In the article What is Smart Manufacturing? the author delves into what exactly smart manufacturing is, as defined by the new technology that has allowed it to come into being. Smart manufacturing has enabled us to use continuously collected and flowing data to continuously improve processes thus taking some the human error element out of manufacturing. It’s not to say that the smartest piece in the manufacturing puzzle isn’t still a human because it most certainly is. It is more a realization that machines can now collect and interpret data themselves (as we have programmed them) so that they almost “think” on their own.
The author points out that some believe we are now in the 4th industrial revolution. This industrial revolution involves big data, predictive analytics, and the artificial intelligence created using these concepts. In essence, the data tells us what to do. Instead of a maintenance cycle that works based on past failures, think of a maintenance cycle that continuously collects data thus giving us indicators before a failure. Furthermore, the data can let us know what failed as well which increases efficiency. This connection is known as the IIoT – the Industrial Internet of Things. The emergence of cheap connected devices, coupled with the availability and affordability of mass computing power, has been the biggest driver of Smart Manufacturing.
Visibility is a big driver in understanding ROI in smart manufacturing. The processes can alert users via messages on their phones; displays on a monitor, or a number of other ways. Communication between machine and humans becomes simple. When the data tells you what to do, decisions normally become easier thus reducing human error, increasing efficiencies in manufacturing processes, and finally saving money.
Will smart manufacturing eventually become so good that actual human jobs are lost?
What safeguards are in place so we know that sensors on manufacturing processes are not relaying operators the wrong data?
As I mentioned in a previous blog, do you believe there is a downside to collecting too much data?