Combining AI and Digital Twins to Improve Supply Chain Performance

One of the most significant transportation crises occurred in the early months of 2023 when a cargo vessel, spanning an enormous length of 400 metres, was swept off course by powerful winds and subsequently became lodged in the Suez canal waterway, disrupting maritime travel to an unprecedented degree.

Recent information uncovered that the canal is relied upon for roughly 12% of worldwide trade, causing hourly losses of around $400,000,000 due to the vessel’s blockage. This occurrence serves as a clear warning to all of us about the delicate nature of our supply networks.

AI: Consequences of Malfunction

The application of Artificial Intelligence was eagerly accepted by the maritime industry as a solution for predicting shipping paths, port schedules, and enhancing overall efficiency. Regrettably, these advancements, including the use of Machine Learning and automation, were not enough to prevent the devastating event.

The benefits of Machine Learning are evident, however, it is not flawless. The effectiveness of this technology is influenced by the accuracy of the data used to create it. As a result, the machine learning model’s capacity to make accurate predictions reduces as the variation from the norm increases.

The Suez blockage and the COVID-19 pandemic are unpredictable events that pose challenges to data scientists and machine learning experts due to their nature being inconsistent with typical patterns of behavior, creating hindrances in forecasting them. Predicting the unpredictable is an onerous task.

An anomaly in data can be disregarded as an outlier and the usual patterns can be re-established, given that the events normalize. On the other hand, if this anomaly becomes the standard, the existing models will become inadequate, necessitating new data assimilation and model training.

The global supply chain predicaments, alongside distribution complications, demand more than just machine learning solutions. Diversifying our approach and investigating alternative strategies is imperative to guarantee that we are well-equipped to tackle future emergencies or unexpected predicaments.

Digital Replication of Analog Components

Amid the onset of the COVID-19 pandemic, researchers attempted to find ways to anticipate the virus’s transference. Surprisingly, some found innovative solutions for their research from the field of video games.

The Blood Plague incident took place in the massively multiplayer online role-playing game, World of Warcraft, in 2005. The occurrence of a virtual epidemic across gaming servers, alongside the players’ reactions that emulated real-world scenarios, revealed how similar circumstances might affect people in reality.

Plague Inc., a smartphone game with a remarkable disease control model, has been granted an invitation to speak at the Centers for Disease Control and Prevention (CDC) in 2023. In this game, players take on the role of solving a disease and preventing it from wiping out humankind.

The idea of digital replicas has existed since the 1960s, but it is relatively recent that businesses in industries like logistics, government, retail, and car manufacturing have adopted this technology to explore alternative solutions and examine diverse scenarios.

One of the most pioneering developments in current economics, acknowledged by Forbes, is the concept of a “Digital Twin.” In essence, it is a digitized version of a physical entity or system that has the ability to respond and develop much like the authentic object, in response to new and unforeseen situations.

Consider owning a store where we construct a precise replica utilizing technologies like digital cameras, the Internet of Things (IoT), and massive data collections. Once a consumer sets foot in the shop, this replicated model replicates and generates novel customers while imitating previous interactions such as enquires posed to sales staff.

A simulation lookalike, but with a significant difference: simulations are capable of predicting the future, whereas digital twins enable us to comprehend existing scenarios and predict potential outcomes.

Envvision an Internet of Things (IoT) data hub that constantly constructs virtual replicas of itself, providing program developers with the ability to simulate scenarios and produce digital environments with current, real-time data.

Digital twins offer an effective approach to examining likely outcomes without jeopardizing physical assets, similar to how philosophers utilize mental imagery and hypothetical scenarios to tackle intricate problems.

Gathering real-time data alongside historical information can significantly benefit supply chain managers in making well-informed resolutions with regards to inventory supplies and product redistribution. Additionally, simulations can prepare for unforeseen circumstances by ensuring availability and the ability to adjust to such events.

It is vital to understand that digital twins do not just produce information, but also require it to operate. Therefore, they are valuable in training Artificial Intelligence (AI) systems, which can simulate various models with distinct values for every variable, thereby providing accurate forecasts.

A Future for Digital Replicas After the Crash

A proactive, data-centered approach can reduce the consequences of disruptions and crises. Businesses can achieve this by utilizing real-time data and integrating details on inventory, demands, projections, backup suppliers, alternative routes, and delivery methods into an AI platform to develop contingency plans.

Digital twins serve more than just crisis preparedness and response. By collating pertinent data, employing real-time models and historical data, businesses can utilize digital twins to streamline performance in transportation, distribution centers, and other supply chain nodes.

Conducting simulations, tests, and assessments of alterations to our active operations before deployment eliminates the need for edge case scenarios, minimizing potential issues during process modernization.

Integrating digital twins with Artificial Intelligence (AI) holds the potential for an even more sophisticated supply chain model. By enabling immediate access to data, this could enhance transparency and reinforce openness across all stakeholders involved in the supply chain.

To sum up, digital twins promise an intriguing new logistics strategy with immense potential for precision, particularly with the acceleration of data transmission speeds by 5G and the development of more advanced IoT solutions.

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