The evolution of AI and ML as a key driver in manufacturing industry!

There is no denying that now Artificial Intelligence (AI) and Machine Learning (ML) are important for any organization in order to be digitally driven and for utilizing data resources. Moreover, with the emergence of Big Data, AI is now more capable than ever given the creative algorithms of Machine Learning and Deep Learning. Given the increased significance of AI in various industries, demand for AI professionals has grown exponentially throughout the globe. You should definitely read about the AI and machine learning trends to watch out for in 2020.

Every business or organization wants to benefit from data monetization or intend to leverage data and ML is imperative for that. Thus, ambitious engineers can easily take advantage of the situation by upskilling with Machine learning and artificial intelligence courses!

AI and ML are being utilized in almost all the industrial sectors across the globe and even governments and non-profit organizations are embracing sophisticated digital technologies. However, let us consider one industrial sector- Manufacturing, and see how AI and ML have been extremely beneficial.

Use of AI and ML in the manufacturing industry:

  • Accurately predicting when tools or machines are going to fail
    According to research by Capgemini, manufacturing firms like to use AI or ML-based prediction systems to estimate exactly when a machine is going to fail or a system needs up-gradation. This lets the management to schedule maintenance and helps them to increase both the efficiency and lifespan of machines and tools.
    Failure to detect equipment failure can result in unexpected outrages and harm the business a lot. However, with an AI or ML-based prediction cum detection system in place, manufacturing plants can take guard against such outrages! 
  • Inconsistencies and faults can be traced before things go out of hand!
    A manufacturing plant has to be constantly alert so that the products do not have any inconsistency or fault. Otherwise, the entire line will have to be recalled and redone which may result in revenue losses and in some cases even a loss of reputation.
    However, with a ML-based monitoring system in place, such events can be totally avoided without risking human error. A good AI or ML empowered computer system will constantly check for faults and provide real-time feedback. Recently Nokia collaborated with Telia and Intel to develop smart factories based on such systems and have reported huge success. BMW too has such a system in place so that its products do not deviate from their world-class quality standards! 
  • Smarter product designing and quick production of prototypes based on deep insights!
    One of the chief problems the tank designers of world war II from both the allied and axis war industries is the problem of bad design. This costed both sides heavily as often the tanks ran into troubles causing loss of life and equipment. Even today designers of any product can run into trouble if smart decisions are not taken or if all the possible criteria not taken into account.
    However, ML can help develop building systems capable of providing the automatic design with the ability to factor in all design constraints. Such designs can be then rapidly prototyped and put to test. All designers have to do is provide definitions of what the product is to do and other constraints. This results in the rejection of bad designs quickly while at the same time designers can be more creative without worrying about loss of time. Recently General Motors collaborated with Autodesk in order to utilize ML for such intentions!

Challenges in the adaptation of AI and ML

There are complaints that although AI and ML have huge potential and can prove very beneficial yet when it comes to applying the same, many fails to do so, resulting in loss of precise time and revenue.

One reason for that is the companies and start-ups intending to provide AI or ML solutions which are still in the development stage or are essentially prototypes. Business enterprises or any organization intending to adopt AI or ML-based solutions are not exactly looking for prototypes. They instead want finished and proven software platforms which can be quickly put to use and benefits reaped. Most do not want to take part in the development process!

Another reason is a lack of skilled individuals in AI and ML. However, the field offers a very lucrative career and any one joining Machine learning and artificial intelligence courses are assured of great opportunities!

Related posts

5G vs 4G SIM Cards: What’s the Difference and Which One is Right for You?

Emart Spider Admin

Search Engine Optimization for Business

Emart Spider Admin

What Are The Unique Features Of MX Player App?

Emart Spider Admin