Method development of statistical modeling for the description of welding fume emissions in gas metal arc welding using transient process characteristics

Abstract

AbstractIn the past, most approaches to reduce welding fume emissions were primarily based on welding consumables, whereas in the context of the present work, a new concept with direct reference to the welding process technology is pursued. Many other measures to improve occupational health and safety, such as use of extended personal protective equipment (e.g., forced air ventilated helmets) and extraction systems, relate to the reduction of immissions of welding fumes already emitted. In comparison, the selection of optimized parameter settings in terms of gas metal arc welding (GMAW) provides a process-related possibility to reduce welding fume emissions without the need for additional equipment. In order to illustrate and quantify the functional interdependencies between process parameterization and the resulting fume emission generation, a model relationship is developed which is primarily based on empirical investigations. Via post-process analysis, certain features are extracted from the transient measurement data and correlated with the process-specific emission rates. With the help of the model, individual parameters can be iteratively set on the basis of representative process features. Besides parameter optimization with regard to emission-reduced processes, a forecast of the expected fume emission rate can be derived based on the selected settings. The methodology described and examined is applicable to different process spaces of GMAW or even other fume-emitting welding processes.