Information overload - AI to the rescue?
I recently participated in a terminal automation seminar in London. In my work group there was me and five terminal operators. We discussed the problem of information overload in control rooms at automated terminals - and how to solve it.
One of the terminal operators summarised the current situation: they have so much data coming in from operations that there is a challenge for the operator of processing it all in real-time. To make decisions and their operations more intelligent, they require the needed data in advance of potential bottlenecks occurring. At the same time, the information needs to be relevant, highlighting the key indicators for operators to prioritise.
That way, if the process is intelligent enough, the ripple effect that would create bad or late choices somewhere later in the process is avoided.
We then went on to discuss collectively about what the solution should be. Artificial intelligence (AI) came up as a definite winner.
Terminal automation creates a huge amount of data at any given moment. To manage all data and respond to events that impact operations, AI - or machine learning - can identify the patterns in operations and recommend actions before a problem occurs. In this way, the person in the terminal operator’s control room can see in advance if there are potential bottlenecks or challenges ahead and take preventative steps.
When data is readily available and presented in the right context, it will be possible to make full use of the intelligent supply chain. Part of the solution is to leverage AI/machine learning to deliver information that really matters to control rooms at any given time: reducing information overload from streams of data presented on multiple screens. By adding a layer of intelligence, the operator’s attention can shift towards deciding what action to select to optimise operational performance.
At our table discussion, we estimated that automated operations today are running at about 60 percent of their full potential in terms of efficiency and productivity gains. Adding machine learning and more intelligence around the data, and how it is being delivered to the control room users, offers a way to unleash more of the power of automation.
What are your thoughts?
How do you see AI and machine learning unleashing the potential of creating an intelligent supply chain? Write your thoughts on the comments section below or join the discussion on social media with the hashtag #smarterbettertogether.