I would say that applied mathematics is of "utmost" importance in almost every areas of Industry.
In particular, applied linear algebra and optimization theory forms an integral part of several sectors related to industrial operations and management.
Applied mathematics plays a crucial role in the field of industry for a variety of reasons. Its importance lies in its ability to provide practical solutions, improve processes, optimize operations, and facilitate decision-making. Here are some key aspects of the significance of applied mathematics in industry:
Problem-solving and optimization: Applied mathematics provides powerful tools and techniques for solving complex problems and optimizing processes. From logistics and supply chain management to resource allocation and production scheduling, mathematical models and algorithms help industries find the most efficient and cost-effective solutions.
Data analysis and forecasting: In today's data-driven world, industries generate vast amounts of data. Applied mathematics enables the analysis and interpretation of this data, helping businesses gain valuable insights, make data-driven decisions, and develop accurate forecasts and predictions for future trends.
Engineering and design: In fields like engineering and product design, applied mathematics is essential for modeling and simulating real-world scenarios. It helps engineers and designers understand the behavior of systems, predict performance, and refine designs before actual implementation.
Financial modeling and risk management: In the financial industry, applied mathematics is vital for creating complex models that assess risks, evaluate investments, and manage portfolios. It allows financial institutions to make informed decisions, manage potential risks, and optimize their investment strategies.
Process control and automation: In industrial automation, applied mathematics is used to develop control systems that regulate and optimize processes. This ensures better quality control, increased efficiency, and reduced waste in manufacturing and production processes.
Predictive maintenance: Applied mathematics aids in predicting equipment failures and determining optimal maintenance schedules. By utilizing data and algorithms, industries can reduce downtime, extend the lifespan of machinery, and save on maintenance costs.
Machine learning and artificial intelligence: Applied mathematics underpins many machine learning and artificial intelligence algorithms. These technologies are increasingly being adopted in industries for tasks such as image recognition, natural language processing, predictive analytics, and autonomous systems.
Resource management: Whether it's managing inventory, workforce scheduling, or energy consumption, applied mathematics helps industries make optimal decisions on how to allocate and utilize resources efficiently.
Quality control and process improvement: By analyzing data and using statistical methods, industries can identify areas for process improvement and implement quality control measures. This leads to enhanced product quality and increased customer satisfaction.
In summary, applied mathematics is instrumental in enabling industries to leverage data, optimize processes, and make informed decisions. It provides a powerful toolkit for problem-solving, analysis, and modeling, making it an essential component of modern industrial practices across various sectors.
Here is a simple example. I worked for a company that produced a product out of some aluminum bars. The bars came in certain lengths. The bars had to be cut because our product needed several different lengths. Each single unit of our product needed a certain number of bar sections of one length, a different number of bar sections at a different length, and so on. Applied math was used to figure out how to cut the bars into sections in the way that minimizes material waste.
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As one of the answers pasted here.
One of them is the application of a system of linear equations in determining the optimum value (profit / loss).
Applied mathematics plays a crucial role in the field of industry and has numerous important applications.
In problem solving: Applied mathematics provides powerful tools and techniques for analyzing and solving complex problems that arise in the industrial setting. These problems could be related to optimization, data analysis, simulation, modeling, and more. By applying mathematical principles, engineers and professionals can devise efficient and effective solutions.
In decision making: Industries often face decisions that involve uncertainty and risk. Applied mathematics, particularly probability and statistics, enables decision-makers to make informed choices by analyzing data, identifying patterns, and predicting outcomes.
In process Optimization: Applied mathematics helps in optimizing processes by finding the best parameters and conditions to maximize efficiency and minimize costs. This optimization is critical in manufacturing, supply chain management, logistics, and various other industrial processes.
In predictive Modeling: In industries where forecasting future trends and behaviors is crucial, applied mathematics provides techniques like regression analysis, time-series analysis, and machine learning algorithms. These models help in predicting market demand, product performance, and other essential factors.
In engineering and design: Engineers use applied mathematics to design and develop products and systems. From structural analysis to fluid dynamics, mathematical principles underpin the understanding and improvement of designs, ensuring safety, reliability, and performance.
In control systems: Control theory, a branch of applied mathematics, is widely used in various industries to design and implement control systems. These systems help regulate and stabilize processes and equipment, leading to improved performance and safety.
In signal processing: Industries like telecommunications and audio processing rely heavily on signal processing techniques that involve advanced mathematics, such as Fourier analysis, to manipulate and interpret signals.
In financial modeling: In the financial industry, applied mathematics is essential for developing sophisticated models for pricing derivatives, risk management, portfolio optimization, and understanding market trends.
In simulation and testing: Mathematical modeling and simulation are critical for testing and validating ideas, products, and processes before implementation. This reduces the risk of costly errors and enables more efficient development.
In technology advancements: Applied mathematics often drives technological advancements. From cryptography to artificial intelligence, mathematical concepts are at the core of many modern technologies that impact industries across the board.
The role of applied mathematics is significant in the industrial field.
You can start by reading or inspecting a book published in 2012 by Patrick Bangert, entitled " Optimization for industrial problems".
You will be able to find some important case studies comprising the role of statistical methods, neural networks, and meta-heuristic optimization in solving crucial practical industrial problems.
All the best.
Applied mathematics is indispensable across industries for various key reasons:
Hi ,
Data encryption or cryptography is a form of applied mathematics. This kind of science is dedicated for preventing data from hackers. Please take a look on my paper:
■ A. Abusukhon, Z. Mohammad, A. Al-Thaher (2021) An authenticated, secure, and mutable multiple-session-keys protocol based on elliptic curve cryptography and text_to-image encryption algorithm. Concurrency and computation practice and experience. [Science Citation Index].
■ Ahmad Abusukhon, Bilal Hawashin and Mohammad Lafi (2021) An Efficient Algorithm for Reducing the Power Consumption in Offices Using the Internet of Things, International Journal of Advances in Soft Computing and its Applications (IJASCA). http://ijasca.zuj.edu.jo/Volumes.aspx
■ A. Abusukhon, N. Anwar, M. Mohammad, Z., Alghanam, B. (2019) A hybrid network security algorithm based on Diffie Hellman and Text-to-Image Encryption algorithm. Journal of Discrete Mathematical Sciences and Cryptography. 22(1) pp. 65- 81. (SCOPUS). https://www.tandfonline.com/doi/abs/10.1080/09720529.2019.1569821
■ A. Abusukhon, B.Wawashin, B. (2015) A secure network communication protocol based on text to barcode encryption algorithm. International Journal of Advanced Computer Science and Applications (IJACSA). (ISI indexing). https://thesai.org/Publications/ViewPaper?Volume=6&Issue=12&Code=IJACSA&Seri alNo=9
■ A. Abusukhon, Talib, M., and Almimi, H. (2014) Distributed Text-to-Image Encryption Algorithm. International Journal of Computer Applications (IJCA), 106 (1). [ available online at : https://www.semanticscholar.org/paper/Distributed-Text-to-Image-Encryption-Algorithm-Ahmad_Mohammad/0764b3bd89e820afc6007b048dac159d98ba5326]
■ A. Abusukhon (2013) Block Cipher Encryption for Text-to-Image Algorithm. International Journal of Computer Engineering and Technology (IJCET). 4(3) , 50-59. http://www.zuj.edu.jo/portal/ahmad-abu-alsokhon/wpcontent/uploads/sites/15/BLOCK_CIPHER-ENCRYPTION-FOR-TEXT-TO-IMAGE ALGORITHM.pdf
■ A. Abusukhon, Talib, M. and Nabulsi, M. (2012) Analyzing the Efficiency of Text_o-Image Encryption Algorithm. International Journal of Advanced Computer Science and Applications ( IJACSA )(ISI indexing) , 3(11), 35 – 38. https://thesai.org/Publications/ViewPaper?Volume=3&Issue=11&Code=IJACSA&Seri alNo=6
■ A. Abusukhon, Talib M., Issa, O. (2012) Secure Network Communication Based on Text to Image Encryption. International Journal of Cyber-Security and Digital Forensics (IJCSDF), 1(4). The Society of Digital Information and Wireless Communications (SDIWC) 2012. https://www.semanticscholar.org/paper/SECURE_NETWORK_COMMUNICATION-BASED-ON-TEXT-TO-IMAGE-Abusukhon_Talib/1d122f280e0d390263971842cc54f1b044df816
Hope this is useful.
Regards
Ahmad
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