Chad Van Derrick*, Vice President, Product Management, Tideworks Technology, highlights the opportunities presented by the adoption of AI in TOS and charts a practical path to its implementation.
The opportunity to harness Artificial Intelligence (AI) in Terminal Operating Systems (TOS) represents a significant advancement in optimising terminal operations. This innovation promises to boost operational efficiency by automating manual tasks and utilising predictive models to anticipate future needs. From minimising yard congestion to anticipating equipment maintenance and monitoring environmental conditions for worker safety and cargo integrity, the potential applications are vast.
AI isn’t as novel as some might believe. In the data community, we’ve been developing algorithms, crafting data models, and delving into predictive analytics for quite some time. AI seeks to leverage those technologies and apply automation, reducing human involvement where possible. With tools like ChatGPT and Microsoft Co-Pilot, data is swiftly collected and analysed. Consequently, when one prompts the model with a question, words are automatically woven together in a predicted manner to form a response.
Likewise, the fundamentals of this same technology can be implemented within terminals. For example, container data can be quickly gathered and updated, then compared to analogous historical data to forecast the future movement of a container. Leveraging this prediction, AI can automate the necessary equipment tasks. This can help reduce operational costs while increasing terminal safety.
LAYING THE FOUNDATIONS FOR AI
As TOS is integral to a terminal’s technology ecosystem, certain components are essential before pursuing AI integration. Three key capabilities emerge as essential pillars as terminals seek to optimize their operations: data governance; digital twins, and simulation. These elements collectively contribute to enhancing efficiency, ensuring safety, and driving innovation within terminal environments.
Data governance is an essential yet often overlooked area in terminal management and a prerequisite for AI to ensure that the data used for optimising operations is accurate, reliable, and compliant with regulations. Without proper governance, terminals risk using flawed or biased data, leading to inefficiencies and potential safety hazards. Data governance establishes rules, policies, and procedures for data management, including data quality control, access control, and data privacy protection. Implementing robust data governance practices can help terminals maintain trust in their AI systems, mitigate risks, and ensure that AI-driven insights drive positive outcomes.
Further, software that provides visualisation and management of equipment through digital twins offers significant value in terminal management by creating virtual replicas of terminal infrastructure and operations. These digital twins leverage real-time data from sensors, IoT devices, and other sources to mirror the behaviour and performance of terminal assets and processes. This allows terminals to monitor and analyse operations in real time, predict maintenance needs, and optimise resource utilisation. By integrating AI with digital twin technology, terminals can unlock insights, improve decision-making, and drive innovation to enhance overall terminal efficiency and performance.
Lastly, simulation software plays a crucial role in terminal management by allowing operators to test and validate AI models in a virtual environment before deploying them in real-world scenarios. Simulations enable terminals to explore various operational scenarios, optimise resource allocation, and assess the impact of changes without disrupting actual operations. This capability is particularly valuable in complex terminal environments where safety, efficiency, and reliability are paramount. By simulating different scenarios, terminals can enhance decision-making, improve productivity, and reduce downtime. Additionally, simulation facilitates continuous learning and refinement of AI models, leading to better performance in real-world terminal operations.
IMPLEMENTING AI IN TOS
As AI becomes more commonly integrated into TOS solutions, it’s redefining terminal operations—making them more proactive and predictive. Though it may be tempting to rush into AI integration with TOS, given its many advantages, the decision must be thought through carefully.
To initiate improvements with AI, pinpoint areas with significant inefficiencies or where measurable business value can be realised with low risk and high staff adoption probability. Avoid trying to tackle multiple problems simultaneously or searching for a single solution for optimisation. Instead, start by addressing a small, easily definable problem that can be measured. Gradually expand upon this success one piece at a time, and you’ll soon see substantial optimisation and improved business outcomes.
EVALUATING AI INTEGRATION
Implementing AI within TOS is not just about adopting new technology in pursuit of hopeful gains — it’s about implementing the right optimisation tool for the right problem.
It’s also crucial to evaluate the existing technology stack. AI should not be an isolated addition but rather a complementary resource that expands or supports current systems. Understanding how AI will integrate with current tools is key to maintaining sound data privacy and security while ensuring a seamless user experience.
When shopping for an AI tool, thorough market research is vital. Beware of “black box” solutions that fail to disclose how they operate. There is no special sauce here; users must understand the technology to trust and adopt it. Operators should evaluate available AI solutions that address the specific problem at the terminal, weighing their capabilities against the terminal’s specific requirements and long-term strategic goals.
SAFE AND EFFECTIVE INTEGRATION
As terminals integrate AI into their TOS, a measured adoption is the best way to navigate AI integration effectively. Gradual incorporation allows for the refinement of secure and safe practices and a smoother transition, minimising disruptions that could arise from a rapid, broad implementation approach.
To effectively leverage the transformative potential of AI, operators must also navigate the complexities of user interaction. The human element remains vital to terminal operations ensuring that the new tools enhance, rather than complicate processes, and ensure that safety remains paramount. Developing usage guidelines and providing thorough staff training cannot be underestimated. Supporting adoption and employee proficiency with AI tools can maximise their benefits.
It’s also helpful to remember that AI serves as an enhancement, not a replacement, for human oversight. AI assists in decision-making and can perform complex, detail-oriented tasks, but it is not the “magic bullet” solution and requires the guidance and understanding that only people can provide. Maintaining this balance is essential for achieving the full potential of AI in TOS and avoiding costly mistakes.
ADVANTAGES
Embracing AI transforms TOS into more agile, forward-looking systems, aligning terminals with the evolving demands of the global marketplace. By integrating AI, terminals can enhance operational efficiency, predict demand fluctuations, reduce costs through automation, improve customer service, and enable data-driven decision-making.
An example of how AI enhances operations is by predicting a container’s dwell time. This helps the terminal reduce container set-asides. Machine Learning aids terminal planning by accurately predicting dwell time, providing terminal operators with reliable insights into the optimal decking location and surface considerations before executing a move.
FUTURE PROSPECTS OF AI IN TOS
For terminals to evolve to meet today’s demands, they must strive for continuous, responsible innovation. The integration of AI within TOS solutions marks a pivotal moment in terminal operations, with the potential to redefine the global supply chain. Using AI-driven tools makes operations more streamlined, interconnected, and automated. These advancements promise to enhance the current logistics landscape and drive the industry toward a more efficient future.
As AI technology becomes more sophisticated, it’s likely to lead to additional breakthroughs that were previously out of reach, setting a new benchmark for what is possible as the supply chain industry aims to become more efficient. However, the successful adoption of AI in terminals depends on a thoughtful, strategic approach that accounts for the unique needs of each facility. AI in TOS will continue to grow and impact the way terminals operate, driving the path for further technological innovation for the supply chain industry.
Chad joined Tideworks Technology with over 20 years of experience delivering innovative large-scale products and services to market across a range of industries.
Heading Tideworks’ Product Management organisation, Chad is responsible for injecting innovation, continuous improvement, and increased stability across Tideworks’ product suite.
