Södertälje Thesis Work Smart Machining Real Time Tool Health Monitoring Using Machine Tool Signals 151 38
- LocationNot stated
- Work typeNot stated
- Posted3 November 2026
- SourceScania's careers page (SAP SuccessFactors)
Live checkFirst seen 3 days ago; still listed on Scania's careers page 3 days ago.
Back from the application? Add your CV and RoleFinder scores your fit for this role, then ranks your best 12 open roles where you want to work, each with a one-line reason.
Check my fitAbout the role
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
Get open roles ranked against your CV
Add your CV once. RoleFinder ranks the open roles where you want to work, plus remote ones, against it, shows your best 12 with a one-line reason each, and emails you new matches once a week. The file is read once by AI and not kept; employers never see it.
Sign in with Google or email to start. How we handle your CV