The hyperdynamic COVID-19 has caused tumultuous events to unfold, cornering businesses and operations into unfamiliar grounds. For a long time, the industries involved with the supply chain and logistics have adhered to traditional methods, which has proved to be detrimental as it can no longer sufficiently respond to the downturn of economic health. The operational flow will continue to suffer a dear amount if authorities fail to emerge from complacency and accept some technological innovations like AI. Therefore, the implementation of a consistent and ubiquitous framework is necessary to deliver best-practice measures to protect the livelihood, wellbeing, and safety to both individuals and businesses.

Achieving a consistent industry-wide solution requires diligence and patience. Technology is continually evolving, and although it may impose significant changes, it is a sustainable approach offering long-term benefits that provide reliability and stability in unprecedented events. However, to ensure the best performance derives from an AI application:

1. TOS must operate on a true real-time architecture that enables both shared memory and in-memory processing.

2. TOS can move operations in the cloud to achieve maximum flexibility, as well as implement optimization and automation tools to strengthen AI capabilities.

3. TOS must operate in a single server infrastructure for consistent and instantaneous data flow.

Although tactical planning consists of smaller short-term steps to reduce immediate impacts, you cannot remedy a problem of global magnitude with a temporary solution. Therefore, it is crucial to practice precaution and evaluate product specifications against your criteria before implementation. More substantial due care must be employed to keep an open mind and leverage optimal levels of such an incredible innovation. Technology advancements no longer connote a downturn of investments or revenues, but rather, has risen as a catalytic force that fights economic contractions.

Artificial Intelligence (AI), at its full potential, can help solve the world’s most significant challenges. Its promises to synthesize, analyze, detect patterns, develop insights, and determine predictions across various dimensions, beyond human capacity is what truly makes us marvel at its constructs. The idea that AI can apply across all industries ranging from health to supply chain further endorses its rising endearment. However, before the world can progress from machine learning into deep learning, it will only prove useful if the foundation already embeds the core blocks required in its current infrastructures and system architectures.

Why is AI relevant to the maritime and container industry?

Nations worldwide have now entered a low-growth economic reality, and the impacts of the worldwide pandemic that were not immediately obvious are now gradually coming to light. While some shipping liners and ports have projected a positive Q1, the epidemic has declared a pandemic in March. Consequently, reports generated for January to March are not accurate indicators, and we are likely to foresee a stark change in results for Q2.

Global trade relationships have had to readjust and implement new reforms to respond to the dwindling supply as crucial players of the supply chain have had to disconnect since the financial burden is too much to bear. Blank sailings, low cargo volumes, and a stark drop in consumer demand are a few of the many impacts ensued from the pandemic. Port authorities overwhelmed at the limited resources on-hand and forced to navigate through such unprecedented events have called for an imminent introduction of technologies like AI.

How can AI help achieve goals and visions?

AI may well be our savior, guiding us to answers we have been struggling to construe. Gathering data is an easy task; it is making sense of the masses of data that proves to be a challenge. Now that the world is adopting a more liberal approach towards technology, AI is gradually gaining traction and will soon deploy more intelligent integrated tools that combat problematic areas within operations. The availability in computational power doubling every three and a half months allows software providers to expand on AI applications and close the gap to achieving deep learning.

Port and terminal operators can heighten operational visibility by introducing predictive analytics. It is a subset of AI that resonates with machine learning and contributes significant value to TOS operators by determining the possible scenarios when dealing with bottlenecks and supposes the best alternative while factoring in specified parameters. Processing the data, then learning, and devising predictions at a magnitude and detail level impossible for an individual human to comprehend, inherently achieves optimization in operations, processes, and resources – something all ports and terminals desperately need in this time of uncertainty.

AI capacity broadens from its ability to draw on a substantial database of scenarios instantly, develop responses to questions, and devise a decision or device that can challenge a way that a human cannot. Its ability to naturally learn from previous answers, and continually improve its learning approach to meet requirements, further reinforces the power of AI. If this is the beginning of AI, imagine the possibilities as it progresses…

TIC 4.0 was founded in 2019 and brings together leading terminal operators, equipment manufacturers and solutions providers to promote, define and adopt standards. Now, the initiative has been formally registered during a ceremony in Brussels, Belgium.

In a statement, TIC 4.0 said Boris Wenzel, Managing Director, Terminal Link, would be its president and Norbert Klettner, Managing Director, RBS-EMEA, its vice-president.

Frank Kho, who has numerous experience with terminal operators and equipment manufacturers, will become CEO. The current 20 members of TIC are a good mix of terminal operators and suppliers in the industry, who are Hyster-Yale, Kalmar, KoneCranes, Kuenz, Liebherr, NAVIS, Phoenix Lighting, RBS, SICK, TBA, TMEIC, ZPMC, APMT, Bollore, Eurogate, Port of Koper, PSA, Terminal Link, MMC Ports and Yilport, several other organizations have expressed their interest to join this unique initiative.

The goal of TIC 4.0 is to promote, define and adopt standards that will enable the cargo-handling industry to embrace the 4th Industrial Revolution. Therefore TIC 4.0 will also strive to attract more members from the terminals operators as well as industry suppliers.

Its initial objectives are as follows:

• Define and agree on a common semantics and definitions among the companies involved in the cargo handling industry, both terminal operators and port solution providers.

• Develop communication protocols and frameworks that will be adopted by the port industry players for seamless data communication regardless of the manufacturer or type of equipment/machine.

• Facilitate the inter-operability of different information sub-systems of a cargo handling facility.

• Promote the adoption of selected existing standards and those developed by TIC 4.0 by the sector.

“I really feel that both energy and commitment prevail among TIC 4.0 members to achieve the goals we have set. I believe that to achieve these goals, the cooperation between terminal operators and solution providers is a great critical success factor,” said Frank Kho.

“TIC 4.0 members all believe that the work on standardization is of utmost importance for our industry in the context of increased digitalization of the supply chain. It will also enable the adoption of innovative processes and solutions” added Boris Wenzel.

Click here to visit RBS EMEA.

Terminals have the dual duty to assess their overall business operations to depict any flaws and evaluate the best fit terminal operating system that can combat these hotspots. The era of terminals taking a crucial point in the global supply chain is fast approaching, and terminal operators may be facing circumstances that are outside their expertise and capabilities. Autonomous operations abreast the help of artificial intelligence in computing masses of data to determine reliable decisions will come to fruition by all industry experts.

A thriving terminal is reflective of terminal operations which are responsive in the scalability of container throughput while maximizing the use of their existing resources. Therefore, terminal operating systems incorporating true AI capabilities become the intrinsic option when decision-making is very time-consuming and are liable to errors. Turnkey software like TOPX Expert has cultivated the essence of AI which overturns these implications. TOPX Expert leverages greater control for terminal operators since the AI instituted automatically learns from the substantial pool of data and creates algorithms to which the knowledge is applied, and different scenarios are deduced for selection. These scenarios have been determined with the consideration of set parameters to achieve the optimum position, time, and departure for a vessel to berth. Early detections of bottlenecks are also another benefit derived from TOPX Expert as it facilitates forecasting any upcoming constraints, driving greater visibility over operations to make faster decisions. The lead up to the completion of berth planning and scheduling is a complex process that is almost impossible for the human to calculate free from errors, requiring automation and artificial intelligence to cease errors before they even appear. Not only does this indicate AI in berth optimization is necessary but requires real-time data to make accurate decisions which benefit the overall terminal.

AI is introduced to assist in complicated tasks that typically fail to address all set factors optimally, and as a result, inhibits resource-, process-, and operations optimization. All this is only made possible due to the real-time and in-memory architecture allowing for the centralization of data. An environment that provides a centralized space for information flow allows all users, independent of the type of operation, to work on data that is always maintained in its most updated state. This is exceptionally important for berth optimization since all these data fuels AI in inferring the most viable decision without sacrificing efficiency in any area. Another benefit of AI conceived on a real-time architecture is that it enables process agility, allowing operators to make changes to previous tasks without compromising the current operation or the overall process. Challenging the conventional TOS, TOPX Expert is built on a robust architecture that makes automatic changes in real-time, despite when it was made within the process timeline. Outcomes such as the elimination of congestion before and after is rendered as the fore benefit of AI in berth optimization. Therefore, decisions are always achieved with precision in TOPX Expert and remain fully functional even when exposed to drastic changes in data.

All in all, terminal operators have the responsibility to take control and define the most ideal solution that captures the entire spectrum of terminal operations which streamlines processes and delivers efficiency. Common deciding factors when searching for the right TOS derives from short-term goals which have precluded revolutionary technology offered in a quality TOS. Consequently, terminal operators miss the opportunity of meeting better capabilities which drive higher efficiency. Every functionality should always be evaluated and proved against its acclaimed level of AI inherent in the technology to understand what the TOS is truly capable of. Don’t just limit your vision to the present, look ahead, and invest for a future. Click here to find out more factors to look for when researching into AI in a TOS.

What does AI mean for Terminals?

In this current era, existing processes and available resources which cannot efficiently or immediately meet operational demands, has become the incentive for terminal operating systems to expand their field into alternative technologies. As a result, AI has become quite the common buzz word, sparking opportunities for the Container Handling Industry to venture for strategies which enhance operational flow and decision-making. However, AI is still in its early stages due to its complexity requiring immense efforts and strong expertise in the area to develop a quality product manifesting its true capabilities. Subsequently, little to no terminal operating systems integrating capable and skillful AI into their systems are available on the market.

Is it really AI in your TOS?

Terminal operating systems are the heart of every terminal powering operations right from planning down to execution. However, when AI is integrated into a TOS, it must be unwavering of the centralized server architecture. Before we continue to expand on this, it is crucial to understand the constructs of AI which follows a process that collects pools of data, then learns from it, makes algorithms, and applies this knowledge to make independent decisions automatically. As a result, Big Data is not only an integral component of the initial stages of AI learning, but having accurate and reliable data is also another necessity.

Your conventional TOS requires multiple servers to load information, which not only instigates longer wait times but inherently pulls fragmented data. Data becomes redundant when flowing through a TOS with a decentralized architecture that cannot support real-time control and planning. A non-true real-time environment instills inefficiencies within operations and management, mainly when changes made to data has already been processed onto the next step. Static control processes respond ineffectively to changes since the information which is now deemed redundant will continue to be worked on until the new modified data is retrieved from the previous workstation operator. Changes made from the previous process may not inflict such drastic impact upon the current planning task, but what if alterations need to be made from five steps prior?

Consequently, if data is not in its most updated state, poor decision-making from AI is a strong likelihood, inducing inefficiencies in terminal operations. The omission of core AI components will directly tamper the execution process such that CHEs will misplace containers in the yard or move containers in a yard bay that is no longer available, incurring additional moves and time for it to be placed in its correct location. These events will snowball and will inevitably yield a reduction in ROI. Therefore, for AI within a TOS to be beneficial for a terminal, it must devise an architecture that sustains real-time control planning to ensure that CHEs are always making the optimum number of moves and achieve accurate decisions.

Technologies that adopt various characteristics of human intelligence and behavior are typically referred to as Artificial Intelligence (AI). It is the study of agents that analyze their surroundings to create plans and accomplish the best decision after accounting for both retrospective and current percepts. AI is a construct using two techniques, which are machine learning and deep learning. Although these derivations are closely related since deep learning is a subset of machine learning when put in simple terms, they have distinct characteristics which impact AI differently.

Machine Learning

Machine learning uses algorithms which interprets data, learns from it, and then applies the knowledge to achieve informed decisions. This term falls under the umbrella of AI as it is used to forecast and render conclusions based on the data analyzed. Rather than following the conventional route of human learning, machine learning is instead, engineered to be proactive when confronting complex and dynamic environments. It uses the provided data to perform this function and progressively improves.

Deep Learning

Machine learning and deep learning are loosely interchangeable due to its similar functions; however, the distinguishing factor lies in its capabilities. Deep learning generates algorithms which analyze data continuously using a logical structure similar to how a human would deduce conclusions, entirely on its own. The overall deep learning decision-making process is driven by a multifaceted framework of algorithms called an Artificial Neural Network (ANN). An ANN is reflective of a human brain, which by far, exceeds the standard machine learning in the aspects of capability and intelligence.

Another disparity between these two concepts draws machine learning as more dependent on engineer intervention to resolve inaccurate algorithm predictions. On the contrary, a deep learning model is independent and can identify whether their prediction is accurate or not on its own. Essentially, correctly executed deep learning is the core fundamental powering true artificial intelligence.

Categories of Artificial Intelligence (AI) – Weak and Strong

AI can further be classified as weak or strong. Weak AI is characterized by its limited design and set of rules conforming it to a particular task. It cannot act upon any information beyond the scope of their assigned rules. For instance, Apple’s Siri may hold the impression that it is very intelligent for being able to respond in conversations and make snarky remarks, but as soon as it is asked a question outside what it is programmed to answer, Siri struggles to deliver accurate results. Although the Internet is an encapsulation of the entire world’s knowledge, leveraging the information and data to power AI is not enough for it to respond in dynamic situations. Its intelligence to compute and make conclusions is capped at an extent since they are only capable of what they are wired to do, which is why Siri’s “Sorry I didn’t quite catch that” has become quite the familiarity. The key takeaway is that weak AI is very competent in executing tasks that it is programmed to do and may even become exceptional at it; however, its stream of certainty is lost when it diverges from the job it is assigned to do.

On the opposite spectrum, the limitations of strong AI are almost non-existent, as it is capable of mimicking cognitive functions without discrepancy from a human mind. Other than adopting the same skillset as humans to facilitate reasoning, problem-solving, planning, learning, and communicating; true intelligence also requires a consciousness with sentiments and self-awareness. These key attributes are crucial in the learning process, which starts with a childlike mind and matures with learning and development. After reaching this stage, it should be able to interact with its surroundings make inferences independently and even render their own creations. However, due to the complex construct governing strong AI, we have yet to witness a technology that embodies true intelligence in its entirety.

Although AI is still in the early stages, RBS has already developed upon its true principles by integrating vital AI attributes to achieve berth optimization. To ensure your terminal meets efficiency in all areas ranging from planning to forecasting, click here to find out how.

Current Landscape

The global supply chain can be alluded to as a network, branching out and connecting several other nodes. Namely, international trade and technological advancements are the underlying sources which influence the overall landscape – extending from the global supply chain to globalization and the entire economy. These two driving forces have formed a pact to pervade other industries, prompting its recognition when conducting business. A grave inference draws these factors as the direct outgrowth of marine terminals. Therefore, the whole economy relies on terminal operations and will plummet if it is exposed to vulnerabilities which may be attributed by an inefficient terminal operating system.

The Problem

Terminals that centralize on a business strategy resisting change end up taking resource intensive routes. A rippling effect will ensue, causing detriment to terminal revenue, magnify inefficient terminal operations, and affect the global supply chain, which is inherent in steering the overall economy. As a result, this should not be the primary goal of any business – this narrow-minded view relays onto a single focus adopting only the necessary actions mitigating change, shackling potential and massive growth. Instead, businesses should retain a reformed perspective on adaptability that responds proactively to changing environments and build various avenues to elevate the economy. An economy that “stays in the expansion phase of the business cycle” is a prolonging and collective goal of many worldwide, whereby technology advancements pose as a substantial factor influencing the decision-making process in every industry. More than ever, the one at large are marine terminals, requiring the cooperation with beneficial technological innovations to engender a thriving economy.

If every business process is stripped down to its resources, the point of supply is terminals. Therefore, they hold a crucial responsibility in adopting a flexible terminal operating system that has the dynamic capacity and innovative functionality to respond to a fluctuation in container throughput. A terminal operating system that is unrepresentative of innovation and fails to incorporate the suite of capabilities that can account for all terminal operations or drive efficiency is a recipe for disaster. Although, advancements in technology may become disruptive, rejecting its presence may deprive avenues that present more efficient methods to running terminal operations, which not only degrades its market position but also drives a downturn in the economy.

The Response

Many avenues strengthen the global supply chain, but the place to start is selecting the correct terminal operating system that cares about your growth, prospects, and objectives. A common denominator that reinforces a viable TOS should include the following innovative technologies:

• 云计算

If the TOS is built on a true cloud architecture, all your data is maintained in a centralized system, granting access from anywhere at any time. A dual advantage is warranted to smaller terminals since they can adopt a pay-as-you-go payment model while larger terminals can achieve economies of scale, which generates extremely low costs for both structures. Enhanced accessibility corresponds to greater efficiency since terminal operators gain better control over operations since resources can be invested to accomplish other business strategies as opposed to maintaining IT facilities which are not needed when using a TOS in the cloud. For more details on cloud technology, click here…

• 自动化

A terminal which experiences many bottlenecks or errors may request the integration of automation into their TOS. Automation, if executed correctly, would render a decrease in error rate and heighten operational efficiency by sustaining the interoperability between a TOS and automated container handling equipment. Due to this nature, an increase in ROI will be achieved. For more insight into the world of automation, click here…

• 优化

Optimization drives functionality that highlights resource, process, and CHE strategy as the core components for efficient operations. An accurate optimization module will make the best possible use of available resources, streamline the execution process, and determine the most optimal number of CHE moves to deliver efficient operations. To gain a deeper understanding of optimization, click here…

• 人工智能 (AI)

A TOS manifesting an infrastructure supportive of a true AI architecture is very rare in the Container Handling Industry. Only offered at RBS, TOPS Expert optimization module integrates AI into berth planning and yard planning to reduce the workload which is practically impossible to calculate manually without entering a trade-off between accuracy, time, and resources. The TOPS Expert AI optimization module exhibits human intelligence in planning to improve reliability in decision-making processes, which intrinsically induces a higher degree of operational efficiency and mitigates error rates. For a more in-depth knowledge of AI, click here…

Ultimately, terminals must comply to a path that leads to a better economy by adopting a TOS that can leverage and proactively adapt to change. Otherwise, a TOS that is unresponsive to new innovative technologies will neglect a terminal from reaching its maximum potential in performance and productivity, putting the economy in a downward spiral.

Terminal optimization is segregated into divisions that are allocated different roles and responsibilities. Optimization in the Container Handling Industry is conceived due to terminals experiencing various bottlenecks when vessels berth at the port, inefficient yard planning affecting container movement, the disarray of CHE instructions causing congestion, and poor management of resources which fail to maximize time. If an area of a terminal evokes inefficiency, it will inevitably impact another which can engender various risks that will accumulate until a complete catastrophic outbreak dismantles the entire terminal. Consequently, terminals are in pursuit of a terminal operating system that incorporates a suite of capabilities that counteract these implications.

Vessel berthing is the most prominent area where optimization has been instituted to enhance planning processes which is accountable for maximizing terminal capacity and limiting congestion. A unique function only offered in RBS, is TOPS Expert is Artificial Intelligence (AI) Berth 优化, which incorporates cutting-edge technology that mimics human behavior by gathering then understanding data to develop algorithms utilized to optimize berth planning. Not only is discharge operations executed at the highest degree of productivity such that it meets the critical vessel schedule when AI is integrated into the vessel berth planning process, but it substantially reduces the amount of human intervention. Personnel no longer must spend copious amounts of time manually analyzing calculations to determine the best date and time to schedule a berth since this conventional method of planning is simply not efficient, nor is it reliable. With AI, decision-making is achieved much faster with extreme accuracy as ETAs and ETDs are strategically and automatically depicted. Real-time visibility is inherently amplified with TOPS Expert AI Berth Optimization module as terminal operators can foresee the actual workflow regarding the vessel operation, eradicating any ambiguity. A positive correlation also emanates from this module for vessel operators as they can save fuel and energy costs due to optimized travel distances. Terminals, therefore, must re-evaluate their TOS and berth optimization functionalities if they confront bottlenecks that are impacting their profitability – let AI do the thinking so you can work smarter not harder.

Deprived throughput may be attributable by a TOS lacking in infrastructure or competency to perform and deliver optimal decisions. As a result, yard space may not be used to its maximum potential, creating chaos when a container enters and departs from a terminal. These complications are offset by deploying a TOS that can efficiently plan the allocation for containers not just when they are active or discharged from the terminal but even prior to their arrival. Strategically managing the containers limit the number of container moves, facilitating CHE optimization as the task is executed faster, and the CHE can move onto other processes. Countermeasures such as seeking for an ameliorate TOS must commence when poor yard management pose as a constraint inhibiting optimization.

The performance of CHE, processes, and resources are the key drivers determining the criticality of vessel berthing optimization and yard optimization. The ability to calculate the minimum number of CHE moves required to move a container from one location to another should be reinforced in the TOS. Like TOPS Expert, every process is carefully planned to consider every set parameter, provide alternative scenarios, and heed only the necessary resources to calculate the shortest but the best path in executing the action. Therefore, as the components in berth optimization and yard optimization are derived and refined, there is a clear inference that optimizing CHE, processes, and resources are just as pivotal since they are the principal factors in defining terminal performance. Always conduct thorough research and evaluate each TOS against its infrastructure, capabilities, and range of functionalities before deciding on which to deploy.

There is an inherent interrelation between technology and trade – whereby inducing advancements in technology instigates further growth of globalization. With containerization playing an integral role in this process, it is critical to understand that the global supply chain has become incredibly dependent on terminals to fuel the economy. Countries worldwide who are working towards a more sustainable economy, hint that terminals, regardless of their size or type of cargo they manage, must expedite their presence in the Container Handling Industry to participate as well as attribute to the growth in the economy. Therefore, all terminals must ensure their operations are always executed at the optimum and adopt a Terminal Operating System (TOS) that is best tailored to their current and future needs at a cost-effective price.

The purpose of a TOS is to accommodate to all operations and processes which provide palpable insight to assist in planning and heed greater visibility over the performance of terminal operations. Selecting a static TOS that only satisfies current projected requirements is an illustration of tactical planning that centralizes only on short-term goals. Although tactical planning can generate immediate results, it may also pose as a barrier to prospective success. Terminals, as a result, must be diligent when selecting a TOS that not only fulfills specialized needs but reinforces both tactical planning and strategic planning to conjure functionalities that are also future proofed. As a terminal grows, their operations and objectives inevitably change, requiring a flexible TOS that can easily accommodate to these scalabilities without incurring irrational expenses or fuss.

Rejecting a TOS with comprehensive functionalities conform to the narrow mindset that limits future opportunities and paves a broader stream for operations becoming obsolete or ineffective. Instead, terminal operators should take prudence and care when selecting a TOS such that it adheres to these following elements:

• Scalable – easily add memory and various modules such as 自动化, 人工智能 (AI), 优化, etc. when terminals encounter a change in objectives or respectively experience higher throughput and growth
• 灵活 – an open TOS system that can interface with any third-party systems such as Gate Operating Systems (GOS), DGPS, automated CHEs, etc. to support automation, business intelligence, and IoT strategies
• Future proofed – avoid TOS’s which integrate just enough functionalities to satisfy current needs as it may be lacking in capabilities due to poor and redundant infrastructure. Seek for a TOS that has all-inclusive functions that accounts for every possible container operation on the spectrum to increase efficiency and limit unproductivity
• Cost-effective – the pool of TOS’s that can concurrently perform exceptionally, offer various and comprehensive functionalities, and provide services at a low price is extremely limited and difficult to discover in the market. Terminal operators should, therefore, consider adopting a true cloud-based TOS to leverage all these benefits without compromising their financial resources

The overarching inference warrants that a terminal operating system in the cloud is the most viable choice as it encompasses all factors ranging from scalability in functionalities to the most imperative; future proofing. When a TOS has purely manifested a cloud architecture, it is embedded with the capabilities to integrate any additional modules and ingest data in any manner which alleviates the need to adopt other external systems and data sources to operate. Any sentiments challenging this conception is a direct indication that the proclaimed cloud TOS is built on a forged infrastructure which is resource intensive and consequently cannot afford adhering to a pay-as-you-go model to offering cost-effective prices.

Although it may not be critical to the operations now, does not excuse it from being crucial for the future. Limit the pool of providers and instill a reliable web-based TOS that truly cares about your future. Never settle for less and find a TOS provider that is committed to your success.