Master Thesis 30 credits - Relating Process Data to Product Quality

Scania is now undergoing a transformation from being a supplier of trucks, buses and engines to a supplier of complete and sustainable transport solutions.

The technologies associated to terms like Industry 4.0, Internet of Things and Digitalization are about to reach also the manufacturing of heavier transmission parts manufacturing here at Scania. Production machines are being connected and Big Data is becoming available, but the practical benefits of this data access remain largely unexplored. The time has come to change that.

Background
To produce products in a metal-cutting machine, certain information is involved. Some information is needed for the operation of the machine, such as electric current in motors and pressure in hydraulic systems. Other process information is produced during operation, such as temperature and vibrations. Retrieving and organizing all this information would give us process data.

Geometric measurements may be performed during workpiece set-up, such as run-out on a fixture on a rotating spindle. To adjust the machine, the produced part is measured. The product is then measured regularly during the production.

Product quality is measured in terms of variation in relation to the tolerance for the product requirements. To get the variation, several products samples need to be measured, which takes time. The process data is mostly available continuously and cause of variation is probably measurable through this data.

Assignment
In a given manufacturing machine or a whole production line, identify probable causes of variation on the manufactured product.

Collect process data and product data from the running production. Perform dedicated test runs if necessary to produce relevant data, probably using design of experiment methods.

Analyse the relation between process data and product data, using e.g. regression analysis.

Propose a model for machine adjustments based only on the process data.

Perform a test run to verify the model.

Target
A proof of concept for machine control based on process measurement. The outcome would be decreased need of measurement resources and a basis for predictive maintenance strategies.

Students Profiles
Machine design and manufacturing methods.

Interest in the merged area of machine design, production quality and statistical data analysis.

Time Plan
20 weeks, Spring semester 2021

Supervisor Scania
Klas Sunesson (DXD) 08-553 802 82, klas.sunesson@scania.com

Application:
Enclose CV, personal letter and school-leaving certificate. Welcome with your application at latest 2020-11-22. JobID 20202571.


Scania is a world-leading provider of transport solutions. Together with our partners and customers we are driving the shift towards a sustainable transport system. In 2018, we delivered 88 000 trucks, 8 500 buses as well as 12 800 industrial and marine engines to our customers. Net sales totalled to over SEK 137 billion, of which about 20 percent were services-related. Founded in 1891, Scania now operates in more than 100 countries and employs some 52 000 people. Research and development are concentrated in Sweden, with branches in Brazil and India. Production takes place in Europe, Latin America and Asia, with regional production centres in Africa, Asia and Eurasia. Scania is part of TRATON.SE. For more information visit www.scania.com.