With the policy lockdown, port congestion, shortage of containers** and container shortages during the new crown epidemic, coupled with the impact of practical factors such as the blockage of the Suez Canal and the drought of the Panama Canal, it has caused immeasurable negative challenges to the operation of enterprises. Countries** and companies must focus on building new decision support systems to effectively respond to these disruptions.
Global shipping is a self-organizing system in which most of the participants, while interdependent in nature, are still largely making major decisions independently. As a result, the shipping industry is fundamentally an industry that is severely underoptimized. There are many different ways in which shippers may attempt to resolve the same issue. For example, some shipping companies prefer to resume services in the Suez Canal, while others may decide to open new routes through the Cape of Good Hope.
The global system is a labyrinthine and complex system, and if there is no comprehensive and macro perspective, independent intervention in individual links is likely to have negative consequences that are difficult to achieve. As part of the global system, the establishment of high-fidelity digital models with dynamic and real-time automatic identification of system data flows (including AIS automatic tracking system and other data) is expected to continue to calibrate the operational thinking of the shipping industry, enhance industry cohesion and greatly enhance the possibility of maintaining efficient operations.
Large self-organizing systems are complex, and any isolated behavior can have a non-linear effect. Evolution at the biological level is not enough to give humans the ability to interpret this complexity. Computer-based tools, system dynamics, data analysis, visualization, and even machine learning are gradually outlining a feasible path for us to develop the best solutions.
Chain disruption crisis: The canal system is unsustainable
The Suez Canal is an important waterway for global commercial shipping, but geopolitical conflicts have led to serious challenges to its normal use, and alternative routes that bypass the whole of Africa are also at risk.
South Africa's bunkering capacity has been stretched for a long time, and the rapid use of bunker fuel** has further exacerbated this challenge.
The Panama Canal has always been a guarantee of fast navigation between the Pacific and Atlantic Oceans, but due to the arid climate, the capacity of the canal has fluctuated dramatically recently. Extremely low levels have forced the canal** to cut back on the number of vessels crossing the border, and although similar problems have occurred before, the canal has recently experienced its worst outage on record. This will continue to impede the flow of goods in the short term and for the foreseeable future, costing the canal operators billions of dollars in lost revenue, and driving up transportation and emissions costs.
Digital twins for disruption management
At the heart of resilience and managerial intervention mechanisms is decision-making, which is at the heart of any organization. Organizations need to act on the intended effects of interventions, and the most reliable way to make decisions today is to build a digital twin of the environment and simulate the impact of a potential action or event.
A digital twin is a dynamic digital representation of an object or system that describes its characteristics and properties through a set of equations. In difficult decision-making environments where many actors are involved and processes are highly complex, it's best to digitally model the entire system before taking action. A digital twin contains the hardware that collects and processes data, as well as the software that represents and manipulates that data.
Digital twins utilize digital data streams to bridge the gap between physical entities and their representations. Digital twin analysis relies on historical data and real-time digital data streams (e.g., AIS and sensor-generated data) to analyze possible outcomes and provide answers to questions such as "if xx will xx" or "if not xx" to support efficient decision-making.
Options
Digital twins require the input of a variety of historical and real-time data that can affect navigational judgments, including weather conditions, fuel**, bunker replenishment possibilities, canals, ports, terminals, and other bottlenecks, and data sharing between peers and institutions can help close the data gap.
Digital twins can provide real-time support for decision-making in dynamic environments.
As the foundation of agile chain management, the digital twin is equivalent to a digital replica of the global chain network, providing real-time visualization of operational data, including goods in transit and inventory metrics. With modeling tools, organizations can immediately visualize the likely impact of an outage, identify potential directions, and determine future risks.
This allows us to simulate different scenarios and destructive events such as natural disasters or regional conflicts. **The resulting insights can be used to plan and design alternative routes or fuel procurement options, taking into account the transit time and cost implications of each of the multiple available routes.
What's more, digital tools are able to facilitate communication and collaboration between the network. **Chain integration enables the coordination and correction of established actions at any time, and responds to crises in a highly collaborative and consistent manner.
The Virtual Tower (VWT) initiative is a real-world example of how to implement disruption management in a human-machine interaction manner. It manages the dependencies between shipping and the various players in the **chain industry in a novel way. Through a shipper-driven, terminal-centric, distributed network planning approach, the project combines community building with the development of digital solutions, where digital solutions are developed by all parties involved in the chain system to better address common challenges.
As the community continues to grow, so do the interests of all parties and the community as a whole. In this process, the core policy of continuous sharing and co-creation also strongly guarantees the suitability of the solution. With more accurate data, virtual towers can greatly complement the gaps and shortcomings in existing visualization solutions.
More cooperation is needed to eliminate chain disruptions
Cooperation is always the premise of creating a perfect chain. To effectively respond to systemic challenges and complex crisis situations, each actor needs to contribute to the eventual establishment of global situational awareness, which in turn will give all individuals a clear understanding of the increasingly dynamic current situation.
Digital twins can provide quantifiable social, environmental and economic value by improving crew safety and reducing CO2 emissions. In the maritime sector, the proliferation of AIS data sharing (e.g., ship position and speed data) has created important real-time data streams. To achieve holistic collaboration across the industry through digital twins, this vast stream of data must continue to be supplemented with real-time voyage decisions, port berth and utilization plans, fuel availability, choke point status, and more.
But a new question remains: how can a self-organizing system build and maintain a real-time model that can support independent competitive decision-making? In the face of the inevitable risk of large-scale and uncontrollable outages, how should this system be coordinated to establish system-level resilience?
The answers to these questions are inseparable from the conscious and systematic cooperation between all stakeholders in the global ** chain. Perhaps the day when a comprehensive "coopetition and cooperation" relationship is realized is the time when this self-organizing digital twin system for shipping is put into place.