T.R. Vijayaram,
N Ramya,
- Professor, Department of Mechanical Engineering, School of Mechanical Engineering, BIST, BIHER, Tamil Nadu, India
- Professor, Department of Mathematics, SHSS, BIST, BIHER, Tamil Nadu, India
Abstract
One of the earliest and most fundamental fields of the physical sciences is mathematics. It has a significant impact on industrial enterprises’ bottom lines and enhances their performance in the current data-driven market. One subfield of applied mathematics is industrial mathematics. It concentrates on issues that arise in the industry and seeks answers that are pertinent to the sector. The use of mathematical models and techniques to diverse industry difficulties has garnered a lot of interest lately. Statistics, trigonometry, dynamics, optimization, and mathematical modeling approaches are all used in industrial algebra. Applied mathematics is a subfield of algebra that focuses only on practical applications and includes the study of computational and physical sciences. It is heavily utilized in computer science and engineering and is based on numerical techniques. A relatively recent area of mathematics research called “industrial mathematics” focuses on using mathematical modeling to solve practical issues in the real world, providing the groundwork for the creation of new technologies. It includes both pure and practical mathematical modeling, including dynamics, discrete mathematics such as calculus, likelihood, statistics, and partial differential equations. To put it another way, it will combine and restructure applied and pure mathematics into a dynamic form that can effectively meet the demands of diverse industries. In contrast to other sciences, industrial mathematics focuses on industry problems and seeks to identify pertinent solutions, including the most economical and efficient approach to address the issue. The need for mathematical skills is growing daily due to the intricate and advanced nature of today’s industries. The newest computer techniques, computer graphics, system reliability software testing and verification, or databases can all be used to develop solutions through mathematical models. The function and applications of algebra in industry are covered in this summary study.
Keywords: Industrial mathematics, Industry, Statistics, Mexican manufacturing, Database
[This article belongs to International Journal of Industrial and Product Design Engineering (ijipde)]
T.R. Vijayaram, N Ramya. Strategic Solutions: How Mathematics Reshapes Industrial Landscapes. International Journal of Industrial and Product Design Engineering. 2024; 02(01):-.
T.R. Vijayaram, N Ramya. Strategic Solutions: How Mathematics Reshapes Industrial Landscapes. International Journal of Industrial and Product Design Engineering. 2024; 02(01):-. Available from: https://journals.stmjournals.com/ijipde/article=2024/view=176091
Browse Figures
References
[1] Anjali Singh, Deepanshi Vij, Dr. Manimala, Ms. Sherry Verma, INTRODUCTION TO INDUSTRIAL MATHEMATICS, ICACCG2020 30-31 July, 2020, Ansal University, Gurgaon, India International Journal of Technical Research & Science (Special Issue) ISSN No.:2454-2024 (online) , DOI Number: https://doi.org/10.30780/specialissue-ICACCG2020/010 pg. 23 Paper Id: IJTRS-ICACCG2020-010 @2017, IJTRS All Right Reserved, www.ijtrs.com
[2] GYAN BAHADUR THAPA, Industrial Mathematics Concepts, Algorithms and Complexity, January 2005
[3] B. Nicola, P. Luigi: Modeling, Mathematical Methods and Scientific Computation, 1995 CRC Press
[4] C. H. Papadimitriou, K. Steiglitz: Combinatorial Optimization: Algorithms and Complexity, 2001 Prentice-Hall of India Pvt. Ltd.
[5] E. F. Thomas, H. M. David, L. S. Leon: Optimization of Chemical Processes, 2001, Second Edition, McGraw-Hill.
[6] F. Glenn, F. Peter, J. Arthur: Modeling with Differential and Difference Equations, 1997 Cambridge University Press.
[7] G. Dahl: An Introduction to Convexity, Polyhedral Theory and Combinatorial Optimization, 1997 University of Oslo, Department of Informatics, Norway.
[8] G. Dahl: An Introduction to Convexity, 2004 University of Oslo, Centre of Mathematics for Applications, Norway.
[9] G. Hadley: Nonlinear and Dynamic Programming, Second Printing 1972 Addison-Wesley Publishing Company, Inc.
[10] G. I. Saul: Linear Programming (Methods and Applications) 3rd edition, 1969. McGraw-Hill Kogakusha, Ltd.
[11] J. N. Kapur: Mathematical Modeling, 1988 (Fourth Reprint 1994) Wiley Eastern Limited New Age International Limited, Printed in India.
[12] K. Samuel: Mathematical Methods and Theory in Games, Programming, and Economics, 1959 Addison-Wesley Publishing Company, Inc.
[13] T. N. Dhamala: Mathematics in Industry, Modeling, Algorithms and Complexity, 2002, an occasional paper, proceedings of the seminar on Applicable Mathematics.
[14] Online, Industrial Engineering Application and Practice: users’ encyclopedia, Mathematical Programming.
[15] Online, SIAM Journal on Applications of Mathematics, the Roles of Mathematics, Mathematics within Non-academic Organizations.
[16] AKOOS-PNU International Conference 2014, Pusan, South Korea, Pusan National University
| Volume | 02 |
| Issue | 01 |
| Received | 16/05/2024 |
| Accepted | 29/05/2024 |
| Published | 18/06/2024 |