Predicting when rented equipment will be returned
Read more at
https://modulai.io/case/logistics-optimization-of-equipment-in-the-construction-sector/
As one of the largest rental equipment providers in the Nordics and suppliers to thousands of construction sites, this client needed a system capable of predicting when lent out equipment was expected to be returned.
Background
The goal was to optimize their vast logistics chain by minimizing unnecessary transport between their local shops and main warehouses.
Solution
In close collaboration with the company’s data scientists, we processed and analyzed their large database of customers, construction projects, and past rentals. As input, the model takes detailed characteristics of the equipment, the customers, geography, and season into account to estimate when equipment will be returned. We developed and assessed several regression and classification approaches.
Tools/Tech
The system was delivered as a Python service to be run on their internal infrastructure and integrated with the ERP system.
Transportation & Logistics
Operations
More Efficient, Smarter Product or Service
Shaper
Optimization
Clustering