Thesis Work - Smart Machining: Real-Time Tool Health Monitoring Using Machine Tool Signals

30 hp - Smart Machining: Real-Time Tool Health Monitoring Using Machine Tool Signals

Introduction

At Scania Transmission Manufacturing – do you want to be part of shaping the future of manufacturing processes by developing smart solutions to improve production efficiency and support our operators?

Within Transmission Manufacturing at Scania, we are entering an expansive development phase. Our machining equipment plays a central role in production. Here, we see great potential in leveraging data signals and digital tools to improve machine availability, optimize machining processes, and at the same time facilitate the work of our operators.

Thesis work is an excellent way to get closer to Scania and build relationships for the

future. Many of today's employees began their Scania career with their degree project.

Background

Modern CNC machines continuously generate valuable process data that can provide insights into cutting tool condition. Using this data for continuous monitoring creates opportunities to detect tool degradation, improve tool utilization, and support more stable and efficient machining processes.

Objective

This thesis aims to develop, implement, and validate a real-time Tool Condition Monitoring solution using machine-integrated signals. The goal is to establish continuous monitoring of cutting tool health in an industrial production environment and evaluate its performance under real production conditions.

Job description

You will develop and implement a real-time Tool Condition Monitoring solution using machine-integrated signals. The work includes automated data acquisition and signal processing, online tool health assessment, and validation in a real production environment. You will also investigate how tool health information can be visualized to support operators and production decision-making.

The output of this thesis would be:

• An implemented real-time data-driven Tool Condition Monitoring solution.
• Validation of the solution under industrial production conditions.
• Visualization of tool health information to support production decision-making.
• Recommendations for further development toward intelligent process monitoring and control.

Education/program/focus

Master students in industrial engineering, production engineering

Number of students: 1

Start date for the thesis work: 2027-01-18

Estimated time required: 20 weeks

Contact persons and supervisors

Mohammad Haddadzade

Mohammad.Haddadzade@scania.com

Application:

Your application must include a CV, personal letter and transcript of grades

A background check might be conducted for this position. We are conducting

interviews continuously and may close the recruitment earlier than the date

specified.    

Publication date from - to.

2026-10-06–2026-11-22