Machine Intelligence in Mechanical Engineering explains the latest applications of machine intelligence and data-driven decision-making in mechanical engineering industries. By providing introductory theory, trouble-shooting case studies, detailed algorithms and implementation instructions, this interdisciplinary book will help readers explore additional applications in their own fields. Those with a mechanical background will learn the important tasks related to preprocessing of datasets, feature extraction, verification and validation of machine learning models which unlock these new methods.
Machine Intelligence is currently a key topic in industrial automation, enabling machines to solve complex engineering tasks and driving efficiencies in the smart production line. Smart preventative maintenance systems can prevent machine downtime, smart monitoring and control can produce more effective workflows with less human intervention.
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Table of Contents
1. Machine Intelligence in Mechanical Engineering: An Introduction2. A smart production line management system using Face Recognition and Augmented reality
3. Maintenance Optimization through Equipment Performance Prediction using Machine Learning based on In line Instrument Datasets
A surface Condenser Case Study
4. Minimizing inter-cellular movement of parts and maximizing the utilization of machines using Correlation index-based clustering algorithm
5. Application of Augmented Reality and Virtual Reality Technologies for Maintenance and Repair of Automobile and Equipment in Mechanical Engineering
6. Application of Machine Vision Technology in Manufacturing Industries-A study
7. Estimation of Wing Stall Delay Characteristics with Outward Dimples using Numerical Analysis
8. An IoT-based integrated safety framework of autonomous vehicles for Special Needs Society
9. Motion Planning and Control for Autonomous Vehicle Collision Avoidance System Using Potential Field-Based Parameter Scheduling
10. Long-Term Predictive Maintenance System with Application and Commercialization to Industrial Conveyors
11. Predicting the mechanical behavior of CFRP using machine learning methods: a systematic review
12. Application of computationally intelligent modelling to glass fibre-reinforced plastics drilling
13. Applied Advanced Analytics in Marketing of Mechanical Products
14. Information and Communication Technologies: Enablers for the successful implementation of Supply Chain 4.0
15. Machine Learning Implementation in Tyre Compounding
16. Machine Intelligence based learning for ecological transportation
17. A review on social impacts of automation on human capital in Malaysia
18. Autonomous systems with intelligent agents.
19. Human-Like Driver Model for Emergency Collision Avoidance using Non-linear Autoregressive with Exoganeous Inputs Neural Network
20. Securing Cloud Application using SHAKE256 Hash Algorithm & Antiforgery token in industrial environment
21. Deep Learning Applied Solid Waste Recognition Targeting Sustainable Development Goal
Authors
K. Palanikumar Professor and Principal, Sri Sairam Institute of Technology, Chennai, Tamil Nadu, India.K. Palanikumar is a professor and principal at Sri Sai Ram Institute of Technology, Chennai, India. He has more than 25 years of experience in teaching and research. He received a "National Best Researcher Award� from ISTE and published more than 100 papers in SCI Journals.
Elango Natarajan Department of Mechanical Engineering, Faculty of Engineering, Technology and Built Environment, UCSI University, Kuala Lumpur, Malaysia.Elango Natarajan is a chartered mechanical engineer (CEng.), who specialized in mechanical engineering design, CAE, optimization, and soft robotics. He has worked for engineering colleges/universities for over 20 years in various academic positions.
S. Ramesh Rajalakshmi Engineering College, Chennai. Dr. S. Ramesh is an Assistant Professor (SS) in the Department of Mechatronics Engineering, Rajalakshmi Engineering College, Thandalam, Chennai. He has completed his Ph.D. degree in Embedded Systems/Machine Learning from VIT University, Chennai in 2020, an M. Tech. Degree in Embedded Systems from SRM University, Chennai, Tamilnadu, India in 2011, B.E. Degree from National Engineering College, Kovilpatti, Tamilnadu, India in 2008. In addition to this, he is currently doing Post Doctoral Research in Malaysia. He has over 13 years of Teaching and Research Experience at various Universities and Engineering Colleges around India. J. Paulo Davim Department of Mechanical Engineering, University of Aveiro, Aveiro, Portugal. Prof. (Dr.) J. Paulo Davim is a Full Professor at the University of Aveiro, Portugal, with over 35 years of experience in Mechanical, Materials, and Industrial Engineering. He holds multiple distinguished academic titles, including a PhD in Mechanical Engineering and a DSc from London Metropolitan University. He has published over 300 books and 600 articles, with more than 36,500 citations. He is ranked among the world's top 2% scientists by Stanford University and holds leadership positions in numerous international journals, conferences, and research projects.
