BUSINESS OPTIMIZATION OF YARD PROCESSES
Problem
A manufacturing company wanted to optimize its yard processes. They had different systems generating data for yard check-in, check-out, and pallet loading that didn’t add value to the company’s decision-making.
Our challenge as consultants was to use the existing data to optimize the yard process in 36 plants across the globe and generate process changes to decrease truck detention costs.
Solution
Optimization of yard processes in a bottling company using statistical model and data mining techniques:
- A statistical optimization model for optimization of the truck in truck out problem in a yard
- Automated feature selection that mimics the behavior of Minimal Redundancy Maximum Relevance algorithm (implementation of a cost function that rewards information gain and penalizes correlation between features)
Results
Using Data Science & statistical models, the detention cost candidates for all the incoming trucks in 2021 was reduced by 6%, saving 3.4 M dollars for the company.
