Spin was invited to a meeting of the Women in Engineering. We would like to…
Artificial Intelligence (AI) is a research and development field that aims to create informatic system that can independently solve complex problems. There are many different types of AI: machine learning, automatic learning, deep learning and reinforced learning. All these systems are all based on algorithms and mathematic models that can analyze a great amount of data, notice patterns and hidden connections. In the next article on AI, we will talk about what is Spin’s solution to use AI technology.
It is of pivotal importance in the engineering field. Our tech team analyzes everyday huge amounts of data, trying to accurately predict future behaviors electrical motors and devices. AI has been around for a long time: it was considered a developing field in 1956, it started to be used in industrial processes in 1981 and then deep learning starting from 2012. Deep learning brought a revolution to AI applications, that with artificial neuronal algorithms could make huge steps forward in images, translation and data analysis. In 2018 AI was used in CAD, helping engineers to optimize complex design solutions.
AI in engineering can be used in:
- automize the process, with faster design
- optimize processes, cutting costs and increasing efficiency
- predictive maintenance
- process complex simulation and modelling with precise outputs in a fast way
- find connections between models and data, uncovering the hidden ones
- assisting the design, coming up with optimized solutions within certain boundaries
AI in automotive
One of the engineering field in which AI would be great to use is the automotive field.
AI has been used in the automotive field for quite a while, because much of the technology installed is based on AI, gathering data with the goal of optimizing driving experience and safety. Studies are being conducted mostly on improving systems to reduce driving mistakes, using AI to recognize and analyze different driving behaviors.
AI in automotive does not necessarily mean ‘autonomous driving’ but more an improvement in driving style. AI is quickly improving the automotive field.
“Data has value in how we use it, not the quantity”
A list of Altair Software connected to AI:
- hyperstudy allows to optimize results, creating DOE (Design of Experiment), predictive
- monarch is a powerful tool to manage data, statistical analysis and Big Data management
- Rapid Minder can also figure out anomalies in the metadata analysis
- romAi constructs and trains a neural network, has a integrated library in Activate and Pulse
Altair has many opportunities for AI in its software suite. It is time to identify the company’s needs and analyze the processes that can be automated and simplified. AI can help to quickly solve those issues, improving trial and error.