The CSS perspective: Smart conveyance and predictive maintenance
Experts from the conveyor and sortation industry share how new technologies built into today’s sophisticated systems help identify maintenance issues before breakdowns can happen.
David Maloney has been a journalist for more than 35 years and is currently the group editorial director for DC Velocity and Supply Chain Quarterly magazines. In this role, he is responsible for the editorial content of both brands of Agile Business Media. Dave joined DC Velocity in April of 2004. Prior to that, he was a senior editor for Modern Materials Handling magazine. Dave also has extensive experience as a broadcast journalist. Before writing for supply chain publications, he was a journalist, television producer and director in Pittsburgh. Dave combines a background of reporting on logistics with his video production experience to bring new opportunities to DC Velocity readers, including web videos highlighting top distribution and logistics facilities, webcasts and other cross-media projects. He continues to live and work in the Pittsburgh area.
Like many technologies, conveyors and sortation systems become more sophisticated with every iteration. Sensors are now built into them to monitor performance so that they can operate more efficiently and economically, while predicting maintenance needs well in advance to allow the work to be done when it’s most convenient.
Group Editorial Director David Maloney recently met with three experts who are all members of MHI’s Conveyor and Sortation Solutions Group (CSS), an industry organization that brings equipment and systems suppliers together with end-users to collaborate and address common challenges and opportunities. What follows are some excerpts from their discussion on how these newer technologies are impacting operations.
Q: One term used to describe some of the intelligence built into today’s conveyors and sorters is smart conveyance. How would you define that for our readers?
Doug Schuchart – Beckhoff: When I think of the term smart conveyance, I think of it referring to multicarrier transport systems that use linear or planar motor technology. Linear track systems have the coils of a motor in a track. In this technology, you’re energizing those coils to move magnetic carriers around in a material handling system.
Planar motor technology is actually very similar, but those coils are in a base of flat tiles, and then the magnetic mover is levitating and has 6 degrees of motion that can move with virtual tracks around the base.
And then there are motorized driven roller conveyors, or MDR, that have motors within a roller to drive the conveying surface. What makes these technologies smart is that we’re able to pull a lot of data through those systems back to the central controller.
Ty Keller – FMH Conveyors: There are several types of equipment that complement the components Doug mentioned, that I would consider part of a smart conveyance system: equipment used for scanning, labeling, measuring, machine learning, or performing any number of actions to collect data for the central controller to turn into inputs for the smart conveyor. Then the smart conveyor takes the product where it needs to go.
Q: Do the same technologies associated with smart conveyance also apply to sortation systems?
Doug Schuchart– Beckhoff: Yes, these technologies can also apply to sortation. For example, what makes planar motor technologies really compelling is that they can replace multiple pieces of equipment in a fulfillment operation. So when we’re looking at material handling for conveyance, sortation, or accumulation—all of those can be handled with planar motor technology.
All of these technologies that we’re talking about are generally controlled with a fieldbus that can capture data from the system and then send the data to the centralized control system to be analyzed. The data can also be sent to the cloud to do further analysis and then make some decisions. And maybe you’re applying some artificial intelligence (AI) to the system for predictive maintenance or better optimization of paths, for instance. All of those would be ways to make the system smarter.
Q: Speaking of maintenance, can you give some examples of how these technologies can help prevent downtime?
Ty Keller – FMH Conveyors: It allows the user to monitor the usage of equipment, to know the exact number of hours in operation and the environment that the conveyor is working in. It can also read things like vibration, temperature, and pressure to help predict when the equipment is going to have issues. If we’re maintaining it appropriately, the equipment will last longer.
This information can also be used to determine preventative maintenance contracts with outside third parties. With the right technology, those contracts can be based on when it is best to perform preventative maintenance instead of a regular maintenance schedule. That’s obviously a more attractive return on investment for the end-user.
Brandon Willard – Banner: There are really four types of maintenance in my mind. There’s reactive maintenance, which is something is broken and we have to go and fix it—the motor is down and that critical conveyance is creating an issue for us.
There’s preventative maintenance, which is scheduled, regularly performed maintenance to reduce failures and is a great step up from just reactive maintenance.
The next step is predictive maintenance, which is using sensors and software to be able to predict failure. It is collecting data to be able to understand when a failure is about to take place so that you can act before it creates downtime and expense.
And then there is one beyond it, which is prescriptive maintenance. This is taking that data and using machine learning to be able to predict failures and identify solutions. If you can take that data that you get from predictive maintenance and use it to service the equipment optimally, then you’re able to extend the life of this type of conveyance. That’s where the value lies.
Q: Can you provide an example of how that might work using smart conveying systems and creating a prescriptive maintenance program?
Brandon Willard – Banner: We could look at vibration data, temperature data, pressure data, and how much electrical current is being drawn. We first want to baseline what that machinery looks like when it’s operating functionally. Then when we see a sharp curve compared to the baseline, we know when a product is about to fail. Sensors on bearings may detect vibration in multiple directions, while other sensors show increases in temperature resulting from rubbing or tearing on a belt or something else that is going wrong. Those vibrations or higher temperatures usually start to spike pretty quickly.
Then applying machine learning, the systems can give a warning threshold. For example, the belt may be rubbing on one side. All we need to do is re-center the belt. Nothing really has to be replaced, but the alerts allow you to check before the belt tears all the way and you’re not able to re-center it. Different warning levels and alerts allow you to protect your assets more efficiently.
Doug Schuchart– Beckhoff: I think we’re talking about a lot of different benefits, such as a reduction of manpower in the facility. We’re also talking about improving reliability and quality of a system. All of those things provide different advantages collectively. We talk to customers about that whole ROI and why you would want to invest in a more automated smart system as opposed to some traditional systems that don’t have that technology.
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.
A Canadian startup that provides AI-powered logistics solutions has gained $5.5 million in seed funding to support its concept of creating a digital platform for global trade, according to Toronto-based Starboard.
The round was led by Eclipse, with participation from previous backers Garuda Ventures and Everywhere Ventures. The firm says it will use its new backing to expand its engineering team in Toronto and accelerate its AI-driven product development to simplify supply chain complexities.
According to Starboard, the logistics industry is under immense pressure to adapt to the growing complexity of global trade, which has hit recent hurdles such as the strike at U.S. east and gulf coast ports. That situation calls for innovative solutions to streamline operations and reduce costs for operators.
As a potential solution, Starboard offers its flagship product, which it defines as an AI-based transportation management system (TMS) and rate management system that helps mid-sized freight forwarders operate more efficiently and win more business. More broadly, Starboard says it is building the virtual infrastructure for global trade, allowing freight companies to leverage AI and machine learning to optimize operations such as processing shipments in real time, reconciling invoices, and following up on payments.
"This investment is a pivotal step in our mission to unlock the power of AI for our customers," said Sumeet Trehan, Co-Founder and CEO of Starboard. "Global trade has long been plagued by inefficiencies that drive up costs and reduce competitiveness. Our platform is designed to empower SMB freight forwarders—the backbone of more than $20 trillion in global trade and $1 trillion in logistics spend—with the tools they need to thrive in this complex ecosystem."