Adaptive Light Material Weld Cell Programming of Servodriven Components

  • Delft


In the automotive industry many different joining technologies are implemented to produce a car body. The conventional way has long been to use spotwelding, a cheap and reliable technology that was easy to implement and provided structural welds at low cost. In recent years the ugly indent it left as a trade mark became more and more a nuisance as nowadays customers are much more critical towards the perceived quality of a car body.

One of the solutions to produce welds with much better appearance was the special projection welding technology introduced by Arplas. It uses the minimum possible energy to produce a structural weld without an indent and with a very limited heat affected zone. This is achieved by using a high energy pulse that lasts only a few milliseconds so the energy is not spread through the part welded but localized at the projection area.


New energy cars are build using light metals as Aluminum and Magnesium. Joining those materials with resistance welding – still the cheapest way of producing metal car bodies – becomes a challenge in itself. Newest servo driven systems are combined for making projections, welding parts together and cleaning electrodes. Effective programming of such cells, using all the data they can produce might, greatly increase their efficiency. The challenge in this case is how to combine all available data into a protocol that enhances the effectivity of the cell, enhances the lifetime of the electrodes and predicts maintenance intervals.

This Thesis challenge for two TU 3ME/ PME Msc students to analyze behaviour of servo systems for resistance welding and the use of sensor systems to increase electrode lifetime and cycle time efficiency as well as predicts preventive maintenance. Part of the challenge is to investigate the possibility of using big data gathered by the sensor systems implemented in these production cells to make them adaptive and therefore more efficient.


Literature Research : international overview and assessment of state of art of servo driven resistance welding systems for aluminum and magnesium resistance welding

Algorithm– write an algorithm exchange of sensor data between the different components leading to an adaptive welding cell

Design– design a test setup where this algorithm can be verified and optimized.

Buildand test– realise an experimental set-up to proof the concept

CONTACT : ARPLAS dr. ir. Karel Pieterman 0653891945 HOLLANDCAREER drs. Ir Theo Lodewijkx