Modern optimization techniques for advanced machining : heuristic and metaheuristic techniques / Imhade P. Okokpujie, Lagouge K. Tartibu.
Okokpujie, Imhade P., author.; Tartibu, Lagouge K., author.
2023
TJ1185
Available Online

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Title Modern optimization techniques for advanced machining : heuristic and metaheuristic techniques / Imhade P. Okokpujie, Lagouge K. Tartibu.
Author Okokpujie, Imhade P., author.
ISBN 9783031354557 (electronic bk.)
3031354559 (electronic bk.)
9783031354540
3031354540
DOI https://doi.org/10.1007/978-3-031-35455-7
Published Cham : Springer, [2023]
Copyright ©2023
Language English
Description 1 online resource (xiv, 359 pages) : illustrations (chiefly color).
Item Number 10.1007/978-3-031-35455-7 doi
Call Number TJ1185
Dewey Decimal Classification 671.3/5
Summary Advanced manufacturing via computer numerical machining is the art of producing mechanical components employed in aerospace, automobile, and industrial applications where a high level of accuracy is needed. This book focuses on the nano-machining of aluminum alloy and its optimization. The application of aluminum alloy in the manufacturing industry has increased tremendously due to its lightweight to high strength ratio and high-level resistance to corrosion. However, aluminum alloy has some challenges during the machining and manufacturing stage in order to solve real-life manufacturing challenges in advanced machining operation for sustainable production processes. Therefore, it is a need for the implementation of a general algebraic modeling system (GAMS) and other metaheuristic techniques for problem solving and to effectively develop mathematical models for high accuracy prediction and optimization under nano-lubrication machining conditions. This book discusses majorly on the major three responses in machining such as surface roughness, cutting force, and material removal rate, which will give an excellent guide to undergraduate and postgraduate students, senior research fellows in academia, operational, and strategic staff in manufacturing industries.
Bibliography, etc. Note Includes bibliographical references.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed July 27, 2023).
Added Author Tartibu, Lagouge K., author.
Series Studies in systems, decision and control ; v. 485. 2198-4190
Available in Other Form Print version: 9783031354540
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
All Resources
Overview of Advanced Machining Process
Cutting Fluid and its Application with Different Delivering Machining Techniques
Development and Application of Nano-Lubricant in Machining: A Review
Global Machining Prediction and Optimization
Multi-objective Grey Wolf Optimizer for improved machining performance
Multi-objective Ant Lion Optimizer for improved machining performance
Multi-objective Grasshopper Optimizer for improved machining performance
A multi-objective optimization approach for improving machining performance using the General Algebraic Modelling System (GAMS)
ANN and QRCCD Prediction of Surface Roughness under Biodegradable Nano-lubricant
Cutting Force Optimization under ANN and QRCCD
Material Removal Rate Optimization under ANN and QRCCD
Application of Hybrid ANN and PSO for Prediction of Surface Roughness Under Biodegradable Nano-Lubricant
Adaptive Neuro-Fuzzy Inference System for Prediction of Surface Roughness Under Biodegradable Nano-Lubricant.

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