Is Data Science in Mechanical Engineering useful?
Hey, are you a mechanical engineering student? Yes? Do you know the usage of data science in mechanical engineering? You must have heard the term data science very often and why not. Data science is the hottest field in the market space right now. We, humans, are creating a humongous amount of data every day with deeper penetration of internet coverage around the globe. Thanks to cheaper internet plans, many new customers are coming online. The data market is growing at a phenomenal rate and is set to reach $103 billion by 2027 according to a report by Statistica. Let us explore the use of data science in the mechanical engineering field.
What is Data Science?
In simplest words, Data Science is an integration of various fields such as statistics, informatics, data analysis, and related fields for the purpose of understanding and analyzing data. It uses theories and techniques from various disciplines such as:
- Computer Science
- Information Science
- Domain Knowledge, etc.
What is Mechanical Engineering?
Mechanical Engineering is a branch of engineering that amalgamates mathematics and engineering physics concepts for the purpose of designing, analyzing, manufacturing, and maintaining mechanical systems. It is one of the earliest and widest of the engineering disciplines. Mechanical engineering requires the core understanding of subjects such as:
- Material Science
- Structural Analysis
In addition to these fundamental principles, mechanical engineers also use several tools like Computer-Aided Manufacturing (CAM), Computer-Aided Design (CAD), Product Lifecycle Management to design and analyze:
- Manufacturing plants
- Industrial Equipments and Machinery
- Heating and Cooling Systems
- Transport Systems
- Medical Devices
Relationship between Data Science and Mechanical Engineering
Although both data science and mechanical engineering are quite different fields they overlap each other in some areas. Individuals with expertise in data science & mechanical engineering are going to be in high demand in the upcoming years.
Nowadays different components of a machine or device are made using intelligent systems and techniques to enhance performance and for optimization. It is important to have suitable predictions for making better decisions in engineering studies, medical studies, and businesses.
Currently, mechanical engineers have only a limited set of tools. These tools are benchmarks of standard tools for processes like hardware design, machine control, etc. Although there is some exceptionally good software like ANSYS, CATIA, MATLAB, Abaqus, etc they are largely complex. And If something goes wrong in a project it would be really difficult for engineers and managers to identify it. Then it will become a huge disaster resulting in a big financial loss along with loss of time, energy, and manpower.
That’s where Data Science comes in with a solution. It provides a way to make online updates for relevant predictions, visualizations, and analysis for the performance of thousands of factors including equipment, parts, environmental conditions, etc.
As we discussed earlier, data science in mechanical engineering employs techniques from various disciplines like computer science, mathematics, and statistics. Mechanical engineers are very familiar with these topics so it would be pretty easy for them to understand advanced concepts of data science in mechanical engineering.
Applications of Data Science in Mechanical Engineering
The applications of data science in mechanical engineering are as follows:-
- Biomechanical Applications
- Robotic Applications
- Control Engineering Applications
- Solid Mechanics Applications
Advantages of Data Science in Mechanical Engineers
Mechanical engineers may quickly increase their value by mastering data science. This indicates they can ask for a raise or switch to a better-paying job. Every organization’s numerous decision-making processes are built on data. Advantages of data science for mechanical engineers are as follows:
- To gain knowledge and value so that they can demand higher salaries or move to bigger organizations.
- To enhance decision-making skills based on data science results and effectively manage massive datasets.
- To get the knowledge of various programming languages so as to develop scalable and effective solutions.
How does the Transition from Mechanical Engineering to Data Science?
By this time we are pretty sure that you are thinking about transitioning to the data science field. So how do you make this transition? Well, there are certain skill sets that you need to acquire prior to making a big step in your career. Let us discuss them in brief:
Math’s and Statistics
Domain Knowledge is an essential skill for a data scientist. There are three main aspects of domain knowledge:
All of these are the applications of data science in mechanical engineering
Learning data science for mechanical engineers is both challenging and rewarding. In this article, we briefly discussed how data science in mechanical engineering can be useful to mechanical engineers and the applications of data science in the mechanical engineering field. In the upcoming times, individuals with knowledge of mechanical engineering disciplines and the skillsets of a data scientist would be very important. They would be required to fulfill various industry needs.