This is not a new concept to the process industry, with some MES vendors offering real time optimization modules as well. However, it still comes down to the decision making process of whether of not there is a need to optimize.
Using AI and Machine Learning could open completely new doors in the way you run your plant. This is due to its predictive operational controls and real time optimization technology which reduce quality and safety issues, as well as energy and raw material consumption; thereby improving the operational uptime of your equipment.
This brings me to my third example where industry 4.0 can make a big difference, which is predictive maintenance. Similar to predictive plant control, real time data is used to predict when equipment will fail. So instead of performing maintenance on a more or less arbitrary schedule, you do it when it is necessary. This also increases the likelihood of spotting equipment failure in time which will allow for proper preparation.
Industry 4.0 use Virtual reality / mobile devices to guide and assist technicians as they rely on AI, machine learning and data science. They are very powerful and if correctly deployed will fundamentally transform how the process industry will operate.
That said, there are no immediate “out-of-the-box wonder pills”. Data models need time to train before they can actually be used. They also require constant improvement and adjustment to stay relevant. This means that Industry 4.0 is not a standard project whereby you just select a solution, deploy it and then go into maintenance mode. On the contrary, the nature of Industry 4.0 dictates that you never go into a standard maintenance mode, but remain in a deployment mode.
Additionally, Industry 4.0 is not something to be used to reduce workforce; instead for it to be really effective you will need to increase your head count by hiring new and more highly specialized personnel to keep your Industry 4.0 initiative alive and well.
Therefore Industry 4.0 holds the same significance and challenges for the process industry as it does for industries like automotive or machinery.