Using AI in Transportation to generate CO2 emission reductions

A primer for high-volume process industries that are profit-oriented and want to reduce CO2 emissions??

According to EY, eight of ten supply chain executives are investigating sustainable transportation practices to create CO2 emissions reductions. This is an excellent place to focus because transportation represents 28% of global greenhouse gas emissions. AI in transportation is a major tool for achieving meaningful goals in CO2 emission reductions and cost savings. In particular, we look at ProvisionAI’s impact on high-volume shippers.

Sustainable Freight Management? //Green Logistics

This article focuses on CO2 emission reduction and leaves it to others to take a broader look at other green logistics considerations, such as air pollution, nitrogen oxides (NOx) and particulate matter (PM), and significant infrastructure impact.? (Don’t? forget building and maintaining transportation infrastructure (roads, bridges, airports) also generates CO? emissions.)

Carbon footprint? reduction: a corporate imperative

Companies have created targets for carbon reduction; for example, “By 2050, we will be carbon neutral,” or “Our carbon footprint will be the same as in 1990.”? Transportation managers have started many initiatives; some are generating cost and CO2 emissions reductions.? Here are some examples:

1. Substitute modes—Move to more cost—and carbon-efficient modes where economically for example from truck to intermodal
2. Consolidate shipments. Take many smaller shipments and putting them together for linehaul efficiency
3. Eliminating shipments—for example shipping from a plant directly to the customer
4. Seeking out inexpensive alternate fuels. And no, we are not saying electric trucks (Recall that 25% of US electricity is generated by burning coal). Instead, biodiesel mixes are sustainable and don’t require special expensive equipment.

These are excellent first steps, but they are not getting us to the targets mentioned above. That is where an AI logistics solution set can help.

AI to the Rescue of Sustainable Freight Managementt

AI in transportation can be very effective in reducing CO2 emissions. Three AI logistics solutions have been shown to have a significant impact.

1. Route trucks in real time to reduce mileage driven and avid CO2 emission causing traffic jams
2. Use AutoO2 from ProvisionAi to fill up each vehicle, thus reducing the number of trucks required to move freight?
3. Use LevelLoad from ProvisionAi to smooth the flow of freight and eliminate carrier deadhead miles

Each are explained in depth in the following sections

Route trucks in real time. Consider implementing routing that considers real-time traffic issues. Think “Waze for trucks.” Waste Management has implemented this technology to save time, carbon, and cost.

AI Logistics Solution:? AutoO2 from ProvisionAi to fill up each vehicle

With 91% of trucks underloaded, according to the analysis of weigh-in-motion scale data provided by the Georgia DOT, using AI in transportation load optimization has huge leverage. In high-volume process industries like consumer products or food and beverage, you should consider replenishment and customer freight separately:

• Replenishment freight is a product being moved to supply production lines, resupply customer-facing distribution centers in, in some rare instances, vendor-managed inventory where the supplier determines what should be shipped.? These all have one thing in common: the company has the ability to determine what get shipped.
• Customer freight is where orders are received, and the customer expects what he orders—nothing more, nothing less.

Optimizing replenishment freight by writing better orders using AutoO2

For simplicity, let’s consider replenishing customer-facing distribution centers.? Legacy load-building technology uses simple rules, such as adding pallets until the weight, cube, or pallet limit is reached. Some may understand product stack-ability, but for the most part, it is nothing more than an algebraic calculation.

AutoO2, in contrast, uses a wide range of AI to calculate the minimum number of containers needed and how each one should be loaded. This includes ensuring that the bricks are not placed on top of the eggs and that all the loads are axle-legal and constructed so that they arrive damage-free.?

AutoO2, an AI logistics solution, reduces the number of trucks needed by 5-10%, which reduces CO2 emissions. A recent article, https://www.inboundlogistics.com/articles/provisionai-and-riviana-foods-get-a-load-of-this/, shows that the savings for one plant exceeded $1mm/year.?

In 2023, ProvisionAi’s impact was the elimination of 88,000 truck journeys, saving an incredible $200 million. At that time, we couldn’t calculate carbon savings – – this is now built into the latest version.

Reducing the number of customer shipments

Rather than talk genetically, let’s repeat what Procter & Gamble revealed at an environmental conference.? Their pricing structure is that the customer will receive free freight if they buy a certain number of pounds or cubes. Unfortunately, they recognized that their facilities' picking and loading process was not a repeatable process. That is, it depended on who did the job. An experienced order selector may be able to get everything on a truck, whereas somebody who is a recent hire may leave pallets on the dock—and annoy the customer.?

The opportunity to increase the minimum required for free freight requires a repeatable process—nothing left of the dock. Enter an AI logistics solution that we developed—P & G calls it APAL (AutoPallet //AutoLoader), and it forms the basis of AutoO2. Guiding the picker and around the warehouse, the order selector builds stable case-pick pallets that fit into the jigsaw puzzle that is the truck. P & G can be assured that the shipment will fit, be axle-legal, and will arrive damage-free.

Now that they have a repeatable process, P&G was able to go back to its customers with higher minimums for free freight, eliminating a huge number of shipments annually without reducing the total volume sold.

Eliminating carrier dead-head miles:? ProvisionAI impact with LevelLoad

Carriers drive empty (without cargo) for about 15% of all miles.? Many of these wasteful miles are caused by violently fluctuating demands from shippers, forcing them to reposition equipment over long distances.? Consider the costs a carrier incurs to accommodate 24 replenishment shipments one day and three the next. Cutting this variability in replenishment using the AI logistics solution LevelLoad generates savings for both the shipper and carrier.

LevelLoad analyzes data from the supply planning (Replenishment) system and determines how much product should flow on each lane each day for the next 30 days. This AI-based optimization considers all the network's constraints (such as a full warehouse) and creates a viable supply network plan that eliminates about 60% of the volatility.

The benefits generated by LevelLoad are significant:

• The 60% reaction in volatility generates a significant reduction in total deadhead miles driven.
• A 4% reduction in total deployment freight cost.
• Ability to switch to lower-CO2 emissions forms of transportation, such as switching from truck to intermodal.

AI in transportation can generate major CO? emissions reductions. ProvisionAI’s impact with AI logistics solutions is a significant step towards sustainable freight management and carbon footprint reduction. The ProvisionAi solutions also save money. What more could you want??

https://provisionai.com/