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fachmedien.de - spezialisierte Fachinformationen für Studium und Beruf
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Pratap Singh / Kumar / Kataria

Evolutionary Optimization of Material Removal Processes

Medium: Buch
ISBN: 978-1-032-19270-3
Verlag: CRC Press
Erscheinungstermin: 09.10.2024
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The text comprehensively focuses on the concepts, implementation, and application of evolutionary algorithms for predicting, modeling, and optimizing the various material removal processes from their origin to the current advancements. This one-of-a-kind book encapsulates all the features related to the application and implementation of evolutionary algorithms for the purpose of predicting and optimizing the process characteristics of different machining methods and their allied processes that will provide comprehensive information. It broadly explains the concepts of employing evolutionary algorithm-based optimization in a broad domain of various material removal processes. Therefore, this book will enable prospective readers to take full advantage of recent findings and advancements in the fields of traditional, advanced, micro, and hybrid machining, among others. Moreover, the simplicity of its writing will keep readers engaged throughout and make it easier for them to understand the advanced topics.

The book-

- Offers a step-by-step guide to implement evolutionary algorithms for the overall optimization of conventional and contemporary machining processes

- Provides in-depth analysis of various material removal processes through evolutionary optimization

- Details an overview of different evolutionary optimization techniques

- Explores advanced processing of various engineering materials-based case studies

It further discusses different nature-inspired algorithms-based modeling, prediction, and modeling of machining responses in attempting advanced machining of the latest materials and related engineering problems along with case studies and practical examples. It will be an ideal reference text for graduate students and academic researchers working in the fields of mechanical engineering, aerospace engineering, industrial engineering, manufacturing engineering, and materials science.

Produkteigenschaften

  • Artikelnummer: 9781032192703
  • Medium: Buch
  • ISBN: 978-1-032-19270-3
  • Verlag: CRC Press
  • Erscheinungstermin: 09.10.2024
  • Sprache(n): Englisch
  • Auflage: 1. Auflage 2024
  • Produktform: Kartoniert, Paperback
  • Gewicht: 386 g
  • Seiten: 250
  • Format (B x H x T): 156 x 234 x 14 mm
  • Ausgabetyp: Kein, Unbekannt

Themen

Autoren/Hrsg.

Herausgeber

Chapter 1 Experimental Investigation of Surface Roughness for Turning of UD-GFRP Composite Using PSO, GSA and PSOGSA Technique
Meenu and Surinder KumarChapter 2 Multi-response Optimization During High-speed Drilling of Composite Laminate Using Grey Entropy Fuzzy (GEF) and Entropy Based Weight Integrated Multi-Variate Loss Function
Jalumedi Babu, Khaleel Ahmed, Lijo Paul, Abyson Scaria, and J. Paulo DavimChapter 3 Implementation of modern meta-heuristic algorithms for optimizing machinability in dry CNC finish-turning of AISI H13 die steel under annealed and hardened states
Nikolaos A. Fountas, Ioannis Papantoniou, John Kechagias, Dimitrios E. Manolakos, and Nikolaos M. VaxevanidisChapter 4 Multi-response Optimization in Turning of UD-GFRP Composites using Weighted Principal Component Analysis (WPCA)
Meenu and Surinder KumarChapter 5 Processes parameters optimization on surface roughness in turning of E-glass UD-GFRP composites using Flower Pollination Algorithm (FPA)
Surinder Kumar and MeenuChapter 6 Application of ANN and Taguchi technique for material removal rate by Abrasive Jet Machining with special abrasive materials
Sachin P. Ambade, Chetan K. Tembhurkar, Sagar Shelare and Santosh GuptaChapter 7 Investigation of MRR in face turning unidirectional GFRP composites by using Multiple Regression Methodology and Artificial Neural Network
Surinder Kumar, Meenu, and Pawan Kumar Chapter 8 Optimization of CNC Milling Parameters for Al-CNT composites using Entropy based Neutrosophic Grey Relational TOPSIS Method
Sachchida Nand, Manvandra K Singh, and C M KrishnaChapter 9 Experimental investigation of EDM potential to machine AISI 202 using Copper-alloy electrode and its modelling by Artificial Neural Network
Subhash Singh, and Girija Nandan ArkaChapter 10 Prediction and Neural Modelling of Material Removal Rate in Electrochemical Machining of Nimonic 263 Alloy
Dilkush Bairwa, Dr Ravi Pratap Singh, Dr Ravinder Kataria, Dr Ravi Butola, Dr Mohd Javaid, Shailendra Chauhan, Madhusudan PainulyChapter 11 Optimization of End Milling Process Variables Using Multi Objective Genetic Algorithm
Jignesh Girishbhai Parmar, and Dr. Komal Ghanshyambhai DaveChapter 12 Micro-Electrochemical Machining of Nimonic 263 Alloy: An Experimental Investigation and ANN-based Prediction of Radial Over Cut
Dilkush Bairwa, Dr Ravi Pratap Singh, Dr Ravinder Kataria, Dr Sandeep Singhal, Dr Narendra Kumar, Shailendra Chauhan, and Madhusudan Painuly