The data-driven lift truck

In the not so distant past, manufacturers and users of automated materials handling equipment, like conveyors and sorters, focused on the movement of goods through a facility. They wanted to know how quickly a conveyor could move a carton from one point to another or how many cartons an hour a sorter could sort. They called it “speeds and feeds.”

Moving a carton or item as efficiently as possible through a facility is, of course, still critical. But just as important, or maybe even more so, is access to real-time information about the movement of those goods. It’s not enough to know that a carton is on a conveyor; it’s just as important to know where it’s located on the conveyor, when it will get to the next stop in the process, and how long before it’s packaged and on the back of a truck. In short, we’re talking about data-driven warehouses.

While less heralded than the automation information revolution, something similar is happening with lift trucks. Truth be told, lift truck manufacturers discovered the value in harnessing the data coming off their trucks before the automated systems providers. But, the user community was slow to recognize the value in all that data. Not so today. While this is still a market driven by early adopters, end users are beginning to catch on. “We’ve had two straight years of triple-digit growth in the number of customers using telematics data to manage their fleets,” says Steven LaFevers, director of aftermarket solutions for Yale Materials Handling Corp.

Driving that shift, according to LaFevers, is that lift truck users, who once focused on the acquisition and maintenance costs of their fleets, are realizing that the biggest cost of ownership is a result of operator productivity, safety and product damage. No one argues that a decrease in maintenance costs is a positive thing, but “just a 2% increase in productivity, which is just one of the things we monitor, can have a major impact on the bottom line,” he says.

That shift in focus has coincided with better reporting tools that deliver the data being collected from the lift truck in an easily digestible format. “As an industry, we’re figuring out how to harness the data and deliver it to a DC manager in a way that allows them to make fact-based recommendations to process change that is not disruptive to their organizations,” says John Rosenberger, manager of the iWarehouse Gateway and Global Telematics for Raymond.

Finally, there is the impact of Big Data, which is beginning to influence all aspects of the materials handling industry. “My 88-year-old mom has heard of Big Data,” notes Frank Cavallaro, chief executive officer of TotalTrax. “Today, we have the ability to aggregate, analyze, sort and present data based on the needs of various end users and their skill sets. That is something we couldn’t do well before.” Cavallaro adds that given the number of systems optimizing automated materials handling systems and even over-the-road productivity, the low-hanging fruit has been picked. “Labor and machinery is where the next opportunity to make improvements lies,” he says.

Making the shift
In some respects, none of this is new. Four years ago, Modern visited a major manufacturer in Ohio that had recently acquired a new fleet of lift trucks equipped with telematics and fleet management software. During the interview, the fleet managers proudly ticked off the benefits of the technology: The functionality could improve productivity, reduce product damage, identify operators in need of training and right size the fleet—the same benefits suppliers and third-party software providers talk about today.

What’s different is this: While the fleet managers at the manufacturer were sold on the potential benefits, nearly a year into using the new trucks they had yet to start using the software to reap those rewards. It was on the shelf, like an unopened can of paint and rollers still in their sleeves. Today, as LaFevers and others point out, some early adopters are starting to realize benefits. While that may be less than a third of new trucks sold today, “based on the rate of adoption, by 2020 we could get to the point where you’ll see 60% to 80% of the market adopting telematics,” he says.

Several events have come together to make this shift. They include:

• Cheap computing: As with laptops and smart phones, the cost of sensors and computing power have come down to a point that makes data collection accessible. Cheap memory, for instance, allows trucks to collect more information than ever, including things like whether the voltage from the battery is fluctuating or an air filter is dirty.
• Better communication: Not only are more sensors than ever installed on a lift truck, those sensors can communicate wirelessly with the vehicle’s computer system. “In the past, we had to directly wire a sensor to a relay to get the data and that had to constantly be touched and tweaked,” says Rosenberger. “Today, the sensors can communicate wirelessly, and the lift truck itself can be programmed to report back anomalies as part of its normal operation. Every second that the truck is on, it can report back things like the speed of the vehicle, the temperature of the engine or RPMs.”
• The cloud: The cloud has made data collection and analysis across a network ubiquitous. “The cloud allows us to aggregate information within a facility or across multiple facilities for a customer,” says Jonah Teeter-Balin, director of product marketing for AeroVironment, which collects the data generated by its brand of battery chargers. “That allows you to make decisions within the four walls of a facility, or you can take steps like standardizing practices from a facility that stands out across your organization.” Those network decisions could not be made easily when data was kept within the four walls of the facility in which it was collected.
• Better analytics: Not only are we collecting more information, the tools for analyzing that data have improved. For instance, after years of saving data, I.D. Systems now has benchmark information that allows it to compare the performance of a facility or network of facilities against the benchmark for an industry. “I called on one very large company for years that insisted it had 98% utilization of its fleet and we couldn’t prove it wasn’t true because we didn’t have the data,” says CEO Ken Ehrman. “With better tools, we were able to show them that in the aggregate their fleet utilization was actually 45%. More importantly, we were able to show them that they were lagging their industry peers on a percentile basis. That was important because they did not want to lag their peers.” Similarly, LaFevers says that Yale is collecting data on thousands of assets every day.
• Improved presentations: Last, but certainly not least, information is available in real time, if required, and in a format that makes sense to a busy fleet manager. “When we first started out, we delivered information in very complicated spreadsheets and then asked distribution people to digest it and make decisions,” says TotalTrax’s Cavallaro. “Now we present it in real time and in a dashboard that allows a shift manager or facility manager to affect change immediately if they see something happening.”

Data everywhere
Just as there has been an evolution in the underlying technology, there has been an evolution in the type of data being collected and the types of companies capturing data. “Early on, we collected basic information such as motion and lift data,” says Raymond’s Rosenberger. “Now, trucks are generating their own fault codes. It’s all part of the natural operation of the onboard computer.”

As an example, Yale is collecting information from 122 different data points from its trucks. That includes five key readers specifically on productivity, such as when the lift truck is on, when it is lifting, when the transmission is engaged and whether the tires are spinning. “We had an instance where a particular truck hadn’t communicated for six weeks,” LaFevers says. “When we looked into it, it turned out it had been cannibalized for parts.”

A second important evolution is the introduction of both Wi-Fi and cellular cameras into systems, says Terry Wickman, president of Keytroller. The camera, for instance, captures and isolates 20 seconds before and 20 seconds after a speeding event or an accident. “The video can be used for accountability and training,” Wickman says. Seeing footage from an operator’s point of view might also identify unsafe operating conditions that can lead to changes in the layout of a plant or distribution center. As an example, a DC in the humid south may have wet floors around the same time every day because of afternoon showers. Lastly, camera systems can be used as a quality control tool. For example, the system can be used to take a video of an operator loading a trailer in the event that there’s a damage claim later.

End users can use the data in a variety of ways, and it is typically situational based. One use case is to validate the ROI of a new process or technology. “Let’s say you put an RFID reader on a lift truck so that an operator doesn’t have to get on and off the truck to scan the pallet,” says I.D. Systems’ Ehrman. “Through telematics and analytics tools, you can look at productivity over three to six months and validate whether there has been an improvement. The ROI becomes much clearer.”

Customers have also used lift truck data to identify facilities that are out-performing others in their network, or operators within a facility who are out-performing the rest of the crew. That, in turn, gives managers the opportunity to look for best practices that can be shared with other operators or other facilities. “One of our customers brought in telematics to prove that two of their 50 operators were outperforming the rest,” says LaFevers. “They were 50% more productive and they wanted to model what they were doing with other operators.”

Meanwhile, dealerships are monitoring the fault codes that come off trucks to schedule maintenance. “With cellular communication sending information back to a dealership, they no longer have to go into a facility every week to read the codes on the truck,” says Rosenberger. “And, if a dealership or technician does notice something, they can call the warehouse and schedule service before a truck dies in the aisle.” He adds that all 21 of Raymond’s dealerships now have that capability.

End users analyze the battery management data collected by AeroVironment to ensure batteries are being properly watered and equalized, which can extend the life of a battery. In turn, that can lend itself to fleet management decisions. “If your batteries are lasting six months longer as a result of good battery management practices, you may be able to operate that facility with one fewer truck,” says Teeter-Balin. “If you can deploy those same practices across your organization, you can extend the savings.”

Given all of the data being collected, it could be easy to be overwhelmed and not know where to start. Yale’s LaFevers urges customers to focus their efforts on two things in the warehouse that if changed could make a difference to their overall performance, and then make those seamless. “If I was a foreman who managed operators, I’d want to know if there were any safety alerts, what was the overall productivity of the fleet,” he says. “I’d then look at the those two things, and set targets and practices that would drive improved performance. Once I made a difference on those two critical areas, I would start look at my dashboards and data to find other areas of improvement.”

What’s next
Right now, much of this information exists in isolation, meaning that it is collected to improve the operations and performance of lift trucks, batteries and operators. The next iteration is to integrate the information with other systems.

LaFevers, for instance, imagines that in the future, machines will be able to communicate directly with a conveyor system or a warehouse management system (WMS).

TotalTrax’s Cavallaro says we are already seeing the emergence of a technology platform that can bring together and analyze all of the disparate systems in use now—what the truck is doing, what the operator is doing, what the battery is doing—to get a more unified picture that allows end users to make links.

The last step could be the integration of other systems and technologies to optimize end-to-end processes, such as using data collected from labor management systems, lift truck fleet management systems and even that data being collected from the truckers over the road to make changes across the supply chain. “We still operate in silos today,” says Raymond’s Rosenberger. “But there are Internet of Things initiatives in Europe that would allow us to communicate and complement one another.”

A true data-driven supply chain like that may be some off in the future, but not as far off as it sounds. “It’s moving slowly, but it’s moving,” says Rosenberger. “But remember, it will still take human intervention to ask the right questions of the software.”