Application of AI, ML in Core Engineering

Session by Mr. Makarand APTE as part of Webinar Series “To Guide Engineering Students to select meaningful projects”

Watch the session

“Calculators did not replace mathematicians … and AI will not replace humans!”

What it also means:

“The Future Jobs / Career Opportunities are in fact Bright.

Future jobs will be more Meaningful, more Intellectually Stimulating and more Humane.”

Now a days whenever we login to any website or call-in to any support desk, we get popup message or interactive voice message from other side about what we are looking for and they help us to browse further or resolve our issues. I always feel like someone is there at other end to help us, after exploring more about it, we come to know that this is facilitated because of power of ARTIFICIAL INTELLIGENCE, which is becoming more intelligent, more realistic day by day by using its own data. That is how we connect with our today’s subject in our daily life. 

Today we have very interesting person Mr. Makarand APTE with us who has around 22 years of experience in CAD Software Research and Development. Last 3 years Mr. Makarand APTE is working on research related to Artificial Intelligence in 3D Design and making SolidWorks more intelligent with human like design thinking. He has also organized and managed many Innovation initiatives within organization. 

It was interesting session where he narrated different examples of application of Artificial Intelligence (AI) and Machine Learning (ML), which really enticed us to know more about it. He gradually navigated us through basic understanding about AI and ML, technologies behind it, and prominent areas in AI and ML and its adoption in Core Engineering fields. 

Around 50 years back, mimicking human activity by machine was considered as Artificial Intelligence.
In last 20 years, AI enhanced and now demonstrates different behaviors associated with human intelligence such as learning, reasoning, problem solving, knowledge representation, perception, motion, and manipulation. Mostly AI systems are now data driven and these systems learn from data at its own. 

With the development in AI and ML, it is now adopted to increase productivity in engineering design. For example in generative shape design, one of the shoe company uses buyers’ foot map to create personalized Shoe Sole. Similarly chair designed by Patrick Jouin, which is very lightweight and very complex design which human mind cannot even think to design. With AI such designs are possible by defining certain constraints and basic shape.  It improves productivity and reduces cost of manufacturing. 

Chair created by artificial intelligence > La Fondation Dassault Systèmes

AI is now encompasses and connects many technologies like Internet, Mobile, Cloud, Internet of Things, BigData, GPU and Edge Computing.  All these technologies played different roles to collect data, access data, process the data, analyze the data, and compute complex equations. 

Makarand illustrated application and use of AI and ML in revolutionizing Predictive maintenance. Using all these technologies, AI driven systems are adopted by many industries for predictive maintenance for their plants. Such systems use and deploy many different sensors such as temperature, humidity, pressure, sound, vibration, proximity and even cameras to collect data. Using IoT, collected data is stored on Cloud. Using BigData, user can analyze and process that data. Using all this data and with appropriate logic, machine can send preventive alarm to operator. It helps to predict machine downtime even before it happens. This way AI helps plants in predictive maintenance. 

To understand opportunities in AI, we have to understand what are those prominent areas in AI and ML which we should explore more to utilize and resolve different real world problems. 

Major areas are –

  • Computer Vision – It consists of many things such as face recognition, object identification, scene resolution, image mapping and many more
  • NLP (Natural language Processing) – Translator, Chat-bots, Information retrieval, Sentiment analysis and many such applications.
  • Speech – e.g. Voice command, speech to text, text to speech, virtual assistant  
  • Analytics –Coupled with some allied things such as IoT, Optimization

If students explore technologies and advancement, in above areas, it will help the students to identify solutions for different real world issues in AI and ML. AI is mainly smart use of all such technologies and logic to achieve our goal. It needs large amount of data sets, which helps the AI system to identify pattern, or some similarity based on which logic is developed and actions defined. 

AI and ML has many usages in Industry, day-t—day life. For example in Agricultural domain, it is used for Field Monitoring, Food Quality analysis, Agri Robots for pesticides or Weed killing, even for crop assessment. Agricultural technology has lot of scope to implement AI and ML to reduce efforts and increase yields. 

Before you move in to take up such AI based projects, Mr. Makarand would like to suggest some guidelines to follow. You have to collaborate and work with many disciplines for implementing any AI solution. As a word of caution, Mr. Makarand suggests that for any AI project you should be ready to do much of dirty work or laborious work, as it needs lots of data processing. 

To conclude the session Makarand Apte advised the students that students should first think about problem about the problem to be solved and then identify appropriate technology. They should not first decide which technology they want to use and for it search the problem statement.