LEADER 03906nam  22005295  450 
001 9910483370803321
005 20251113190544.0
010   $a3-030-70009-7
024 7 $a10.1007/978-3-030-70009-6
035   $a(CKB)4100000011950221
035   $a(MiAaPQ)EBC6634997
035   $a(Au-PeEL)EBL6634997
035   $a(OCoLC)1257666807
035   $a(PPN)255883897
035   $a(DE-He213)978-3-030-70009-6
035   $a(EXLCZ)994100000011950221
100   $a20210531d2021      u|         0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aFuturistic Trends in Intelligent Manufacturing $eOptimization and Intelligence in Manufacturing /$fedited by K. Palanikumar, Elango Natarajan, Ramesh Sengottuvelu, J. Paulo Davim
205   $a1st ed. 2021.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2021.
215   $a1 online resource (268 pages)
225 1 $aMaterials Forming, Machining and Tribology,$x2195-092X
300   $aIncludes index.
311 1 $a3-030-70008-9 
327   $aChapter 1. Smart Manufacturing- a lead way to sustainable manufacturing -- Chapter 2. Smart machining of Titanium alloy using ANN encompassed Prediction model and GA Optimization -- Chapter 3. Fuzzy Interference System of Drilling Parameters for Delrin Parts -- Chapter 4. Optimization and Effect Analysis of Sustainable Micro Electrochemical Machining using Organic Electrolyte -- Chapter 5. Artificial Fish Swarm Algorithm Driven Optimization for Copper-Nano Particles Suspended Sodium Nitrate Electrolyte enabled ECM on Die Tool Steel -- Chapter 6. Comparative Analysis between Conventional Method Versus Machine Learning Method for Pipeline Condition Prediction -- Chapter 7. Application of Back Propagation Algorithm in Weave Stir Friction Welding ? a Study -- Chapter 8. ANFIS and RSM Modelling Analysis on Surface Roughness of Particleboard Composite Panels in Drilling with HSS Drills -- Chapter 9. Machine Learning for Smart Manufacturing for Healthcare Applications -- Chapter 10. A comparative analysis of two soft computing methods for sales forecasting in dairy production: a case study -- Chapter 11. Augumented reality and Virtual reality towards intelligent manufacturing -- Chapter 12. Industrial IoT towards Intelligent Manufacturing -- Chapter 13. Cyber-Physical Systems: A Pilot adoption for intelligent Manufacturing -- Chapter 14. Intelligent machining of abrasive jet on Carbon Fiber and Glass Fiber Polymeric Composites using modified Nozzle -- Chapter 15. Additive Manufacturing of Nylon Parts and Implication study on Change in Infill densities and structures.
330   $aThis book shows how Industry 4.0 is a strategic approach for integrating advanced control systems with Internet technology enabling communication between people, products and complex systems. It includes processes such as machining features, machining knowledge, execution control, operation planning, machine tool selection and cutting tool. This book focuses on different articles related to advanced technologies, and their integration to foster Industry 4.0, being useful for researchers as well as industrialists to refer and utilize the information in production control.
410  0$aMaterials Forming, Machining and Tribology,$x2195-092X
606   $aIndustrial engineering
606   $aProduction engineering
606   $aIndustrial and Production Engineering
615  0$aIndustrial engineering.
615  0$aProduction engineering.
615 14$aIndustrial and Production Engineering.
676   $a658.5
702   $aPalanikumar$b K.
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910483370803321
996   $aFuturistic trends in intelligent manufacturing$92585615
997   $aUNINA