1) Applications of ML in Mechanical Engineering:
1) Autonomous Cars: machine learning algorithm allow a car to collect data on its surroundings from camera and other sensors, interpret it, and decide what action to take and even allows cars to learn how to perform these tasks as good as (or even better than) humans.
2) If a mechanical device or engineering project can collect lots of data, applying machine learning could find patterns and reveal problems.
3) Designing:
Machine learning can be considered as a tool just similar to ANSYS or Solidworks that you use for designing, simulation and analysis purposes.
Lets take machine design course. The basic idea of it is designing a shaft for a given load conditions. Where as using machine learning algorithms like classification methods are used to find out the likelihood of new shaft being failure one under given load condition. Both theories are emerged by using previous data.
4) Manufacturing:
A lot of work is going on improving the efficiency of various manufacturing processes using data from various sensors (accelerometers, vibration etc). Machine Learning techniques and Deep Learning Techniques are being applied in the field of manufacturing systems to generate process plans etc.
5. The technology offers undreamt-of possibilities for machine and plant construction: Existing business and production processes can be optimized. The machines become intelligent and almost self-sufficient process service providers.
6. Transportation and commuting.
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~😎Application of machine learning in Mechanical Engineering:
Machine Learning offers undreamt-of possibilities for machine and plant construction: Existing business and production processes can be optimized. The machines become intelligent and almost self-sufficient process service providers.
The efficiency, flexibility and quality of the systems can be significantly improved with the help of the available data.
New business models for customers are developed. Machine Learning ensures that software and information technology are increasingly becoming the key drivers of innovation in mechanical engineering.
- 1. Designing:
Machine learning can be considered as a tool just similar to ANSYS or Solidworks that you use for designing, simulation and analysis purposes.
Let’s take machine design course. The basic idea of it is designing a shaft for a given load conditions.
Whereas using machine learning algorithms like classification methods are used to find out the likelihood of new shaft being failure one under given load condition. Both theories are emerged by using previous data.
- 2. Manufacturing:
A lot of work is going on improving the efficiency of various manufacturing processes using data from various sensors (accelerometers, vibration etc). Machine Learning techniques and Deep Learning Techniques are being applied in the field of manufacturing systems to generate process plans etc.
- 3. If a mechanical device or engineering project can collect lots of data, applying machine learning could find patterns and reveal problems that might otherwise show up only after long periods of testing. In the field of Mechanical Engineering, you work with humongous amount of data, in thermal applications, product designing, manufacturing etc.
- 4. Transportation and commuting
- 5. Virtual Personal Assistant
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😎Application of machine learning in Mechanical Engineering:
Machine Learning offers undreamt-of possibilities for machine and plant construction: Existing business and production processes can be optimized. The machines become intelligent and almost self-sufficient process service providers.
The efficiency, flexibility and quality of the systems can be significantly improved with the help of the available data.
New business models for customers are developed. Machine Learning ensures that software and information technology are increasingly becoming the key drivers of innovation in mechanical engineering.
- 1. Designing:
Machine learning can be considered as a tool just similar to ANSYS or Solidworks that you use for designing, simulation and analysis purposes.
Let’s take machine design course. The basic idea of it is designing a shaft for a given load conditions.
Whereas using machine learning algorithms like classification methods are used to find out the likelihood of new shaft being failure one under given load condition. Both theories are emerged by using previous data.
- 2. Manufacturing:
A lot of work is going on improving the efficiency of various manufacturing processes using data from various sensors (accelerometers, vibration etc). Machine Learning techniques and Deep Learning Techniques are being applied in the field of manufacturing systems to generate process plans etc.
- 3. If a mechanical device or engineering project can collect lots of data, applying machine learning could find patterns and reveal problems that might otherwise show up only after long periods of testing. In the field of Mechanical Engineering, you work with humongous amount of data, in thermal applications, product designing, manufacturing etc.
- 4. Transportation and commuting
- 5. Virtual Personal Assistant
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