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3 Applications & Advantages of Data Science in Mechanical Engineering

Are you a mechanical engineering grad or about to graduate from your discipline? Chances are you might have heard the buzz around emerging trends in the data science field and the rapid growth it has seen. According to reports, data science will see 36% growth in jobs and around 13k+ new jobs will open each year between 2021-31.

Mechanical engineers with strong mathematics and physics skills can set foot into data science and learn data analytics and machine learning tools. Doing so can give you the flexibility to apply and implement data science in various mechanical engineering fields.

In this article, we’ll get to know the numerous applications and advantages of data science in mechanical engineering. But before that, let’s look into what data science is and how it’s useful in mechanical engineering.

What is Data Science?

Data science is a field where businesses extract meaningful information by combining the principles and practices of mathematics, analytics, computer programming, artificial intelligence, and others. This combination of tools, technology, and data science skills helps analyze a large amount of data to uncover valuable insights.

These valuable insights help data scientists to analyze what happened, why it happened, what are the outcomes, and the best course of action. Data science heavily relies on machine learning algorithms of AI to make better and more accurate predictions. The process involves stages such as:

  • Capture: It involves data acquisition, data entry, and reception
  • Maintenance: Data sorting, staging, and storing
  • Process: Data modeling and summarizing
  • Communication: Data reporting and visualization
  • Analysis: Predictive analysis, regression, and qualitative analysis

What is Mechanical Engineering?

Mechanical is an engineering discipline that involves studying concepts of mathematics, physics, and other subjects required for designing and manufacturing mechanical systems.

Mechanical engineers need to get a thorough understanding of mechanics, dynamics, material science, thermodynamics, and others. They extensively study the concepts and acquire their EIT certificate after passing the FE exam and then take the PE to get their license for the practice.

In addition to those core principles, mechanical engineers use tools such as CAD, CAM, and others. They often use such tools to design and build elevators, locomotives, turbines, generators, and other high-end motors.

Is Data Science Useful in Mechanical Engineering?

The Mechanical engineering foundation is over a hundred years old and faces the challenge of a limited set of tools. It requires a touch of the latest technology to foresee the problems before they happen using data science methods. Even though there are great software available today, most of them are complex.

If something goes wrong in a project, it’d be really difficult for engineers to identify what went wrong before it turns into a big disaster and a huge financial loss. However, data science’s predictive analysis could help prevent such disasters.

For instance, a digital twin technology amalgamates AI, VR, AR, and others to help engineers assess how mechanical equipment performs in the real world even before they are manufactured. Just like digital twins, data science has various other use cases and applications in mechanical engineering.

3 Applications of Data Science in Mechanical Engineering

Data science has numerous applications for organizations, but here are some for mechanical engineering:

1. Biomechanical

Biomechanics solve complex medical and health problems using the principles of anatomy, physiology, biology, mathematics, and chemistry. Since biomechanists have to analyze daily human activities, the available data piles up in huge quantities. Thus, different data science methods help study the evolution of anatomical and biological systems over time.

2. Robotics

Robotics has definitely evolved with advancements in data science. By using the machine learning arm of the AI, data scientists were able to resolve initial challenges such as,

  • Predicting every action of robots
  • Reducing the real-time vision complexities

Through ML, data scientists have provided robots with new behavior patterns, for instance, handwriting recognition. As data scientists continue to leverage AI and ML, robots are evolving and becoming smart machines.

3. Data Science in Control System

Control systems are an inseparable part of the modern manufacturing process. The operators in the industry are responsible for 90-180 loops, which constantly move actuators quicker than 90-180 humans could.

However, the control systems rely on actionable data analytics for high-value precision. Thus, for positive actions and outcomes, quality data should be made available for sorting, visualizing, decision-making, and qualitative analysis.

Advantages of Data Science for Mechanical Engineers

Even though data science and mechanical engineering are different from each other, they share a symbiotic relationship and have some overlapping areas. Thus, mechanical engineers with experience and expertise in data science will have a high demand in the market.

That said, here are some advantages of learning data science for mechanical engineers:

  • The primary benefit of data science is it helps mechanical engineers earn potentially higher salaries or move to job roles and bigger organizations
  • It enhances the decision-making skills of mechanical engineers and helps them effectively manage larger datasets
  • You will gain knowledge, expertise, and experience necessary to level up your career and acquire a distinctive skillset. 
  • You will also gain knowledge of various computer programming languages to develop effective and scalable solutions using data science.

Final Words

In this article, we dived deep into how data science is useful for mechanical engineering and learned its various applications for the discipline. Data science is an interdisciplinary field where individuals combine the skills and knowledge of computer science, mathematics, statistics, and others to extract valuable insights.

Mechanical engineering, on the other hand, involves designing and building industrial machinery, equipment, manufacturing plants, HVAC, and others using fundamental principles and computer-aided design and manufacturing software.

Data science offers a promising career path for mechanical engineers, however, learning it is challenging and rewarding at the same time. But one thing we are sure of is that the future generations adorned with data analytics skills would see a high demand to meet various industry needs.

 

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