Supply Chain Digital Twin Technology

Supply Chain Digital Twin Technology

Dorota Owczarek - January 3, 2023

Digital twin technology is a revolutionary new way for businesses to have a 360-degree outlook on their businesses. Digital twins are a popular solution in pharma or manufacturing sectors because they allow companies to simulate and optimize their processes in a virtual environment before implementing changes in the real world. Logistics and supply chain management companies are not staying behind and are applying this technology to improve their operations as well. By creating a virtual replica of their supply chain, companies can analyze and understand their processes in a way that was previously not possible. Predictive analytics can also be very useful in supply chain management.

In this blog post, we’ll explore what a supply chain digital twin is, the benefits it can offer, and some examples of companies already using this technology to their advantage. We’ll also discuss some challenges and considerations a business should consider when implementing a supply chain digital twin. So, without further ado, let’s dive into the world of supply chain digital twin technology.

Supply Chain Dynamics

Global supply chain management is a wild ride. One minute, demand is sky-high, and you’re struggling to keep up. The next, it’s tanked, and you’re stuck with excess inventory. And let’s not even get started on the bumps and detours caused by transportation issues, technological disruptions, and world events. Many factors can influence the flow of goods and services. Effective management of these dynamics is essential for maximizing efficiency, minimizing costs, and maintaining customer satisfaction. While navigating this terrain can be challenging, companies that can anticipate and adapt to changes in the supply chain can gain a competitive advantage and stay ahead of the competition.

What Is a Supply Chain Digital Twin?

Have you ever wished you had a magic mirror that could show you exactly what’s happening in your supply chain at any given moment? Well, wish granted! Introducing the supply chain digital twin - the virtual twin of your supply chain that gives you a crystal clear view of its inner workings. It allows an organization to analyze and understand its supply chain in a way that was previously impossible, by providing real-time data and insights into the flow of goods and services from suppliers to customers.

Digital twin technology can also track and monitor shipments in real time, providing greater visibility and control over the supply chain. This revolutionary technology allows to simulate and optimize the logistic processes in a virtual environment, giving logistics companies the power to identify bottlenecks, reduce waste, and improve performance.

It’s like having a crystal ball for your supply chain - providing real-time data and insights that can help you make informed decisions and stay ahead of the competition.

End-to-End View on Supply Chain Network

Supply chain digital twins track a wide range of historical data (and access to real time data streams) to provide a comprehensive model and understanding of the supply chain. A digital representation of a real supply chain network can include the following:

  • Production and inventory data: This can include information on raw materials, finished products, and work-in-progress inventory, as well as data on production rates and capacities.

  • Transportation and logistics data: This can include data on distribution centers, routes, carriers, shipping and receiving schedules, and delivery times.

  • Customer and demand data: This can include data on customer orders, forecasts, and preferences, as well as on market trends and demand patterns.

  • Supplier and procurement data: This can include supplier performance, delivery times, and quality.

  • Financial data: This can include costs, sales, orders, revenues, margins, and profitability.

    The landscape of logistics data sources

    The landscape of logistics data sources

Benefits of Using a Digital Supply Chain Twin

The value of digital twins is fourfold. It provides descriptive, analytical, diagnostic, and predictive value. Advanced applications implemented by supply chain leaders have one more - prescriptive value. These values resemble in the following direct benefits of applying digital twin solutions in the supply chain industry:

Improved Decision-Making and Forecasting

By providing real-time data and insights into the supply chain network, digital twins can help many organizations to make more informed decisions and improve their forecasting capabilities. Digital twin technology lets you model and test the supply chain’s behavior under specific circumstances (e.g., how well the physical supply chain is prepared for increased demand or delays from subcontractors, predictive and prescriptive maintenance solutions). Advanced analytics and artificial intelligence can lead to better utilization of resources, more accurate planning, and reduced risk of unexpected disruptions.

Increased Efficiency and Productivity

A digital twin can help to identify bottlenecks and inefficiencies in the supply chain, allowing businesses to optimize their processes and improve productivity. Process optimization based on insights from digital supply chain systems may result in faster turnaround times, reduced lead times, and increased output.

Improved Supply Chain Resilience

Improved supply chain resilience in regard to digital twin technology refers to the ability of a digital twin to help a supply chain withstand and recover from disruptions. Real-time data and insights into the supply chain from a digital twin can help businesses to identify potential vulnerabilities and take proactive measures to minimize the impact of disruptions.

For example, a digital twin model might alert a company to a potential bottleneck in its production process or create contingency plans based on insights from the end-to-end model, allowing the company to take steps to address the issue before it becomes a significant problem. Or a digital twin might help a company to identify alternative transportation routes or suppliers in the event of a disruption, allowing the company to maintain a high level of customer satisfaction.

Cost Savings and Reduced Risks

By optimizing the supply chain and eliminating waste, digital twins can help organizations to reduce costs and minimize risks. This can include everything from lowering transportation costs (with better route optimization and shipment scheduling) and reducing inventory levels to minimizing the impact of unexpected disruptions (like stress testing warehouses with stocking inventory).

Enhanced Customer Satisfaction and Service Levels

In today’s fast-paced world, customers expect speedy service and timely delivery. A supply chain digital twin can help you deliver on that promise and then some. By optimizing your processes and reducing lead times, this technology allows you to get orders out the door faster than ever before. And when you make your customers happy, they’ll keep coming back for more.

Limiting Carbon Footprint

Using a digital supply chain twin can also help businesses to limit their carbon footprint by identifying opportunities to reduce energy consumption and increase sustainability in their supply chain. For example, with digital twins, organizations can analyze transportation routes to identify the most fuel-efficient options, or it can suggest alternative modes of transportation such as rail or sea shipping.

It can also help companies to optimize their production processes to reduce waste and energy use, leading to a more sustainable and environmentally-friendly supply chain. By taking steps to reduce their carbon emissions, businesses can not only reduce their environmental impact but also improve their reputation with customers and stakeholders.

Companies Using Digital Supply Chain Twin Technology - Case Studies of Successful Implementations

Supply chain leaders are already implementing digital representation of their supply network and leveraging digital twins in their daily operations.

Digital Twins in Manufacturing

Digital twin technology has been widely adopted in manufacturing operations due to the abundance of data available in these environments and the focus on producing physical assets. By using digital twins to simulate and optimize production processes, manufacturers can improve efficiency, reduce waste, and increase profitability.

Leading aero engine manufacturers such as GE, Rolls-Royce, and Pratt & Whitney are at the forefront of digital twin technology adoption. They use digital twins in various stages of their operations, including new product development, manufacturing, and customer aircraft engine monitoring and support. Siemens, the German multinational engineering company, used a digital twin to optimize the production of gas turbines at its manufacturing plant, and is widely applying these techniques in other production processes. These companies are leveraging the power of digital twins to drive innovation and improve efficiency in their manufacturing operations.

Digital Twins of Shipments

Digital twins of shipments can be used to track and monitor the progress of a package or cargo as it moves through the supply chain. These digital twins provide real-time data on the location, condition, and status of the shipment, allowing businesses to identify potential issues and take corrective action. For example, a company might use a digital twin of a shipment to monitor the temperature and humidity of a perishable cargo, ensuring that it is being transported in optimal conditions.

One real-life example of a company using digital twins of shipments is FedEx, the global courier delivery services company, which uses a digital twin to optimize the routing of its delivery trucks and track shipments at all times.

From reactive and real-time visibility of the fleet, cargo details, schedules, etc., to predictive and prescriptive modeling for fleet and route optimization.

From reactive and real-time visibility of the fleet, cargo details, schedules, etc., to predictive and prescriptive modeling for fleet and route optimization.

Related case study: Implementing AI model to optimize routes and timelines of deliveries

A company from the logistics sector approached us to create a custom AI model that optimizes routes and the scheduling of deliveries.

Our challenge? The key challenge here was to prepare a dedicated AI-based system designed for carriers to optimize delivery time depending on the destination address. Thanks to the model we managed to reduce failed and late delivery rates by 30%. Read our detailed case study of this project.

Digital Twins of Warehouses and Distribution Centers

With warehouse digital twins, companies can optimize the layout and design of new facilities, simulating the movement of products, personnel, and material handling equipment to maximize space utilization. These virtual models provide a valuable tool for planning and decision-making, helping companies to streamline their operations and improve efficiency.

To optimize operational efficiency and improve safety in their warehouses, DHL uses heat maps based on Internet of Things (IoT) technology. These heat maps provide real-time data on the movement and behavior of warehouse personnel, allowing DHL to identify areas for improvement and lay the foundations for safer working practices.

Digital Twins of Global Supply Chain Network

In the world of logistics, the ultimate digital twin would be a model of an entire network, encompassing not just individual assets but also the entire transportation system, including oceans, railways, roads, and even customer homes.

By creating digital twins of their logistics networks, providers can use data on customer locations, demand patterns, and travel times to optimize their operations. This might include planning more efficient distribution routes and identifying the best locations for inventory storage.

Related case study: Developing a logistics platform offering real-time visibility and integrations with different carriers

One of our clients was seeking to improve the global supply chain optimization product

Our challenge? Providing visibility and data transmission for maximum efficiency and control. We supported solution development for end-to-end execution of logistics activities in Supply Chain Management at the PO/SKU level, including PO creation, stock management, suppliers and distributors management, consolidation and load planning, carrier allocation, documentation, and final delivery. Read more about this case study.

Philip Morris International (PMI) has utilized the power of digital twins by creating a virtual model of their global manufacturing and logistics footprint. This allows them to analyze and anticipate the effects of changes in product portfolio, market demand, and procurement network. PMI can then optimize scenarios related to manufacturing costs, duties, and transportation costs across their network, resulting in a 90% reduction in spreadsheet simulations and a drastic decrease in scenario-evaluation times from weeks to hours.

Benefits of AI and digital twins on every step of the supply chain management flow to support decision-making

Benefits of AI and digital twins on every step of the supply chain management flow to support decision-making

Challenges and Considerations for Implementing Supply Chain Digital Twins

Clear Objectives are Key

When implementing digital twin solutions, it is essential to have clear objectives. This can help to ensure that the project stays on track and delivers the desired results. One practical approach is an iterative process, targeting different scenarios and workloads before creating a complete digital twin of a supply chain network. This allows the company to build and refine the digital twin model incrementally rather than tackle the entire project simultaneously.

With clearly set goals and objectives, a business can prioritize its efforts and ensure that it is making the most of its resources. It is also essential to remember that digital twins are dynamic and evolving tools, and the objectives may change over time as the company’s needs and priorities shift.

Cost and Resources Required

Implementing a digital supply chain twin can be a significant investment in terms of both time and money. Companies will need to allocate resources for the design and development of the digital twin, as well as for training and ongoing maintenance. It’s essential for a business to carefully evaluate the potential benefits and return on investment before committing to a digital twin project.

Big Data Processing - High Throughput and Low Latency

Digital supply chain twins generate and analyze large amounts of data in real time, requiring high-throughput and low-latency processing capabilities. To achieve a precise representation of their networks, companies must ensure that they have the necessary infrastructure and resources to handle this data volume and speed.

Integration With Existing Systems and Processes

A digital supply chain twin should be integrated with a company’s existing systems and processes to provide accurate and relevant data. This can be a complex and time-consuming process, requiring the coordination of multiple teams and departments.

Future Potential for Digital Twin Technology in Logistics and Supply Chains

The future potential for digital twin technologies in logistics and supply chains is vast and exciting. As organizations continue to embrace these new technologies, we can expect to see even more innovative and transformative use cases emerge. The possibilities are endless, from optimizing production and transportation to improving forecasting and decision-making with advanced machine learning models.

If you’re a logistics or supply chain management company looking to leverage digital twins technology to improve your operations, we invite you to contact nexocode’s team of data engineers. Our experienced team has a track record of building advanced solutions for logistics and manufacturing companies, and we would be happy to discuss how we can help your business succeed. Don’t let the competition get ahead - seize the opportunity and contact us today.

References

DHL Digital Twins in Supply Chain Report

Capgemini Report on Digital Twins

About the author

Dorota Owczarek

Dorota Owczarek

AI Product Lead & Design Thinking Facilitator

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With over ten years of professional experience in designing and developing software, Dorota is quick to recognize the best ways to serve users and stakeholders by shaping strategies and ensuring their execution by working closely with engineering and design teams.
She acts as a Product Leader, covering the ongoing AI agile development processes and operationalizing AI throughout the business.

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This article is a part of

AI in Logistics
31 articles

AI in Logistics

Artificial Intelligence is becoming an essential element of Logistics and Supply Chain Management, where it offers many benefits to companies willing to adopt emerging technologies. AI can change how companies operate by providing applications that streamline planning, procurement, manufacturing, warehousing, distribution, transportation, and sales.

Follow our article series to find out the applications of AI in logistics and how this tech benefits the whole supply chain operations.

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