Tideworks, a US-based terminal operating system (TOS) developer and provider, has found that terminal businesses are lagging behind in using AI. That is despite AI’s potential for improving key aspects of their operations, and ultimately, profit margins. How do we get them on board?
The use of AI to optimise terminal yards and planning can lead to a considerable reduction in rehandles and travel distance of equipment. It lowers, among other things, maintenance, fuel and human resources costs. In that way, it has the potential to grow profit margins by quite a bit.
However, not everyone is on board with using AI yet. “Although 73% of larger terminal networks identified AI and automation as essential for future competitiveness, only 36% reported actually using AI to collect and analyse operational data”, Tideworks found in an industry survey.
In other words, only half of those who recognise AI’s importance actually use it in practice. RailFreight.com sat down with Chad Van Derrick, Tideworks’ vice president of software product management, at TOC Europe to discuss how to get terminal operators on board.
The Tideworks booth at TOC Europe. Image: © Tideworks
“People badly understand AI”
A big part of the problem, explains Van Derrick, is a lack of a clear expected outcome. “People badly understand what AI is, it’s a buzzword”, he adds. “They don’t have an outcome in mind, but implementing AI needs to be centred on the outcome we want to achieve.” At the same time, new users may not always have a clear idea of what is needed from them to get the most out of the technology.
It all starts with the data that goes into the system. It needs to be high quality. “An easy place to start is the inventory”, says Van Derrick. “The system needs to reflect what’s on the ground. If that is not accurate, you’re at a loss.” Terminals need people to govern the quality of the data: standardised, normalised and cleansed.
For example, a container has a life cycle and will be in different places, like a train, in the terminal, on the road, coming into the gate, or moving around the yard. Information about the status of the container might be in different systems at different times. Those systems sometimes do not talk to one another, so you need a system to bring the data into one place. “That may not always be an easy task, depending on the maturity of the terminal and the people involved.”
Data visibility and feedback
Then we reach step two: getting visibility into the data. With dashboard, KPIs and reports, you can use your data to inform decision-making. “You’d be surprised how few use it, and if they do, they might use it for a month and then move on to new reports”, says Van Derrick. The key here is consistent, daily use.
“Ideally, you want it as near real-time as you can get. How long are trucks waiting? What is the turn time? How long are we waiting for containers? You want those insights to begin to understand what data is important and the quality of it.”
Terminal operations. Image: © Tideworks
Once a sense of trust in the machine has been established, we proceed to step three: feeding the machine with data. “It then learns, which will give you a functioning predictive machine with confidence”, says Van Derrick.
It could then tell you ahead of time, for example, expected container dwell times in terminals. “Then you may know that there is a 90% chance that it may be picked up after three days, allowing for you to place it in a strategic location.”
Trust the system
Understanding the basic functionality of AI in terminals is key to getting businesses on board with it. But in addition, says Van Derrick, people need to trust it. “It is important to provide for a feedback system. If an AI-suggested decision did not work out, you need to let it know.”
Without such feedback, AI could even create safety issues. “It really wants to give real-time instructions, which can lead to dangerous situations”, continues Van Derrick. “For example, it could tell a truck driver to suddenly change course, and then the driver runs into another truck. The AI needs training to understand these sorts of things.”
