Asset management
Track assets with unique codes, service dates, status, serial numbers, location, manufacturer, and maintenance history.
Maintenex is a web-based maintenance platform designed to track assets, monitor service schedules, manage technicians, and visualize machine operating risk through an interactive synthetic machine simulator.
The project combines practical maintenance operations with an interactive machine-risk demo, making it useful both as a management system and as a showcase of data-driven monitoring logic.
Track assets with unique codes, service dates, status, serial numbers, location, manufacturer, and maintenance history.
Highlight overdue or upcoming service work so teams can respond before downtime becomes expensive.
Keep technicians, employees, and role-based access organized in one place for smoother operational control.
Use sensor sliders for temperature, vibration, RPM, load, and days since service to estimate current operating risk.
Show which signals are contributing most to risk so users can understand the result instead of seeing a black-box number.
Maintain a record of edits and service updates to provide traceability and accountability across assets.
A clean summary view showing asset health, service urgency, and key operational counts.
A showcase page where users adjust sensor inputs and view a live risk score with clear signal breakdown.
The project brings together maintenance administration, service planning, and condition monitoring in one workflow.
Assets are added with structured metadata, service dates, operational status, and a unique generated asset code.
The platform identifies overdue and upcoming service windows, helping teams prioritize what needs attention.
The synthetic machine page lets users adjust sensor conditions and instantly see a continuous operating-risk score with reasons.
Built as a practical full-stack project using Python, Flask, MySQL, HTML, CSS, JavaScript, and synthetic maintenance data analysis.
Key documentation and resources used throughout the development of Maintenex, covering design, research, implementation, and evaluation.
Defines the system scope, requirements, and intended behaviour of the Maintenex platform.
Background research on maintenance systems, sensor data relationships, and synthetic data validation.
System architecture, database structure, UI design, and backend logic for Maintenex.
Complete write-up including implementation details, testing, validation of synthetic data, and evaluation.
Source code for the Maintenex system, including backend, frontend, and synthetic data tools.
Hi, Iām Nebojsa Kukic.
Final year Software Development student at South East Technological University, Carlow, with a strong interest in secure application development and machine learning.
I developed this project to bring together my interest in software, engineering, and problem solving by building a system that makes maintenance tracking clearer, smarter, and easier to manage.
From the database structure and backend logic to the frontend design and synthetic machine simulator, I built Maintenex as a full end-to-end project. A major goal was to create something that not only works technically, but also feels practical, explainable, and relevant to real maintenance operations.