As our world has become more reliant on technology, we have just begun to change certain practices. The way we manufacture is one example of this. Artificial intelligence and machine learning have begun to be implemented in the workplace in several ways, and have a positive outlook on the future.

The workplace is one area that artificial intelligence has started to improve. New technology can identify employees and monitor their interactions. Accidents can also be stopped before they happen with machine learning. Keeping equipment operational is another way AI can prove useful. Maintenance managers can use it to identify potential failures and prevent them, allowing for more productivity. These are just a few ways new artificial intelligence has the potential to completely change how we make things. I believe that advancements in this technology will allow for safer, more productive work spaces in the future.   

To understand this in more detail, I talked to Manny Singh, principal cloud architect at Amazon Web Services. According to him, “They do not fully understand what AI is.” He then told me about two ways artificial intelligence can benefit the way we make products: predictive maintenance and computer vision. Predictive maintenance uses the Internet of Things to collect data from the assembly line in the facility to allow artificial intelligence to identify issues in the air quality, temperature, vibration, etc, of the equipment. This way, any potential errors in the process are predicted and resolved before they can take place and waste valuable time and resources. Computer vision uses cameras that oversee the manufacturing process in real time to identify any mistakes as soon as they occur. The computer uses artificial intelligence to compare what it sees with past products. Once the error is found, data is sent back to the machine, and the process can be stopped to replace the part before it creates the same flaw in more products. 

AI is only being leveraged by less than ten percent of organizations today, but the solutions used by manufacturers today are readily available and have the potential to change the process all together.