π Projects
In this section, you can find several projects of visualization tools, and web applications for supply chain optimization or logistics process improvement.
ABC Analysis & Product Segmentation π

π Topic
Product segmentation refers to the activity of grouping products that have similar characteristics and serve a similar market. It is usually related to marketing (Sales Categories) or manufacturing (Production Processes).
The objective is to understand the sales volumes distribution (fast/slow movers) and demand variability to optimize your production, storage and delivery operations to ensure the best service level by considering:
- The highest contribution to your total volume: ABC Analysis
- The most unstable demand: Demand Variability
I have designed this Streamlit App to provide a tool to Supply Chain Engineers for Product Segmentation, with a focus on retail products, of their portfolio considering the complexity of the demand and the volume's contribution of each item.
π Understand the Theory

π Access the Application
You can access the application here: link
π₯οΈ Source Code
The entire source code with explanations is available in this Github repository: Code.
Improve Warehouse Productivity π¦
Reducing this walking time is the most effective way to increase your DC overall productivity.
π Topic
In a Distribution Center (DC), walking time from one location to another during the picking route can account for 60% to 70% of the operatorβs working time. Reducing this walking time is the most effective way to increase your DC overall productivity.

I have published a series of articles that propose an approach to designing a model to simulate the impact of several picking processes and routing methods to find optimal order picking by using the Single Picker Routing Problem (SPRP) for a two-dimensional warehouse model (axis-x, axis-y).
SPRP is a specific application of the general Traveling Salesman Problem (TSP) answering the question:
βGiven a list of storage locations and the distances between each pair of locations, what is the shortest possible route that visits each storage location and returns to the depot ?β
π Understand the Theory

π₯οΈ Source Code
The entire source code with explanations is available in this Github repository: Code.
Vaccination Centers Availability in Paris using Google Maps Visualization Tool πΊοΈ

π Understand the Theory
A Python Flask Web Application that extracts information from the health authority's official website and creates visuals using Google Maps API.
The application is hosted in Heroku using the free tier plan, you can face a short loading lead time of 5 seconds for your first connection.
π Access the Application
You can access the application here: link
Interactive Visualization using D3.js π
Luxury Brands E-Commerce Sales Matrix

π Access the Visual
You can access the application here: link
Cosmetics Product Sales Sankey Chart

π Access the Visual
You can access the application here: link
Violin Plot Chart for Pareto Analysis

π Access the Visual
You can access the application here: link
Post Offices in France

π Access the Visual
You can access the application here: link
Telegram Bot for Shipment Tracking π

π Topic
Implement a simple, cheap and easy-to-implement solution to track your shipments that
- Does not require additional IT development for your carriers
- Easily integrates into the current transportation processes
- Reduces admin workload for your logistics team
- Does not impact driversβ productivity
- Does not require additional equipment
- Provides visibility, real-time tracking and transparency
How does it work?
Scenario Your shipment has been unloaded in your store. DRIVER wants to send delivery confirmation before leaving for his next destination.\
Step 1: DRIVER opens telegram and starts a discussion with BOT
Step2: DRIVER shares its GPS Location (= Store Location)
Step 3: DRIVER shares a delivery number
Step 4: DRIVER shares a picture of the shipment
Step 5: Your logistics teams receive a shipment confirmation
π Understand the Theory
π₯οΈ Source Code
The entire source code with explanations is available in this Github repository: Code.