineering. vol. 64 (1).
2012
- (2012) Application of Soft-Computing Methods in Cellular Manufacturing. IGI Global. 2012.
- (2012) Modelling of Optimal Design of Manufacturing Cell Layout Considering Material Flow and Closeness Rating Factors. 4th International & 25th AIMTDR Conference ; 2012-12-14 - 2012-12-16.
- (2012) Particle swarm optimisation in development of component families using classification and coding system: a case study in an Indian manufacturing firm. International Journal of Services and Operations Management. vol. 13 (4).
- (2012) Soft Computing Based Techniques in Cellular Manufacturing Systems: Various State-of-the-art Heuristics to Manufacturing Cell Formation Problems. 2012. ISBN 3659245763.
- (2012) A neuro-agglomerative approach to strategic design of a manufacturing cell. International Journal of Intelligent Enterprise. vol. 1 (3/4).
2011
- (2011) An Effective Machine-Part Grouping Algorithm to Construct Manufacturing Cells. National Conference on Industrial Engineering (NCIE 2011) . WBUT India; 2011-02-10 - 2012-12-12.
- (2011) Applying improved median linkage heuristic for cell formation problem considering binary data. International Journal of Modelling in Operations Management. vol. 1 (4).
- (2011) EFFECTIVE CLUSTERING METHOD FOR GROUP TECHNOLOGY PROBLEMS: A SHORT COMMUNICATION. E-Journal of Science & Technology. vol. 6 (4).
- (2011) Renewable energy scenario and disregarded petition of rural populace of an Indian island: A critical survey and concept of an inexpensive artifact. The International Journal of Energy and Environment. vol. 2 (3).
- (2011) TAGUCHI’S ORTHOGONAL DESIGN BASED SOFT COMPUTING METHODOLOGY TO SOLVE CELL FORMATION PROBLEM ON PRODUCTION SHOP FLOOR. Acta Technica Corvininesis. vol. 4 (4).
- (2011) SAPFOCS: a metaheuristic based approach to part family formation problems in group technology. international journal of management science and engineering management. vol. 6 (3).
- (2011) Fa-walca-cf : a Novel Method to Machine-part Grouping Problems. Advances in Production Engineering & Management. vol. 6 (4).
- (2011) Solving component family identification problems on manufacturing shop floor. International Journal of Advancements in Technology. vol. 2 (1).
- (2011) A hybrid neural network approach to cell formation in cellular manufacturing. International Journal of Intelligent Systems Technologies and Applications. vol. 10 (4).
- (2011) Fuzzy ART K-Means Clustering Technique: a hybrid neural network approach to cellularmanufacturing systems. International journal of computer integrated manufacturing (Print). vol. 24 (10).
- (2011) Hybrid Fuzzy-ART based K-Means Clustering Methodology to Cellular Manufacturing Using Operational Time. International Conference on Operational Excellence for Global Competitiveness . RVEC; Bangalore. 2011-02-05 - 2011-02-07.
2010
- (2010) Application of analytic hierarchy process and heuristic algorithm in solving vendor selection problem. Business Intelligence Journal. vol. 4 (1).
- (2010) Genetic rule based techniques in cellular manufacturing (1992-2010): a systematic survey. International Journal of Engineering, Science and Technology. vol. 2 (5).
- (2010) Coding and classification based heuristic technique for workpiece grouping problems in cellular manufacturing system. International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies. vol. 2.
- (2010) Meta-heuristics in cellular manufacturing: A state-of-the-art review. International Journal of Industrial Engineering Computations. vol. 2 (1).
- (2010) A hybrid heuristic based clustering algorithm to design manufacturing cell. Management and Production Engineering Review. vol. 1 (4).
Lenker
Kompetanseord
- Algoritmer og beregnbarhetsteori
- Industri- og produktdesign
- Produksjon og driftsteknologi
- Kunstig intelligens
- Maskinlæring
- Multivariate statistical analyses
- Big Data
- Matematisk modellering
- Manufacturing and production engineering
- Bio Inspired Algorithms
- Evolutionary Computing
- Deep learning
- Artificial Neural Networks