Sustainable Logistics

We conducted a case study evaluating a distribution center in Mexico. Most systems take into consideration delivery date, weight of the products, real-time traffic, and dynamic routing, but they do not include topography.

We did a study to see how much more efficient we could make the delivery routes by including topography and comparing multiple solutions.

The organization that we chose had the following metrics:

  • 21 medium-duty and 22 heavy-duty trucks
  • ~8,000 customers
  • ~6,500,000 km traveled yearly
  • ~55 million of tons delivered yearly
  • ~300,000 Lt of diesel consumed yearly
  • ~4,000,000 MXN (~380,000 USD) spent on fuel yearly
Green Logistics
SolutionDistance (Km)Fuel (Liters)
VRP/PRP51.137.08 [+4.74%]
TPRP53.1 [+3.8%]36.30 [+2.54%]
VRP+/PRP+52.05 [+1.75%]36.08 [+1.92%]
TPRP+53.63 [+4.8%]35.40 L

Approximate savings of 5% in Fuel Consumption in each route!

That is huge savings in the course of a year for a company.

From August 2018 to September 2019 we conducted a study to see if having the flexibility to delay some deliveries to  be able to consolidate packages would reduce the amount of emissions and the cost of fuel.

Consolidation

From August 2018 to September 2019 we conducted a study to see if having the flexibility to delay some deliveries to  be able to consolidate packages would reduce the amount of emissions and the cost of fuel.

Image

We then conducted a pilot which covered:

  • 34 Business Days
  • ~25,000 records
  • ~700 zip codes
  • Delivery Window Extension of up to 4 business days
Consolidation

The results were quite surprising. Making these changes produced a fuel reduction of 39%!

Using Geospatial Analysis, we define the right freight vehicle, and what to do with the old fleet. We partnered with Coppel to review the process they are currently using and evaluate how to best reconfigure their freight trucks to be the most efficient as possible. We evaluated:

  • ~ 1300 Retail Stores in Mexico
  • 19 Regional DC’s
  • ~ 1200 last mile delivery vehicles
  • 6.3M delivery attemps
  • 36M Kilometers
  • 6.3M of liters of Fuel
Model estimation

Ten trucks exchange pilot (Oct 2018). Model estimation ~2.6% of savings on fuel consumption

experiment results

The experiment results showed ~8% savings in fuel efficiency!

report

Note that the older vehicle (vehicle 1) showed a 15% better performance than the newer vehicle (vehicle 2), that is, 0.50 vs 0.59 when assigned to cluster B.

The newer vehicle performs ~20% better in a region that is more congested, and with shorter distance between stops!

The results were quite surprising. Making these changes produced a fuel reduction of 39%!

The Dynamic Lot-Sizing (DLS) Assumptions:

Order quantity that minimizes the total holding costs and ordering costs

  • Demand is known but varying
  • Lead time is known and constant
  • Costs are known but varying
  • Shortages are allowed*
  • Orders are delivered in full

Loss of goodwill and future revenues are difficult to ascertain. This explains why service level constraints are more popular in practice than shortage costs.

The negative consequences of not satisfying customer demands on time may also involve increased emissions.

Ten trucks exchange pilot (Oct 2018). Model estimation ~2.6% of savings on fuel consumption

The first question you need to ask is actually what is your purpose for emissions accounting? If you are looking to just get an aggregate emissions number then any accounting method will do. But how accurate do you want the information to be, and what are you looking to do with this information? If you want to be able to see hot spots and make changes at the shipment level then you need a high level of accuracy, and you need real data. When you compare the different methods, GHG protocol has a very high inaccuracy rate, whereas the GLEC has a low inaccuracy for the overall aggregated emissions accounting. But you need real data to be able to make real changes for your organization.

If you don’t know where you are going, any path can take you there.

Transportation
Transportation

Coming soon