How To Apply A Digital Twin To Your Supply Chain
By Emily Newton, Revolutionized
Perhaps you’re at the point where you’re interested in using a digital twin to improve fleet management and other supply chain necessities. Here are some tips to keep in mind as you move through that process.
1. Ensure Your Digital Twin Gives A Complete Picture
A digital twin creates a virtualized version of company equipment, locations, and more. While business leaders are in the early stages of creating them, they must show exceptional thoroughness.
Vikram Murthi, vice president of industry strategy at LLamasoft, explained, “The supply chain system is a complex network of entities which needs an end-to-end representation that can be leveraged to respond to market pressures, external factors, and internal considerations — this model is referred to as the digital twin.”
Murthi also explained how complementing technologies could provide even more company benefits:
“The digital twin with AI, machine learning, and optimization techniques can be used to simulate and optimize the supply chain. The digital twin encapsulates suppliers, factories, contract manufacturers, distribution facilities, transportation lanes, and customer locations. Using the digital twin, businesses can evaluate the complex, interconnected trade-offs in capacity, service, inventory, and total landed cost.”
A primary advantage of artificial intelligence (AI) is that it can find patterns in gigantic amounts of data. Thus, you might use AI-driven conclusions to shape how your company uses the digital twin and gets the best outcomes.
2. Set Applicable And Achievable Goals
Implementing a digital twin is not something company leaders can do overnight. Instead, they should view the task as a significant undertaking, including setting goals and determining what resources would help with achieving those milestones.
In one recent instance, food and pet care brand Mars, Inc. moved ahead with its digital transformation — which included digital twins, as well as the Internet of Things (IoT) and AI. It initially deployed digital twins in manufacturing facilities to reduce waste, enhance margins, and help employees make more informed decisions.
However, the company intends to apply digital technology to the supply chain more widely soon. For example, some of the plans in the pipeline include using digital simulations to figure out how to create better products while taking things like an area’s climate and other specifics into account. If the company can make more offerings that won’t break, melt, or otherwise become unsellable during transit, that’s a supply chain optimization win.
It’s not sufficient to decide to start building a digital twin for fleet optimization or any other reason. Instead, the people in positions of authority at a company must create precise goals related to what they want to achieve by using that technology. From that point, it becomes easier to measure the return on investment (ROI) for the digital twin and identify potential ways to improve results even more.
3. Consider Using A Digital Twin To Reduce Losses Of High-Value Products
Business leaders frequently assess the best ways to improve transportation management with digital twins. Better oversight of how and where goods move allows company representatives to give precise updates to customers about item locations and expected arrival times. Such details are arguably especially desirable when dealing with perishable goods.
The importance of keeping goods within the required temperature range has become a popular topic during the COVID-19 vaccine rollout. During the early days of vaccine distribution, a climate control malfunction in a truck caused an investigation into 3,000 affected doses. Representatives said the vaccines never left the vehicle and that an unidentified issue caused the temperature in the storage area to get too cold.
However, fleet managers can avoid situations like those by deploying real-time digital twins for each shipment. Then, relevant parties can get second-by-second insights about a product’s current status and any potential issues.
It’s also possible to aggregate the data from digital twins associated with shipments happening across an entire country or region. Then, managers can broaden or narrow their insights into a fleet as needed.
If your company frequently experiences preventable losses due to transit errors or failures, think about how using a digital twin could minimize them or at least help you get to the bottom of what’s going wrong.
4. Implement Risk Planning When Using The Digital Twin
People can’t predict the future with certainty. However, digital twins can help them determine the most proactive ways to respond to possible issues that arise.
Cleaning brand Clorox recently upgraded its supply chain with numerous digital improvements, starting with a global planning tool. Before investing in that solution, the company experienced pain points associated with a vastly outdated product.
Kirk Niehaus, the company’s vice president of global planning and supply chain technology, discussed how Clorox would soon use digital twins for efficient scenario planning: “The use of routine scenario planning is so powerful — I can't overstate how powerful it is to be able to create a digital twin and generate multiple ‘What if?' analyses in minutes, not hours or days.”
He continued, “To be able to answer those questions about ‘What if?' — to understand, can we do it? What if we take that big order? What if we have a supply outage? We're going to invest substantial resources and time into learning that skill and being able to perform that on a very regular basis. It's just super important for us as a planning team and being responsive to the business.”
Before moving ahead with this tip, think about the risks that are most likely to affect your business and prioritize those. It could prove too resource-intensive to simulate scenarios that have a minuscule chance of impacting operations.
5. Use Digital Twins To Improve Decision-Making In High-Pressure Situations
Even the most experienced professionals occasionally experience fleet management mishaps. When those circumstances arise, it’s often necessary to make the most appropriate choice to mitigate the situation as quickly as possible. Delaying action could lead to lost profits and unhappy customers.
However, a recent project associated with MIT showed that digital twins could give people a more accurate picture of what ramifications certain choices may have. Researchers created the virtual models for delivery drones — which are increasingly popular as fleet management professionals address last-mile concerns.
The team’s work could become foundational for future digital models that predict things rather than only showing a current state. While testing their effort, the researchers built an unpiloted aerial vehicle with a 12-foot wingspan. It had adhesive sensors to collect data about acceleration, strain, and more.
The idea was that people would get those details fed into a digital twin that assists with decision making about whether to keep a damaged drone flying or command it to land. Incidents could happen during a flight that harms the vehicle, but not enough to necessitate immediately ending its trip.
That’s a concept still under development. However, fleet managers can take inspiration from it by ensuring their digital twins include information about all applicable vehicles. Getting details about things such as a truck’s gas mileage or the time since its last oil change could steer decisions about which vehicles to use for specific trips.
Digital Twins Improve The Supply Chain And Fleet Management
Digital twins require time and resources to implement successfully. However, these tips and examples show that using them can pay off in meaningful ways.
About The Author
Emily Newton is the Editor-in-Chief of Revolutionized. She regularly explores the impact technology has on the industrial sector.