Applied AI Delivery Test
Thesis Work

Applied AI Delivery Test

Sweden | Mellansel

Thesis Work: Applied AI Delivery Test

Bosch Rexroth AB – A Bosch Company | Sweden | Mellansel | R&D

Bosch Rexroth Mellansel AB delivers complete hydraulic drive systems for the industry, mainly where low rotational speed and high torque are required. One important part of the drive system is the Hägglunds Compact motor that is designed and produced in Mellansel. Reliability is an important feature for Hägglunds products and Condition monitoring is one tool for increased reliability and availability of Hägglunds drive systems. A Condition monitoring system, called CMp, has been delivered to customers since 2018 but the system need continuous development. All motors that leave the factory in Mellansel pass a production test as a final quality control. Speed and pressure can be controlled in detail and various parameters are monitored.

At a glance


The idea is to use data from delivery test of hydraulic motors in order to train a model, a digital twin, which describe functions in the hydraulic motor, like friction and leakage. The model and data from individual motors can be used:

  • As a finger print of the motor when using Condition Monitoring at the customers application.
  • To monitor production quality of the motor in more detail.


A literature review will be made where one part is to study the theories of Hägglunds products and study the delivery test equipment and sequence. Another part will be to study the theory behind applied AI and the use of digital twins. The delivery test equipment is designed so that speed and pressure can be controlled which means that speed and pressure dependence on leakage and friction can be measured. One part of the work is to design the delivery test sequence so that suitable information is collected to train the model. Another part of the work is the model itself and here, information from existing motor simulations will be a valuable input. Practical tests with the designed test cycle will be performed in hydraulic laboratory. A very important part of the work is to suggest future work with suggestions on future strategies on how Bosch Rexroth Mellansel can use applied AI and digital twins to increase competitiveness.

Additional Information

  • Suitable for one or two Master of Science students.
  • Date for completion; August 2020.

Apply Now

We need your application no later than 2019-10-06.


Contact at Bosch Rexroth AB

Daniel Svanbäck
Senior Development Engineer

Contact at Luleå Tekniska Universitet

Roland Larsson
Chaired Professor