Artificial Intelligence (AI) and Machine Learning (ML) are concepts that are nothing new to the tech sector. ML has been a reality for a bit longer than AI, but they effectively come from the same place. Both concepts lend themselves very well to software systems that are still new to many manufacturing sectors. More and more assembly lines and logistical networks are being upgraded or replaced with systems that feature industrial AI software.
AI software platforms can optimize any assembly line, manufacturing space, or logistics operation by putting data to work. Thanks to the availability of vast seas of data that are only getting bigger by the day, AI and auto ML software platforms are getting faster and smarter. While these platforms have been around for a while, the impact they are having on industrial manufacturing is just starting to be felt. The torrents of data we are creating are giving these platforms more to work with than ever before.
Who is benefiting from industrial AI software?
The short answer is everyone. Industries as diverse as food manufacturing and packaging to mining are being made more efficient by implementing AI or ML software. A common misconception is that software solutions don’t have a place in heavy industry. People may associate terms like AI and data with computer programmers and cloud computing. The reality is the innovations in AI and ML platforms can help heavy industrial sectors the most.
Mining, agriculture, and heavy manufacturing are all vulnerable to supply chain issues and other factors of modern life. These industries need to operate more efficiently and be more agile than ever before to mitigate these issues. Efficiency and agility are two of the advantages of AI software programs. Here are the specific areas where an auto ML software platform can improve efficiency:
· AI or ML software can help monitor machines in any heavy industry and can even predict when they may break down. This is crucial in an industry like mining. Mining involves the use of complex machines that are integral in each process. AI-driven software can be used to monitor each machine. After a little bit of time, in some instances after just a few hours of collecting data, the software systems will be able to devise maintenance schedules and even predict mechanical breakdowns.
· While monitoring machines, the software platforms can help to determine which settings are optimal. This helps keep operations running smoothly and increases the overall efficiency of the processes. In an industry such as mining, this aspect is even more important since many of the materials extracted from mines are non-renewable resources. Optimizing efficiency and eliminating waste in a mine, or in any situation with non-renewable resources, is crucial for reducing the footprint of that industry.
AI and ML platforms can monitor energy consumption. They can even keep tabs on which machines use the most fuel and offer solutions on how to increase their fuel efficiency. Collecting data on the fly, in conjunction with existing data, can have a real time impact on energy conservation.
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