🎯 Executive Summary
Optimizing the placement and retrieval of steel coils in the warehouse based on the production plan and orders — reducing transfer time and increasing crane productivity.
💰 Estimated ROI: 15–25% less handling time, higher warehouse throughput without physical expansion, lower crane energy cost.
🏭 Target Industries: Steel, metals, heavy industries
⏱ Implementation Time: 8‑week pilot, 4–5‑month rollout
📊 Key KPIs: Average coil‑access time, crane productivity, warehouse output rate per day
📋 Technical Project Details
This project is designed to manage and optimize warehouse space for storing steel coils, where the main challenge is minimizing space usage and precise scheduling for the inbound and outbound flow of goods. The system must account for the placement constraints of coils with diverse properties such as weight, diameter and thickness, and manage unexpected changes in customer orders. By leveraging deep optimization algorithms (DRL), warehousing operations are planned automatically to increase response speed and reduce human error. This approach is useful in manufacturing and warehousing to improve overall efficiency and can significantly lower operating costs.
In the development stage, the focus was on modeling the physical constraints and dynamics of the warehouse so the algorithms can simulate real scenarios. The system not only optimizes storage space but, by predicting order changes, also provides dynamic planning — a feature that increases flexibility. Data security is ensured through access control to protect sensitive warehouse information. The project has been delivered and its results show reduced operation time and higher productivity, which can help avoid unnecessary stoppages.
Beyond the technical aspects, the system emphasizes integration with existing processes to improve the workflow without disruption. Using intelligent dashboards, it produces analytical reports that show the warehouse status in real time. This shift from manual to intelligent management not only increases accuracy but also manages resources more intelligently.
Ultimately, the goal of this project is to create a warehouse‑optimization tool that helps industries manage inventory. This innovation can be a model for similar use cases in logistics and manufacturing and improve overall efficiency. With a successful rollout, this system is expected to become a standard in industrial‑warehouse management.