Logistics analytics company Savi reveals the positive results its customers see when they place sensors on trucks and cargo to track and trace the goods.
A major logistics provider needed to find a way to ensure that goods were getting to market in an African country. The company discovered that the goods it was shipping were getting to port, but by the time the same goods arrived at their final in-country destination, 50% of them were missing. Closer investigation revealed that the goods were being stolen in transit and then sold on the black market.
"To attack this problem, the company asked us to place sensors on trucks and cargo for purposes of tracking and tracing the goods," said Jim Hayden, vice president of solutions for Savi, a logistics analytics company. "This gave the company visibility of when a truck was driving through high-risk areas, or if a truck was dwelling in a location where it shouldn't be. Truck drivers could also see the sensors on the trucks, so this also acted as a deterrent."
The end result was that the company saw its 50% parts theft rate drop to 4%. "It benefitted everyone," said Hayden. "There was more revenue earned, more taxes paid, and many more satisfied customers."
The oil and gas and other industries operate large projects in remote geographies and can see an immediate benefit in sensor-tracking parts that are shipped over difficult to traverse terrain to their final destinations. By attaching sensors to individual parts that are ultimately assembled into subassemblies and large pieces of equipment at jobsites, they also escape the ravages of thefts and other logistics nightmares that delay shipments and projects.
To affect sensor-based tracking and analytics for goods on the move, Hayden describes a hierarchical communications structure in which sensors and RFID devices on the ground track shipments, and then send track and trace results through a GSM network. This enables companies to see their end-to-end transportation networks at a headquarters thousands of miles away.
"In this way, companies can track their global fleets," said Hayden. "They can ensure trucks are where they are supposed to be, see which vehicles are in use, how many miles the vehicles are traveling, and which vehicles are sitting idle."
The visibility is achieved by attaching sensors to trucks that measure travel miles, and that sense whether or not an engine is warm to determine if the vehicle is in use.
"It's important that we track logistics at this level, because if you're not aware of where all of your assets are or if they are in active use, you're potentially not optimizing your fleet inventory," said Hayden.
It can go even farther than that. In one case, a yard manager told me that a company had forgotten about a truck that had been sitting in the yard for three weeks -- carrying a full load of produce. Needless to say, the goods were spoiled.
"In the pharmaceuticals industry, not having real-time sensor reporting over your network can be equally devastating," said Hayden. "Many medical supplies must be shipped at certain temperatures in secure containers and packages. Sensors attached to these parcels log temperatures inside the container every five minutes, but logging at five minute intervals isn't fully real time -- and there is also a surrounding context that these environmentals must be evaluated in."
Hayden gives the example of medicine that is being shipped in a refrigerator where the refrigerator itself is not failing but the sensor is issuing a temperature alert. "In this situation, analytics can step in to look at the situation in a historical context," he said. "For instance, the refrigeration data can be combined with truck telemetric data such as where the truck is located, whether there is a temperature event, or whether there is a stop -- say at a border where there is a two-hour delay in getting through customs. In this case, the truck's engine might be overheating, also affecting the environmentals of the medicine's refrigeration."
It is this ability to combine different information factors into a composite picture that enables problem solving at greater levels of precision.
"The key to it all is being able to look at a context in real time and to take action," said Hayden. "If a sensor on the back of one of your trucks suddenly alerts you that there is tampering, you can also look at the speed the truck is travelling. Once you see that the truck is moving at 70 miles an hour on a thoroughfare, you can also see that it is likely that the sensor is being triggered by vibration, and not by someone tampering."