Hybrid Modeling and Optimization of Manufacturing [electronic resource] :Combining Artificial Intelligence and Finite Element Method / by Ramón Quiza, Omar López-Armas, J. Paulo Davim.
by Quiza, Ramón [author.]; López-Armas, Omar [author.]; Davim, J. Paulo [author.]; SpringerLink (Online service).
Material type:
BookSeries: SpringerBriefs in Applied Sciences and Technology: Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2012.Description: VIII, 95p. 67 illus. online resource.ISBN: 9783642280856.Subject(s): Engineering | Materials | Structural control (Engineering) | Engineering | Operating Procedures, Materials Treatment | Continuum Mechanics and Mechanics of Materials | Computational IntelligenceDDC classification: 670 Online resources: Click here to access online | Item type | Current location | Call number | Status | Date due | Barcode |
|---|---|---|---|---|---|
| MAIN LIBRARY | T55.4-60.8 (Browse shelf) | Available |
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| TK5105.5-5105.9 Distributed Computing and Internet Technology | QA75.5-76.95 WALCOM: Algorithms and Computation | QC350-467 Plasmonics | T55.4-60.8 Hybrid Modeling and Optimization of Manufacturing | QD71-142 Solid State Gas Sensors - Industrial Application | RB155-155.8 JIMD Reports - Case and Research Reports, 2012/2 | QA75.5-76.95 The Universal Machine |
Relevance and convenience of hybrid (AI and FEM) modeling and optimization of manufacturing processes -- Approaches for combining AI and FEM -- FEM/AI models -- AI/FEM models -- Other approaches -- Artificial intelligence tools -- AI tools for modeling -- Artificial neural networks -- Fuzzy logic and neuro-fuzzy system -- Bayesian probability -- AI tool for optimization -- Evolutionary algorithms -- Swarm intelligence -- Finite element method for manufacturing modeling -- Plasticity models -- Constitutive equations -- Finite element discretization -- Case of study -- Experimental study -- FEM-based modeling -- AI-based modeling -- Optimization -- Concluding remarks.
Artificial intelligence (AI) techniques and the finite element method (FEM) are both powerful computing tools, which are extensively used for modeling and optimizing manufacturing processes. The combination of these tools has resulted in a new flexible and robust approach as several recent studies have shown. This book aims to review the work already done in this field as well as to expose the new possibilities and foreseen trends. The book is expected to be useful for postgraduate students and researchers, working in the area of modeling and optimization of manufacturing processes.
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