Update README.md

README.md

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-# 🏭 SteelAI Module #2 — Blast Furnace & EAF Data Intelligence Explorer
+# SteelAI Module #2 — Blast Furnace & EAF Data Intelligence Explorer
 
 **Part of the TenderMatcher.Tech AI & Digital Intelligence for Metallurgy Suite**
 
@@ -23,7 +23,7 @@ Ready-to-deploy **Streamlit + SHAP application** for **energy and yield optimiza
 
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-## 🎯 Objective
+## Objective
 
 Predict and optimize key furnace variables such as:
 
@@ -36,30 +36,30 @@ This module simulates a **complete furnace data intelligence environment** with
 
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-## ⚙️ Core Features
+## Core Features
 
-- 🧠 Synthetic EAF dataset generator (3,000+ records)
-- 🧮 Derived physical proxies:
+-  Synthetic EAF dataset generator (3,000+ records)
+-  Derived physical proxies:
   - `carbon_proxy`, `oxygen_utilization`, `slag_foaming_index`
-- 🔍 PCA and clustering for operating modes
-- ⚙️ Ensemble regression (Linear, RF, GB, ExtraTrees)
-- 💡 SHAP explainability for model transparency
-- 📊 Business framing & annotated bibliography for metallurgy ML
-- 🧾 Fully local synthetic data generation (no external upload needed)
+-  PCA and clustering for operating modes
+-  Ensemble regression (Linear, RF, GB, ExtraTrees)
+-  SHAP explainability for model transparency
+-  Business framing & annotated bibliography for metallurgy ML
+-  Fully local synthetic data generation (no external upload needed)
 
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-## 🧮 Use Case Alignment (SteelAI Framework)
+##  Use Case Alignment (SteelAI Framework)
 
 | # | Use Case | Alignment | Description |
 |---|-----------|------------|--------------|
-| **2** | Blast Furnace / EAF Data Intelligence | ✅ **Primary (100%)** | Furnace temperature, gas chemistry, and power-density modeling for yield & energy optimization |
-| 7 | AI-Driven Alloy Design Tool | ⚙️ Partial | Shares compositional features (`chemical_C`, `chemical_Mn`, etc.) |
-| 8 | Predictive Maintenance Framework | ⚙️ Partial | Includes rolling, lag, and vibration signals for maintenance AI |
+| **2** | Blast Furnace / EAF Data Intelligence |  **Primary (100%)** | Furnace temperature, gas chemistry, and power-density modeling for yield & energy optimization |
+| 7 | AI-Driven Alloy Design Tool |  Partial | Shares compositional features (`chemical_C`, `chemical_Mn`, etc.) |
+| 8 | Predictive Maintenance Framework |  Partial | Includes rolling, lag, and vibration signals for maintenance AI |
 
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-## 💡 Example Targets
+##  Example Targets
 
 - Predict **`furnace_temp`** from operational data  
 - Analyze **feature importance** with SHAP plots  
@@ -69,7 +69,7 @@ This module simulates a **complete furnace data intelligence environment** with
 
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-## 🧰 How to Run Locally
+##  How to Run Locally
 
 ```bash
 pip install -r requirements.txt
@@ -80,7 +80,7 @@ Then open the local URL shown in your terminal (typically http://localhost:8501)
 
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-## 🌐 Deploy on Hugging Face
+##  Deploy on Hugging Face
 
 1. Create a Space → choose **SDK: Streamlit**
 2. Upload:
@@ -97,7 +97,7 @@ https://huggingface.co/spaces/singhn9/SteelAI_Module2_EAF_Intelligence_Explorer
 
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-## 🏭 Business Value Snapshot
+##  Business Value Snapshot
 
 | Dimension | Improvement | Impact |
 |------------|-------------|---------|
@@ -109,7 +109,7 @@ https://huggingface.co/spaces/singhn9/SteelAI_Module2_EAF_Intelligence_Explorer
 
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-## 🤖 Generative AI & Industrial Innovation
+##  Generative AI & Industrial Innovation
 
 Beyond process modeling, **TenderMatcher.Tech** extends AI into Generative domains:
 
@@ -119,7 +119,7 @@ Beyond process modeling, **TenderMatcher.Tech** extends AI into Generative domai
 
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-## 🔗 AI–ServiceNow Integration Mapping
+##  AI–ServiceNow Integration Mapping
 
 | # | AI Module | ServiceNow Integration | Business Value |
 |---|------------|------------------------|----------------|
@@ -134,19 +134,19 @@ Beyond process modeling, **TenderMatcher.Tech** extends AI into Generative domai
 
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-## 👨‍🔬 About Naval Singh
+##  About Naval Singh
 
 **Naval Singh** — Digital Transformation Advisor  
 Specializing in AI, analytics, and industrial systems.  
 Focused on production-grade decision systems for metallurgy, mining & manufacturing.
 
-📧 **singhn9@gmail.com**  
-🔗 [LinkedIn](https://linkedin.com/in/navalsingh9)  
-📍 **Rourkela, India**
+ **singhn9@gmail.com**  
+ [LinkedIn](https://linkedin.com/in/navalsingh9)  
+ **Rourkela, India**
 
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-## 🌍 Why Rourkela Matters
+##  Why Rourkela Matters
 
 Rourkela — India’s steel and metallurgy hub — provides the perfect ecosystem for AI pilot collaborations among academia, consulting, and industry.
 
@@ -155,3 +155,29 @@ Rourkela — India’s steel and metallurgy hub — provides the perfect ecosyst
 © **TenderMatcher.Tech** — *AI & Digital Intelligence for Metallurgy*  
 **[Read More](https://tendermatcher.tech/ai-metallurgy)**
 
+#  SteelAI — EAF Intelligence Explorer (MODEX)
+
+An industrial-grade AI demonstrator for Electric Arc Furnace (EAF) analytics at
+**Steel Authority of India Limited (MODEX)** — combining synthetic metallurgical datasets,
+automated feature engineering, and AutoML ensembles with SHAP explainability.
+
+###  Key Highlights
+- Generates full synthetic EAF datasets (~3000 rows × 200+ features)
+- Supports ensemble AutoML across RandomForest, XGBoost, LightGBM, CatBoost, etc.
+- Performs Optuna-based hyperparameter tuning per family
+- Uses meta-stacking (Ridge) and SHAP explainability
+- Includes “Recommended Target Variables” and Business Impact framing
+- Features annotated bibliography with direct research paper links
+
+###  Logging & Reproducibility
+- All generated CSVs, JSONs, and logs are stored under `./logs/`
+- Each session in Hugging Face ephemeral environment appends new timestamps
+- Users can download artifacts directly via the **Download Saved Files** tab
+
+ *Ephemeral note*: Data and models are cleared when the Space rebuilds,  
+but logs persist for the current runtime session.
+
+---
+
+###  Credits
+Developed as part of SteelAI MODEX initiative for AI-driven metallurgy R&D.