DELULU: A Role-Based Web Restaurant Management System

A full-stack web restaurant management system designed to replace paper-based workflows with a streamlined, real-time order-to-payment lifecycle. The system supports four employee roles—Manager, Staff (Waiter), Chef, Cashier—each with distinct permissions and dashboards.

UI/Prototype reference (Figma): https://www.figma.com/design/ee5qyBs9MTQ6OMZnE3LFcG/Restaurant-Management-App

Deployment Link (Azure VM): http://webdevfromthitlwin.koreacentral.cloudapp.azure.com/login

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Team Members

• Thit Lwin Win Thant
• Honey Linn
• Eaint Myat Thu

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Project Overview

Problem Statement

Traditional paper-based restaurant operations often cause:

• miscommunication between dining area and kitchen
• slow billing and payment handling
• limited visibility into real-time sales performance

Target Users

Restaurant employees with role-based responsibilities:

• Manager
  admin@gmail.com
  1234
• Staff (Waiter)
  waiter@rest.com
  1234
• Chef
  chef@gmail.com
  1234
• Cashier
  cashier@rest.com
  1234

Why It Matters

This system helps reduce customer waiting time, minimize human errors (orders, tax, totals), and provides managers with instant insights (e.g., daily sales totals) for better decision-making.

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Core Features (Scope)

• Role-Based Access Control (RBAC)
  Secure login with distinct permissions for Manager, Staff, Chef, and Cashier.

• Table Management
  Real-time visualization of table status (e.g., Free vs Seated) and seat capacity.

• Digital Ordering System
  Menu browsing + “add to cart” ordering with automatic tax and total calculation.

• Kitchen Display System (KDS)
  Chef workflow to move orders across stages such as Processing → Finish → Completed.

• Manager Dashboard

  • Today’s Sales
  • Total Orders
  • CRUD for Staff/User management
  • CRUD for Menu management

• Sales Performance Ranking
  Automated Top 5 best-selling menu items based on aggregated order quantities.

• Peak Traffic Visualization
  Bar chart showing order volume by hour (helps staffing decisions).

• Payment Method Analysis
  Breakdown of payment types: Cash vs Card vs QR.

• Average Order Value (AOV)
  Real-time average revenue per table.

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Data Models (High-Level)

Menu_Item

Fields: menu_item_id, name, price, is_available, photo, category
Operations: Manager CRUD; Staff read (view menu)

App_User

Fields: user_id, name, email, password, role (manager/chef/staff/cashier), phone_no
Operations: CRUD staff access + login/authentication

Order

Fields: order_id, table_id, user_id (staff), order_time, status (new/processing/ready/paid)
Operations: create order, view active, update status, void

Restaurant Table

Fields: table_id, table_no, capacity
Operations: Manager CRUD; Staff read table availability

Order Item

Fields: order_item_id, order_id, menu_item_id, quantity, unit_price
Operations: add/remove/update items in cart and order summary

Kitchen Status

Fields: kitchen_status_id, order_id, chef_user_id, kitchen_status, start_time, finish_time
Operations: ticket generation, queue viewing, status updates, archive completed

Payment

Fields: payment_id, order_id, cashier_user_id, pay_time, method (cash/card/qr), tax, discount, payment_status
Operations: invoice creation, transaction viewing, mark paid, void transaction

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Tech Stack

• Frontend: React.js
• Backend: Node.js (Express)
• Database: MongoDB
• Deployment: Microsoft Azure VM

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Running the Code (Development)

Frontend

Install dependencies and run the development server:

npm i
npm run dev

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Backend + MongoDB (Local)

1. Start MongoDB with Docker

cd backend
docker compose up -d

2. Create a single environment file at the project root Create a .env file in the workspace root and add:

• MONGODB_URI=<your mongo connection string>
• MONGODB_DB=<your database name>
• VITE_API_BASE_URL=http://localhost:3003

3. Start the backend

cd backend
npm i
npm run dev

Backend runs on: http://localhost:3003

Backend Environment Requirements

The API expects:

• MONGODB_URI (Mongo connection string)
• MONGODB_DB (database name)

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