In this episode COO of Ruckit, Diego Larrea paints a picture of what the future for trucking logistics looks like for today and tomorrow. From reducing queues at the plant to automatically scheduling and dispatching when orders are placed, AI is going to make big changes in how construction materials get transported.
Advances in AI made headlines last month when a shipment of butter was sent across the country without human interaction. While this is great and gives some insight into what is possible, we shouldn’t be too worried about Robots taking over the world just yet.
Sure, an autonomous truck delivering 40,000lbs of butter across the country is cool, but there are far more practical and arguably more impactful ways you can start using AI today.
One example is AI assisting dispatchers by giving them the data to make better decisions when ordering trucks. It may seem like a simple math problem but it can get pretty complex when you account for travel time with traffic, paving throughput, waiting and loading times at the plant. Not to mention that these things change throughout day.
Job Superintendents, Foremen and Dispatchers are doing this for 20 jobs each day. It quickly becomes many hours of work that can be done in seconds by a computer.
By scheduling a fleet more accurately, projects can ditch the inflated costs of overbooking or under-booking their jobs.
Another way that AI is being used is to help stagger trucks effectively to avoid delays for the crew and drivers.
Say a paving job starts at 7am, and has a throughput of 250 tons/hr, when should the first truck show up at the plant to get loaded? When should the second truck show up at the plant to get loaded and the next.
Pick a time that’s too early, and you end up having to pay the truck to sit idle at the job-site. Not only are you paying a truck to sit still, if it’s an asphalt project, the material is getting cold which leads to thermal segregation issues and poor quality pavement. Pick a time that’s too late and you end up with the paving crew having to wait for material, this can be exponentially worse for your bottom line.
AI can be used to take historical traffic data, plant-wait times, and paver throughput into account and provide suggested staggered start time for each truck.
And lastly, auto dispatching. If the data is available, AI can see Orders for tomorrow as they are created in the POS and determine fleet size and scheduling. It can then automatically assign drivers and dispatch them to the jobs.
While AI often sounds intimidating, we’re already starting to witness the positive impact on making trucking logistics more efficient and effectively lowering the cost of transporting construction materials. 2020 is going to be a big year for construction tech, and we expect AI to be in the driver’s seat.