Managing heavy equipment: Making sense of equipment operation data
Construction, it is frequently observed, has not enjoyed the technology-driven productivity gains that have occurred in manufacturing over the past two decades. A partial explanation for this is that manufacturing equipment operates in a static environment, making it relatively easy to manage, while construction machines – trucks, earth moving equipment, cranes, etc. – are constantly on the move.
New technology is helping to close this equipment management gap. Thanks to a trend called the Internet of Things (IoT), construction equipment is now being equipped with a plethora of sensing devices, and through the use of telematics, the resulting data can be gathered and transmitted to a central repository for computational purposes.
“The challenge here is to have better analytics,” says Denver-based John Naughton, business area manager for Machine Control at Trimble, a global provider of electronic positioning solutions. “We need to present information in usable ways for operators, fleet operators, or construction management teams – ways that haven’t been there in the past.”
User requirements vary considerably. “Each company looks at their data differently,” says Chicago-based Scott Sutarik, associate vice-president of Commercial Vehicle Solutions at global telematics provider GeoTab. “One might be interested in safety. Another might be interested in utilization. Another might be interested in compliance.”
Sutarik notes that due to government mandated emissions for diesel engines, current equipment is required to have sensing capabilities for monitoring environmental performance. In order to accomplish this, OEMs include a variety of electronic modules that control the various systems on the vehicle. These modules record rich information, including idle time, fuel burn, and hours used. By utilizing this information, fleets can also reduce emissions and associated costs, helping them better manage their day to day business.
Gathering the data manually, however, can be time-consuming and unreliable. By installing a telematics device on each vehicle, contractors can automate the data collection process.
Maximizing uptime is another basic requirement. Software can use metrics, such as engine hours, fuel consumption, engine fault codes and temperatures, to predict potential failures for preventive maintenance purposes, or detect patterns that could shorten the lifespan of the equipment.
“Data scientists can utilize techniques like machine learning,” Sutarik says. “This allows firms to look at large swaths of data and typical failure patterns, and then leverage that information to avoid instances where failures are most likely.”
One of the keys on the maintenance side is the ability to aggregate data from different OEMs. “Contractors have mixed fleets, and each OEM has its own equipment management system,” Naughton says. “In the past people had to log into multiple systems. Today, you can manage maintenance on an overall scale so you can do more accurate planning for various levels of maintenance. This leads to more uptime, better predictability, and better profitability.”
When it comes to safety, vehicle data tells owners not only how the equipment is operating, but how it is being operated. Accelerometer data can detect driving behaviours such as hard cornering or sudden braking. Images from cameras and backup sensors can warn of hazards. Interfaces that require operators to “badge in” can prevent untrained workers from operating a piece of dangerous equipment. When accidents do occur, post mortem data can be analyzed to help prevent future incidents.
In complex tasks such as site grading, management technology can be applied to help workers operate equipment more effectively. “We have point solutions that help a single operator do a better job,” Naughton says. “That ties into what we call the connected site, which allows you to have an overall view that lets you optimize and manage that site.”
For example, the work of multiple machines and operators can be coordinated using a virtual model. “We can send a design or terrain model to all of the grading and excavating machines out there,” Naughton says. “Then each operator has an indication of where to dig and how to grade. We’ve automated elements of operating the machine. With a dozer, for example, we use high-accuracy GPS to drive hydraulics on [the] right and left side of the blade.”
The benefits that equipment management technology can provide – optimal equipment operation and total visibility of all costs and risks – are compelling, but depend on overcoming the same technology challenges that contractors have struggled with for over a decade. Bringing data into a common platform, ensuring data integrity, and keeping all system components operating synergistically are the same hurdles that contractors face with BIM systems and other categories of advanced construction software. The potential advantages of proactive equipment management may be just one more tipping point motivating construction firms to overcome these barriers.
Jacob Stoller is principal of StollerStrategies. Please send comments to firstname.lastname@example.org.
This article first appeared in the October 2018 issue of On-Site. You can check out the full issue here.