How digital twins can transform trucking operations
The trucking industry is facing unprecedented cost challenges and pressure to improve operational efficiency. Digital twins have the potential to radically improve fleet planning in ways that could minimize deadheads, reduce driver dwell time, and maximize driver and asset utilization.
Balaji Guntur is a co-founder and chief executive officer of Hoptek, a trucking industry-facing software company, and also a vice president in the Transportation practice of global strategy and management consultancy Kearney.
This story first appeared in the September/October issue of Supply Chain Xchange, a journal of thought leadership for the supply chain management profession and a sister publication to AGiLE Business Media & Events’' DC Velocity.
For the trucking industry, operational costs have become the most urgent issue of 2024, even more so than issues around driver shortages and driver retention. That’s because while demand has dropped and rates have plummeted, costs have risen significantly since 2022.
As reported by the American Transportation Research Institute (ATRI), every cost element has increased over the past two years, including diesel prices, insurance premiums, driver rates, and trailer and truck payments. Operating costs increased beyond $2.00 per mile for the first time ever in 2022. This trend continued in 2023, with the total marginal cost of operating a truck rising to $2.27 per mile, marking a new record-high cost. At the same time, the average spot rate for a dry van was $2.02 per mile, meaning that trucking companies would lose $0.25 per mile to haul a dry van load at spot rates.
These high costs have placed a significant burden on the operations of trucking companies, challenging their financial sustainability over the last two years. As a result, 2023 saw approximately 8,000 brokers and 88,000 trucking companies cease operations, including some marquee names, such as Yellow Corp. and Convoy, and decades-long businesses, such as Matheson Trucking and Arnold Transportation Services.
More so than ever before, trucking companies need to get better at efficiently using their assets and reducing operational costs. So, what is a trucking company to do? Technology is the answer! Given the nature of the problem, technology-led innovation will be critical to ensure companies can balance rising costs through efficient operations.
One technology that could be the answer to many of the trucking industry’s issues is the concept of digital twins. A digital twin is a virtual model of a real system and simulates the physical state and behavior of the real system. As the physical system changes state, the digital twin keeps up with the real-world changes and provides predictive and decision-making capabilities built on top of the digital model.
DHL, in a 2023 white paper, suggests that—due to the maturation of technologies such as the internet of things (IoT), cloud computing, artificial intelligence (AI), advanced software engineering paradigms, and virtual reality—digital twins have “come of age” and are now viable across multiple sectors, including transportation. We agree with this assessment and believe that digital twins are essential to radically improving the processes of fleet planning and dispatch.
THE NEED TO AUTOMATE
Outside of attaining procurement efficiencies, trucking companies can achieve lower costs by focusing on critical operational levers such as minimizing deadheads, reducing driver dwell time, and maximizing driver and asset utilization.
However, manual methods of planning and dispatch cannot optimally balance these levers to achieve efficiency and cost control. Even when planners work very hard and owners strive to improve processes, optimizing fleet planning is not a problem humans can solve routinely. Planning is a computationally intensive activity. To achieve fleet-level efficiencies, the planner has to consider all possible truck-to-load combinations in real time and solve for many operational constraints such as drivers’ hours of service, customer windows, and driver home time, to name just a few. These computations become even more complex when you add in the dynamic nature of real-world conditions such as trucks getting stuck in traffic or breaking down or orders getting delayed. This is not a task humans do best! For these sorts of tasks, technology has the upper hand.
When a company creates a digital twin of its trucking network, it has a real-time model that factors in truck locations, drivers’ hours of service, and loads being executed and planned. Planners can then use this digital model to assess possible decisions and select ones that increase asset utilization, improve customer and driver satisfaction, and lower costs.
For example, a digital twin of the network can offer significant insights and analysis on the state of the network, including exceptions such as delayed pickups and deliveries, unassigned loads, and trucks needing assignments. Backed by AI that takes business rules into account, digital twins can allow companies to optimize their fleet performance by finding the most efficient load assignments and dynamically adjusting in real time to changes in traffic patterns and weather, customer delays, truck issues, and so on.
With a digital twin, carriers can optimize the matching of assets, drivers, and freight. Typically, an investment in this innovative technology results in a 20%+ increase in productive miles per truck, while also improving driver pay and significantly decreasing driver churn. Drivers get paid by the miles they run, so when they run more, they are able to make more money, resulting in less need to chase the next job in search of better pay.
ADDITIONAL BENEFITS
Digital twins also combat deadheading, another source of driver dissatisfaction and cost inefficiencies. On average, over-the-road drivers spend 17%–20% of road miles driving empty. Using a digital twin, a company can search across several freight sources to find a load that perfectly matches the deadhead leg without impacting downstream commitments. These additional revenue miles will help drivers to maximize their earnings on the road and carriers to maximize their asset utilization and profitability.
The traditional manual dispatch planning model is becoming increasingly outdated—each planner and fleet manager tasked with overseeing 30 to 40 vehicles. Carriers try to manage this problem by dividing the fleet into manageable chunks, which results in cross-fleet inefficiencies. Such a system isn’t scalable. A digital twin acts as an equalizer for small and mid-sized fleets. It enables carriers to expand by venturing beyond the fixed routes and network they were forced to run out of fear of additional logistical complexity.
A digital twin can also give an organization the transparency and visibility it needs to find and fix inefficiencies. A successful carrier will leverage the technology to learn from the hitches in its operations. While this visibility is beneficial in its own right, it also provides the first step toward a seamless, digitized operation. “Digital revolution” is a buzzword frequently heard at transportation conferences. Yet not too many organizations are dedicated to digitizing their operations past the visibility stage. The end goal should be using decision-support systems to automate key elements of the system, thus freeing up planners from their daily rote tasks to focus on problems that only humans can solve.
Finally incorporating a digital twin can also help trucking companies work toward the broader trend of creating greener supply chains. Because they have lower deadhead and dwell times, trucking companies that have adopted a digital twin can be more attractive to shippers that are looking for more efficient operations that meet their environmental, social, and governance (ESG) goals.
THE FUTURE IS HERE
It is important to note that the benefits described here are not dreams for the future; digital twin technology is already here. In fact, choosing a digital twin can seem daunting because there are already a spectrum of options out there. First and foremost, an organization must ensure that the digital twin it selects aligns with both the goals and the scope of its operation.
Additionally, the ideal digital twin should:
Operate in near real time. A digital twin should be able to refresh as often as the network changes.
Be able to factor in specific customer delivery requirements as well as asset- and operator-specific constraints.
Be computationally efficient and comprehensive as it considers thousands of permutations in milliseconds. The digital twin should be able to reoptimize an entire fleet’s schedule of multi-day routes on the fly.
Before implementing a digital twin, carriers need to make sure that they have robust data management processes in place. Electronic logging devices (ELDs), customers’ tenders, billing, shipments, and so on are already inundating carriers with a glut of data. However, the manual nature of operations in many carriers leads to poor data quality. Carriers will need to invest in data management approaches to improve data quality to support the generation and use of high-fidelity digital twins. Otherwise, the digital twin will not be representative of reality and companies will run into an issue of “garbage in, garbage out.”
REINVENTION AND TRANSFORMATION
While data management is critical, change management through the ranks of dispatch operations is often a harder task. In fact, the largest roadblock carriers face when undergoing a digital transformation is the lack of willingness to change, not the technology itself. Many carriers cling to outmoded planning methods. Planners, used to operating based on well-worn business rules and tribal knowledge, could be wary of the technology and resistant to change. They may need to be assured that, while it is true that every trucking network is uniquely complex, digital twins can be set up to model the intricacies of their specific dispatch operations and drive value to the network. A significant amount of time and resources will need to be expended on change management. Otherwise even though trucking companies may invest in cutting-edge technology, they won't be able to fully capitalize on the added value it can provide.
As the truckload industry works through the current freight cycle, it is important to realize that change is inevitable. Carriers will need to reinvent their operations and invest in technologies to ride through the busts and booms of future freight cycles. Recent global events point to the many ways that wrenches can be thrown into global transportation networks, and the fact that such volatility is here to stay. Digital twins can provide companies with the visibility to navigate such changes. But above all, an operation that uses the digital twin to drive decisions can make customers and drivers happy, and help the carriers keep their heads above water during times such as now.
David Scheffrahn is the North American vice president of sales at Ocado Intelligent Automation, a part of the technology specialist Ocado Group. Although he began his career focusing on robotic solutions for semiconductor, electronics, and automotive manufacturers, Scheffrahn eventually moved on to the logistics sector, where he worked at Rethink Robotics, Seegrid, Plus One Robotics, and Dexterity before joining Ocado in 2023. He holds a degree in mechanical engineering from the University of Texas.
Q: How would you describe the current state of the automation industry?
A: Today, automation is available for nearly every task in the supply chain. Yet we know from industry analysts that only one-fourth of warehouses are “automated.” [The market research firm] Interact Analysis predicts that 27% of warehouses will be automated by 2027.So many warehouse operators still have the opportunity to embrace and benefit from automation.
Whether companies are just getting started with automation and could benefit from swapping out manual carts for automated ones or are looking for an end-to-end omnichannel fulfillment solution, there will be options available.
Q: You’ve worked in the robotics industry for the past 25 years. What changes have you seen in robotic design and applications during that time?
A: Believe it or not, robots pre-date me! I fell in love with robots right out of college. When I graduated in 1994, I was hired by a local robotics company, and one of my early jobs was to program robots to cut circuit boards into the correct shape to fit into cellphone housings. I was hooked for life. Back then, robots did exactly what you programmed them to do, very precisely, over and over.
In the mid-2000s, an explosion of software and sensor-based technologies started to give robots the capability to operate in environments that are much less structured, such as warehouses and fulfillment centers. Nowadays, robots can perform a wide range of tasks and movements, seemingly on the fly. They can interact with the world around them—and even people—because they can safely operate and adapt to changes in the environment.
Q: How are artificial intelligence and machine learning being applied to robotics?
A: Think of a robotic pick arm. Traditionally, it was trained and tested to always pick the same—or very similar—object or item set. Now, when we apply artificial intelligence, vision systems, and sensors to the same robotic arm, it can teach itself to handle new items without previous training or testing. Vision systems and sensors scan shapes and identify items to direct the arm on how to handle fragile products without damaging them or how to grasp an item with a new and different shape.
Q: Automation used to be a major investment. Has it become any easier for smaller companies to get started with automation?
A: A few years ago, automating was a choice. In 2024, the question isn’t whether you should automate, but rather what’s the right automation solution for your operations. Automated solutions can be big or they can be small, but they should always improve warehouse operations and be “right-sized” for the application.
Autonomous mobile robots (AMRs) are some of the most approachable automated solutions available for 3PLs or small and mid-sized warehouses. AMRs can be deployed quickly one at a time or by the dozen. They can integrate seamlessly with existing warehouse systems and infrastructure, and work safely alongside human pickers. Customers we have worked with report that deploying automated carts based on AMRs has doubled their productivity, improved accuracy by 40%, and reduced employee training time by 80%.
Q: What is the next frontier in robotic design and applications?
A: The use of 3D printing is opening up new opportunities in robotic design. I think we’ll see that technique used more because of the resulting benefits.
Robots made via 3D printing are lighter, which, in turn, means the grids used in automated storage and retrieval systems (AS/RS)—like the Ocado Storage & Retrieval System (OSRS)—can be lighter. Lighter grids are easier and quicker to assemble. But more importantly, in Ocado Intelligent Automation’s solution, they can provide 33% more vertical storage capacity within the OSRS than heavier grids. The more cubic density in an AS/RS, the more warehouse operators can conserve footprint, lower real-estate costs, and scale inventory.
Q: How is Ocado Intelligent Automation expanding its offerings for the supply chain industry?
A: Ocado Group has been developing automated technology for more than 20 years. In 2023, it formed Ocado Intelligent Automation (OIA), the division I work in, to bring automation solutions to intralogistics (supply chain activities that take place within a warehouse) and to sectors beyond online grocery, which is where the company got its start.
Online grocery is one of the most demanding e-commerce environments—with needs that are very analogous to the fulfillment and logistics requirements of the health-care, retail, consumer packaged goods, and third-party logistics sectors. I can’t wait to see how these sectors benefit from OIA technology and robotics in the coming years. It’s going to be impressive!
Congestion on U.S. highways is costing the trucking industry big, according to research from the American Transportation Research Institute (ATRI), released today.
The group found that traffic congestion on U.S. highways added $108.8 billion in costs to the trucking industry in 2022, a record high. The information comes from ATRI’s Cost of Congestion study, which is part of the organization’s ongoing highway performance measurement research.
Total hours of congestion fell slightly compared to 2021 due to softening freight market conditions, but the cost of operating a truck increased at a much higher rate, according to the research. As a result, the overall cost of congestion increased by 15% year-over-year—a level equivalent to more than 430,000 commercial truck drivers sitting idle for one work year and an average cost of $7,588 for every registered combination truck.
The analysis also identified metropolitan delays and related impacts, showing that the top 10 most-congested states each experienced added costs of more than $8 billion. That list was led by Texas, at $9.17 billion in added costs; California, at $8.77 billion; and Florida, $8.44 billion. Rounding out the top 10 list were New York, Georgia, New Jersey, Illinois, Pennsylvania, Louisiana, and Tennessee. Combined, the top 10 states account for more than half of the trucking industry’s congestion costs nationwide—52%, according to the research.
The metro areas with the highest congestion costs include New York City, $6.68 billion; Miami, $3.2 billion; and Chicago, $3.14 billion.
ATRI’s analysis also found that the trucking industry wasted more than 6.4 billion gallons of diesel fuel in 2022 due to congestion, resulting in additional fuel costs of $32.1 billion.
ATRI used a combination of data sources, including its truck GPS database and Operational Costs study benchmarks, to calculate the impacts of trucking delays on major U.S. roadways.
There’s a photo from 1971 that John Kent, professor of supply chain management at the University of Arkansas, likes to show. It’s of a shaggy-haired 18-year-old named Glenn Cowan grinning at three-time world table tennis champion Zhuang Zedong, while holding a silk tapestry Zhuang had just given him. Cowan was a member of the U.S. table tennis team who participated in the 1971 World Table Tennis Championships in Nagoya, Japan. Story has it that one morning, he overslept and missed his bus to the tournament and had to hitch a ride with the Chinese national team and met and connected with Zhuang.
Cowan and Zhuang’s interaction led to an invitation for the U.S. team to visit China. At the time, the two countries were just beginning to emerge from a 20-year period of decidedly frosty relations, strict travel bans, and trade restrictions. The highly publicized trip signaled a willingness on both sides to renew relations and launched the term “pingpong diplomacy.”
Kent, who is a senior fellow at the George H. W. Bush Foundation for U.S.-China Relations, believes the photograph is a good reminder that some 50-odd years ago, the economies of the United States and China were not as tightly interwoven as they are today. At the time, the Nixon administration was looking to form closer political and economic ties between the two countries in hopes of reducing chances of future conflict (and to weaken alliances among Communist countries).
The signals coming out of Washington and Beijing are now, of course, much different than they were in the early 1970s. Instead of advocating for better relations, political rhetoric focuses on the need for the U.S. to “decouple” from China. Both Republicans and Democrats have warned that the U.S. economy is too dependent on goods manufactured in China. They see this dependency as a threat to economic strength, American jobs, supply chain resiliency, and national security.
Supply chain professionals, however, know that extricating ourselves from our reliance on Chinese manufacturing is easier said than done. Many pundits push for a “China + 1” strategy, where companies diversify their manufacturing and sourcing options beyond China. But in reality, that “plus one” is often a Chinese company operating in a different country or a non-Chinese manufacturer that is still heavily dependent on material or subcomponents made in China.
This is the problem when supply chain decisions are made on a global scale without input from supply chain professionals. In an article in the Arkansas Democrat-Gazette, Kent argues that, “The discussions on supply chains mainly take place between government officials who typically bring many other competing issues and agendas to the table. Corporate entities—the individuals and companies directly impacted by supply chains—tend to be under-represented in the conversation.”
Kent is a proponent of what he calls “supply chain diplomacy,” where experts from academia and industry from the U.S. and China work collaboratively to create better, more efficient global supply chains. Take, for example, the “Peace Beans” project that Kent is involved with. This project, jointly formed by Zhejiang University and the Bush China Foundation, proposes balancing supply chains by exporting soybeans from Arkansas to tofu producers in China’s Yunnan province, and, in return, importing coffee beans grown in Yunnan to coffee roasters in Arkansas. Kent believes the operation could even use the same transportation equipment.
The benefits of working collaboratively—instead of continuing to build friction in the supply chain through tariffs and adversarial relationships—are numerous, according to Kent and his colleagues. They believe it would be much better if the two major world economies worked together on issues like global inflation, climate change, and artificial intelligence.
And such relations could play a significant role in strengthening world peace, particularly in light of ongoing tensions over Taiwan. Because, as Kent writes, “The 19th-century idea that ‘When goods don’t cross borders, soldiers will’ is as true today as ever. Perhaps more so.”
Hyster-Yale Materials Handling today announced its plans to fulfill the domestic manufacturing requirements of the Build America, Buy America (BABA) Act for certain portions of its lineup of forklift trucks and container handling equipment.
That means the Greenville, North Carolina-based company now plans to expand its existing American manufacturing with a targeted set of high-capacity models, including electric options, that align with the needs of infrastructure projects subject to BABA requirements. The company’s plans include determining the optimal production location in the United States, strategically expanding sourcing agreements to meet local material requirements, and further developing electric power options for high-capacity equipment.
As a part of the 2021 Infrastructure Investment and Jobs Act, the BABA Act aims to increase the use of American-made materials in federally funded infrastructure projects across the U.S., Hyster-Yale says. It was enacted as part of a broader effort to boost domestic manufacturing and economic growth, and mandates that federal dollars allocated to infrastructure – such as roads, bridges, ports and public transit systems – must prioritize materials produced in the USA, including critical items like steel, iron and various construction materials.
Hyster-Yale’s footprint in the U.S. is spread across 10 locations, including three manufacturing facilities.
“Our leadership is fully invested in meeting the needs of businesses that require BABA-compliant material handling solutions,” Tony Salgado, Hyster-Yale’s chief operating officer, said in a release. “We are working to partner with our key domestic suppliers, as well as identifying how best to leverage our own American manufacturing footprint to deliver a competitive solution for our customers and stakeholders. But beyond mere compliance, and in line with the many areas of our business where we are evolving to better support our customers, our commitment remains steadfast. We are dedicated to delivering industry-leading standards in design, durability and performance — qualities that have become synonymous with our brands worldwide and that our customers have come to rely on and expect.”
In a separate move, the U.S. Environmental Protection Agency (EPA) also gave its approval for the state to advance its Heavy-Duty Omnibus Rule, which is crafted to significantly reduce smog-forming nitrogen oxide (NOx) emissions from new heavy-duty, diesel-powered trucks.
Both rules are intended to deliver health benefits to California citizens affected by vehicle pollution, according to the environmental group Earthjustice. If the state gets federal approval for the final steps to become law, the rules mean that cars on the road in California will largely be zero-emissions a generation from now in the 2050s, accounting for the average vehicle lifespan of vehicles with internal combustion engine (ICE) power sold before that 2035 date.
“This might read like checking a bureaucratic box, but EPA’s approval is a critical step forward in protecting our lungs from pollution and our wallets from the expenses of combustion fuels,” Paul Cort, director of Earthjustice’s Right To Zero campaign, said in a release. “The gradual shift in car sales to zero-emissions models will cut smog and household costs while growing California’s clean energy workforce. Cutting truck pollution will help clear our skies of smog. EPA should now approve the remaining authorization requests from California to allow the state to clean its air and protect its residents.”
However, the truck drivers' industry group Owner-Operator Independent Drivers Association (OOIDA) pushed back against the federal decision allowing the Omnibus Low-NOx rule to advance. "The Omnibus Low-NOx waiver for California calls into question the policymaking process under the Biden administration's EPA. Purposefully injecting uncertainty into a $588 billion American industry is bad for our economy and makes no meaningful progress towards purported environmental goals," (OOIDA) President Todd Spencer said in a release. "EPA's credibility outside of radical environmental circles would have been better served by working with regulated industries rather than ramming through last-minute special interest favors. We look forward to working with the Trump administration's EPA in good faith towards achievable environmental outcomes.”
Editor's note:This article was revised on December 18 to add reaction from OOIDA.