Refactor and enhance CalMiner application

- Updated README.md to reflect new features and usage instructions.
- Removed deprecated Dashboard.html component and integrated dashboard functionality directly into the main application.
- Revised architecture documentation for clarity and added module map and request flow diagrams.
- Enhanced maintenance model to include equipment association and cost tracking.
- Updated requirements.txt to include new dependencies (httpx, pandas, numpy).
- Improved consumption, maintenance, production, and reporting routes with better validation and response handling.
- Added unit tests for maintenance and production routes, ensuring proper CRUD operations and validation.
- Enhanced reporting service to calculate and return detailed summary statistics.
- Redesigned Dashboard.html for improved user experience and integrated Chart.js for visualizing simulation results.

docs/architecture_overview.md

@@ -0,0 +1,44 @@
+# Architecture Overview
+
+This overview complements `docs/architecture.md` with a high-level map of CalMiner's module layout and request flow.
+
+## Module Map
+
+- `main.py`: FastAPI entry point bootstrapping routers and middleware.
+- `models/`: SQLAlchemy declarative models for all database tables. Key modules:
+  - `scenario.py`: central scenario entity with relationships to cost, consumption, production, equipment, maintenance, and simulation results.
+  - `capex.py`, `opex.py`: financial expenditures tied to scenarios.
+  - `consumption.py`, `production_output.py`: operational data tables.
+  - `equipment.py`, `maintenance.py`: asset management models.
+- `routes/`: REST endpoints grouped by domain (scenarios, parameters, costs, consumption, production, equipment, maintenance, reporting, simulations, UI).
+- `services/`: business logic abstractions. `reporting.py` supplies summary statistics; `simulation.py` hosts the Monte Carlo extension point.
+- `middleware/validation.py`: request JSON validation prior to hitting routers.
+- `templates/`: Jinja2 templates for UI (scenario form, parameter input, dashboard).
+
+## Request Flow
+
+```mermaid
+graph TD
+    A[Browser / API Client] -->|HTTP| B[FastAPI Router]
+    B --> C[Dependency Injection]
+    C --> D[SQLAlchemy Session]
+    B --> E[Service Layer]
+    E --> D
+    E --> F[Reporting / Simulation Logic]
+    D --> G[PostgreSQL]
+    F --> H[Summary Response]
+    G --> H
+    H --> A
+```
+
+## Dashboard Interaction
+
+1. User loads `/dashboard`, served by `templates/Dashboard.html`.
+2. Template fetches `/api/reporting/summary` with sample or user-provided simulation outputs.
+3. Response metrics populate the summary grid and Chart.js visualization.
+
+## Simulation Roadmap
+
+- Implement stochastic sampling in `services/simulation.py` (e.g., NumPy random draws based on parameter distributions).
+- Store iterations in `models/simulation_result.py` via `/api/simulations/run`.
+- Feed persisted results into reporting for downstream analytics and historical comparisons.