The use cases of digital twins are many across the industry. The following are a few use cases of digital twins in logistics. Let’s take a look at what they are.
Supply chain coordination
Internal and external stakeholders, buyers, merchants, customers, finance departments, manufacturers, agents, etc., are some of the stakeholders involved in logistics. That’s a lot of hands in a cookie jar.
Managing these huge numbers of personnel for each project is hectic. One wrong move and things could go south fast. Relaying real-time information is the crux of the process. So digital twins create a single, unified view of the entire network to aid in planning and execution,
Agile planning and execution
Let’s take a look at the things that could go wrong-
Transportation delay
Rate changes
Manufacturing problems
Customer issues
These are situations where change occurs rapidly in supply chain management. Try integrating the data manually, you will mess up.
Manual information gathering and disparate systems can now be replaced with up-to-the-minute data that reflects on-the-ground conditions. How? Digital twins.
By sourcing data in real-time, and flagging threats and issues earlier gives the team a buffer time to react. It minimizes disruptions, costs, and potential stockouts by allowing plans to be adjusted.
In logistics, improvisations will be like knocking over a Domino. The need to explore a variety of options and find the optimum response is crucial. When teams receive information in advance, they can manage routing or processes to meet deadlines comfortably.
Cost management and reduction
A change in supply chain conditions can result in extra costs, such as rebooking and D&D charges or charges for additional storage.
Teams can calculate the true cost of moving goods through the supply chain and quantify the impact of different stakeholders' actions by collating data holistically.
In the short run, you might use this view to evaluate the tradeoffs between different carriers, manufacturers, and routes to make better operational decisions.
In the long run, planners, equipped with a fuller view of where spend is incurred, can more confidently optimize the overall cost structure of the business without harming lead times and inventory levels.
Discover the crucial role of digital twins in manufacturing.
Long-term optimization
It is difficult to build a view of past and present supply chain activities and results that can be compared when data is not captured in a structured way that facilitates proper analysis and review.
As a result, supply chain issues go unnoticed and damage long-term performance as a result of the 'black box' that prevents progressive improvement.
A before/after analysis can be performed by standardizing historical data across suppliers, manufacturers, carriers, and internal processes.
In this way, it is easier to identify areas that may require process changes and distinguish them from one-time problems: for example, identifying a supplier that consistently delivers late or identifying a particular bottleneck from factory to port that creates inefficiencies, extra costs, and delays on a regular basis.
Improving sustainability
Businesses are under increasing pressure from customers, boards, and regulators to reduce their environmental impact. Although raw materials, manufacturing, and transportation will always produce emissions, teams can reduce any unnecessary impact by understanding the environmental costs of various suppliers and options.
By recognizing that stock levels in warehouses are sufficient to meet the demand for the next few weeks, the system can suggest ocean transportation for freight scheduled for air delivery, reducing carbon emissions and costs.
The system could reduce costs and environmental impact by rerouting goods from factories to ports instead of airports, tracking the availability of space on relevant ships, and possibly even combining goods from additional manufacturers into one container.
Even though there is a wide range of digital twin use cases, it comes with its challenges. Let's take a look.
Digital twins in supply chain management include warehouse management, supply chain mapping, and much more. If you are into logistics and lack this tech, you need to take a look at this.
