Mathematical Modelling: Simulation Analysis and Industrial Applications

by Pramod Belkhode, Prashant Maheshwary, Kanchan Borkar, J.P. Modak

Overview

This book investigates human–machine systems through the use of case studies such as crankshaft maintenance, liner piston maintenance, and biodiesel blend performance. Through mathematical modelling and using various case studies, the book provides an understanding of how a mathematical modelling approach can assist in working out problems in any industrial-oriented activity.

Mathematical Modelling: Simulation Analysis and Industrial Applications details a data analysis approach using mathematical modelling sensitivity. This approach helps in the processing of any type of data and can predict the result so that based on the result, the activity can be controlled by knowing the most influencing variables or parameters involved in the phenomenon. This book helps to solve field and experimental problems of any research activity using a data-based modelling concept to assist in solving any type of problem.

Students in manufacturing, mechanical, and industrial engineering programs will find this book very useful. This topic has continued to advance and incorporate new concepts so that the manufacturing field continues to be a dynamic and exciting field of study.

Product Details

ISBN-13:	9781000840155
Publisher:	CRC Press
Publication date:	05/16/2023
Sold by:	Barnes & Noble
Format:	eBook
Pages:	230
File size:	16 MB
Note:	This product may take a few minutes to download.

About the Author

Dr. Pramod Belkhode did his doctoral research degree in Mechanical Engineering from Rashtrasant Tukadoji Maharaj Nagpur University, Nagpur. He is currently working as an Assistant Professor at Laxminarayan Institute of Technology since 2009. He has published more than thirty research papers in international journals and has delivered more than 20 guest lectures on various topics. Four students have been awarded doctoral degrees under his supervision.

Dr. P. B. Maheshwary did his double doctoral research degree in two different specializations (Machine Design and Thermal Engineering) of Mechanical Engineering. An accomplished teaching professional with more than 3 decades of teaching experience and 10 years of research experience, he has published more than twenty research papers in SCI and Scopus (A+) indexed international journals and has in-depth administrative experience which he gained as the Director of an Educational Institute since 2008. He is a self-driven, result-oriented person with flexibility and the ability to connect to all levels in an organization. Continuous self-development and continuous learning have added to his knowledge and are an asset to the Institution he is associated with.

Dr. Kanchan Borkar is currently an Assistant Engineer in the Department of Military Engineer Services under the Ministry of Defence for the last 12 years in Nagpur. She did her doctorate in Mechanical Engineering, master in Design Engineering, and graduated from Rashtrasant Tukadoji Maharaj Nagpur University, Nagpur (MS) India. She has published more than fifteen research papers in international journals and has delivered 5 guest lectures on various topics.

Dr. Jayant P. Modak is currently a professor of Mechanical Engineering at J. D. College of Engineering, Nagpur. With a keen interest in the areas of automation, the theory of experimentation, ergonomics, man-machine system, applied robotics, rotor dynamics and kinematics, and dynamics of mechanism, Dr. Modak has contributed more than 800 research paper publications, including more than 100 journals of international repute. He has won the national award for the "Best Research Paper" twice during his eminent career. He has been instrumental in developing various products and applications in the field of Mechanical Engineering and has turned out around 90 Ph.D. students and 12 postgraduate degrees by research candidates.

Table of Contents

1. Evaluation of the System. 2. Concept of Field Data Based Modelling. 3.Design of Experimentation 4.Experimentation. 5. Formulation of Mathematical Model. 6. Artificial Neural Network Simulation 7. Sensitivity Analysis. 8. Interpretation of Mathematical Models