The word digital twin is something we have been hearing about lately, but do we truly understand what it is? A digital twin is a dynamic, virtual representation of a physical system or operation across multiple stages of its lifecycle. It includes the real-world data, simulation data, or machine learning models, combined with data analysis, to enable understanding, learning, and reasoning. What makes them so useful is that digital twins are ideal for applying what-if questions or analyses to obtain a predictive analysis and to present the insights in an intuitive way. Digital twins are just one example of a broader trend towards digitalization that is having a profound effect on port businesses.
Because a digital twin is a realistic digital representation of assets, processes or systems in the built or natural environment, many people see it as a simple digital replica of a real thing – a ‘twin’. However, what distinguishes a digital twin from any other digital model or replica is its connection to its physical twin, with ‘connection’ meaning there is some type of relationship and association between the physical and digital. This is where the complexity of this industry-agnostic concept lies. Depending on its maturity, the twin can range from a simple 2D, or 3D model of a local component, all the way to a fully integrated and highly accurate model of an entire asset, facility or even process, with each element dynamically linked to engineering, construction, and operational data.
According to Gartner, a digital twin is a “digital representation of a real-world entity or system”. More exactly, digital twin technology provides the ability to create a virtual representation that accurately simulates both the physical components as well as the dynamics and behaviour of how an Internet of Things (IoT) device performs and functions throughout the entire duration of its lifecycle. This is achieved by collecting and interpreting vast datasets from deployed sensors to realize the desired sameness between the real-world element and its duplicate.
This broad range of what a twin can be has made defining and understanding them extremely difficult, with disagreement on what level of maturity or features represent a ‘true’ twin where it is part of data generation and information management.
When it comes to port management, digital twins provide visibility, resilience and a wealth of useful applications across the business processes and lifecycle of a port asset. They stand as a bridge between the physical and digital. Digital twin technology is one of the more interesting developments in the port digitalization space taking place right now.
Almost anything at port level can have a digital twin that can be used to:
- Gain insights into operational.
- Prolong the lifespan of equipment through better stewardship, i.e., preventive maintenance, ongoing parameter optimization.
- Minimize downtime.
- Use operational data to inform research and development, resulting in superior future designs and implementations.
Key Digital Twin Concepts:
A digital twin framework needs to consider both asset-centric and system-centric viewpoints, as well as the relationships between the two but what is a system? A system is any group of entities that are related and that interact according to a set of rules to form a unified whole. A system, surrounded and influenced by its environment, is described by its boundaries, structure, and purpose, and expressed in its functioning.
Different types of systems
A good way to understand the idea of a physical system is to look at the human body. The human body is a collective processing unit comprising several organs acting as subsystems. These subsystems work in coordination with one another. Subsystems cannot work alone because there are certain needs of every subsystem that need to be fulfilled and the subsystem itself cannot fulfill those needs. All subsystems of the human body system need to support each other to perform the processes. The state of this system hierarchy can be represented digitally in the same manner that an IoT device can be represented by a “digital twin”.
Digital Systems
Businesses and organizations of all sizes implement digital systems to control their operations efficiently and accurately. Each of these systems incorporates computing elements to manage, process, and store information objects.
Examples of digital systems include artificial intelligence (AI), machine learning (ML) and analytics engines, and applications, services.
Cyber-Physical Systems
Cyber-physical systems provide a key interface between digital and physical systems.
A cyber-physical system integrates computing elements with the physical components and processes. Cyber-physical systems use sensors to connect all distributed intelligence in the environment to gain a deeper knowledge of the environment.
Digital Twin Policy for Ports
By collecting the right data, setting standards, and sharing data securely for the port operation, a port authority is in a position to support the adoption of digital twins for port management.
The creation of a Digital Supply Chain Twin (DSCT), an ecosystem of digital twins connected by securely shared data, is an initiative to improve the performance, service, and value of the port, delivering benefits to society, business, the environment, and the economy.
Digital Supply Chain Twin
The Digital Supply Chain Twin (DSCT) is a reflection of the supply chain real world across its entire life cycle. It helps ports turn valuable data sets into models of port life in which the port’s information and facts are analyzed, shared and presented. With the use of a DSCT, ports can make better decisions, gain operational efficiency, monetize data, and offer better risk management. By using advanced analytics and artificial intelligence, the DSCT simulates the supply chain’s complex processes and environment and helps the ports’ decision-makers test different scenarios, planning and process optimization to make decisions based on business needs.
The real value of the DSCT technology is directly related to the reliability, quality and depth of the data powering the model, such as operating data or supply chain data. To build the DSCT, the data that DSCT technology leverages is mainly historical data. However, the DSCT can be fed with real-time data stream as well. To build digital twin of a supply chain system, the main challenge is the data collection. The data needs to be extracted and collected from various sources and should be cleaned as the data quality is crucial part of this process. Therefore, the port’s management should leverage data transformation tools that use AI and machine learning to enhance data quality.
Digital Supply Chain Twin Benefits
Digital Supply Chain Twins allow the port’s management to understand their supply chain dynamics. A DSCT reveals the hidden information that’s helping to make a better decision. Some benefits associated with a digital supply chain twin include:
- Dynamic optimization by offering the ability to continuously optimize supply chain performance.
- Short-term and longer-term planning: the port’s management can improve the efficiency of capex and optimize the supply chain system by understanding where the bottlenecks exist and how much additional capacity is needed.
- Understanding of patterns, behaviour, or situations to reduce costs and improve efficiency of processes.
- Monitoring: to provide an end-to-end monitoring for port processes to help port management take efficient decisions at a real-time.
- Predictive analysis: to provide a port with significant foresight by simulating future scenarios that enable ports to re-evaluate their data, efficiency, and resource requirements.
