AI IN MECHANICAL ENGINEERING

 

AI  in mechanical engineering

AI IN MECHANICAL ENGINEERING
        Hello guys. You will be really amazed after reading this article that gives some curious information to the mechanical engineers. Imagine that you can design and manufacture the products with your AI friend, they will give suggestions on how to improve the CAD on generative design projects, software simulation and give quick methods to manufacture the products. You may think it is possible only in the future. But the future is now. The future is AI in the Mechanical Engineering domain.

                                                   https://builtin.com/artificial-intelligence 

      Artificial intelligence technology plays an important life in people's lives, such as self-driving cars, autonomous drones, lifters even smart dishwashers, smart sweepers, which can be developed by interfusion of artificial intelligence and the mechanical manufacturing industry. In the 4.0 industrial revolution, the mechanical domain also needs to rely on AI technology to achieve automation and intelligent developments.

AI IN MECHANICAL ENGINEERING

ABOUT ARTIFICIAL INTELLIGENCE TECHNOLOGY:

      Artificial intelligence technology is the advanced technology in the computer engineering domain. It is the representative technology that learns the importance of intelligence, mimics human intelligence, and produces similar intelligence artificially by simulating and expanding human intelligence. Artificial intelligence systems are powered by machine learning and deep learning.

i) MACHINE LEARNING:

AI IN MECHANICAL ENGINEERING


Machine learning is a form of AI that imitates the way humans learn by a set of data and algorithms without explicit programs. it means the machine learns itself by experience with data and becomes more accurate at predicting outcomes. The categories of machine learning are 

  • Supervised data(Labeled data)
  • Unsupervised data (Unlabeled data)

ii) DEEP LEARNING:

Deep learning is a type of machine learning that learns by itself from the inputs through biologically-inspired neural network architecture. This network contains many hidden layers of data which makes the machines learn deeply and gives efficient outputs for the input problems like human intelligence.

AI IN MECHANICAL ENGINEERING:

AI IN MECHANICAL ENGINEERING
Source: XenonStack

CATEGORIES OF AI:

     AI is generally classified into two categories:

  • Narrow AI
  • Artificial General Intelligence(AGI)


    i) Narrow AI:

  •  Narrow AI is also called Weak AI, 
  •  It can do a single or limited task correctly.

   ii) Artificial General Intelligence:

  • Artificial General Intelligence is sometimes referred to as Strong AI.
  • It can perform many tasks perfectly at the same time.

AI in the CAD design:

  • AI used in Computer-Aided Design generally works on the principle of knowledge-based systems(KBS).
  • Knowledge-based systems (KBS) are computer programs that utilize artificial intelligence (AI) to solve complex problems and can capture the knowledge of humans for taking perfect decisions.
  • Design rules and problems in CAD are stored which later assist CAD designers.
  • The combination of AI and CAD is done through Model-Based Reasoning (MBR).
  • A model-based reasoning system is based on a model of the structure and behavior of the device that the system is designed to stimulate.
  • The major field for the application of AI in mechanical engineering is Generative Design. 
  • The generative design gives standard outputs for the given inputs.
  Example:

  1. Autodesk launched a project named Dreamcatcher which provides the feature of generative design. 
  2. SolidWorks gives a feature of topology optimization in its 2018 version by using a different algorithm based on generative design.

AI in the manufacturing industry:

AI IN MECHANICAL EGINEERING


      Mechanical engineers with AI skills would be needed to figure on a software package that may handle knowledge provided by sensors in elements of a powerhouse, production facility, or client merchandise. One example of information science is used in powerhouse optimization. knowledge collected from superordinate management And knowledge Acquisition (SCADA) will facilitate predict failures, avoiding any loss of cash or life.

      A US-based company Sparks cognition is providing solutions to power firms that sight anomalies in plant knowledge and predict any failure enough time ahead, avoiding period and loss of revenue.  AI is making strides in self-driving cars furthermore as industrial AI.

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