With vision for pioneering weld seam inspection
Reliable weld seams are important for piping systems in the semiconductor industry. To test this quality, SCS has developed an innovative vision inspection system for its customer Georg Fischer.
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Problem definition
In the semiconductor industry, reliable weld seams on pipes are extremely important. If a spot leaks, the factory has to be stopped, which has major financial consequences.
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SCS solution
SCS has developed suitable imaging processes and algorithms to analyse and verify the quality of weld seams.
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Added value
Based on SCS's work, the customer was able to further develop the project into a product. This won second place at the IVS Innovation Award 2019 and was launched in February 2020.
Project insights
The customer Georg Fischer offers a wide range of products that enable pipes to be welded together (Fig. 1). The pipes are welded by heating and pressing them together. Molten material emerges at the pressing point (cross-section Fig. 2). Possible solutions for the quality control of such weld seams were developed together with the customer. The solution ideas developed in the innovation workshop formed the basis for a feasibility study carried out by SCS.


The aim of the study was to develop a method that could be used to determine different quality characteristics of a weld seam. For example, the weld seam thickness, pipe misalignment, etc. were to be detected.
Various methods and algorithms were developed and tested in the feasibility study. Ideas were developed, difficulties discussed and the best possible solutions worked out in the SCS Vision Lab. The test set-ups enabled a quick evaluation of the various approaches and their feasibility. For example, the test setup with a laser (Fig. 3) initially looked promising, but was quickly discarded thanks to a short iteration cycle. It turned out that the different optical properties of the pipe materials were not suitable for quality control with a laser.

For this reason, the current solution uses transmitted light to provide similar images for different materials. This setup made it possible to use inexpensive camera modules and lighting (Fig. 4). This solution is therefore simpler and delivers very good results.
The captured images were then analysed and evaluated using a classic vision algorithm. The vision algorithm analyses the various dimensions and determines the weld seam quality (Fig. 5).


