Since 1987 Uddcomb Engineering has repaired pulps by their own developed overlay welding method even called Uddcomb method. Currently each welding machine is operated by two persons. To increase Uddcomb Engineering competitiveness the reduced number of operators is desired. An installation of a monitoring system which can aid humans in the welding quality control also helps to improve company’s position. A future goal would be to make this monitoring system automatic without a human operator in the loop. In this thesis, arc voltage, weld current and audio signals were collected and analyzed with aim on finding algorithms to monitor the quality of the welding process. The use of statistics tools is the basis for detecting variations in the voltage and current data, associated with welding process. It has been shown that voltage signal can be used as a part of the welding quality control. The audio signal from welding at low frequencies varies with the speed of the process. The signal can also be incorporated in the monitoring of the process. The use of filters, growing sums and statistics are key elements in the algorithms presented in this report.