Abstract
In 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.
Highlights
Numerous investigations prove the dependence of the welding fume emission on the welding process parameter settings [1,2,3]
The Latinized Centroidal Voronoi Tessellation (LCVT) algorithm, which combines the advantages of Centroidal Voronoi Tessellation (CVT) and Latin Hypercube Sampling (LHS) [11,12,13], was used to ensure equal distribution of the experimental parameters
Since the parameter spaces created by LCVT are often considerably larger than the actual parameter spaces that make sense from the welding point of view, the final experimental design can be reduced in this way
Summary
Numerous investigations prove the dependence of the welding fume emission on the welding process parameter settings [1,2,3]. It is desirable to create an empirically based model that can map the relationships between process behavior and the resulting welding fume emissions, compare Fig. 1. Information gain in both directions is conceivable. Resulting emission rates can be predicted on the basis of selected parameter settings and adjustment recommendations can be given under specification of a limit value of the emission rate. The information basis for modeling is provided by experimental welding fume investigations using a fumebox, from which process-specific emission rates are determined. Continuous validation by expert knowledge and adaptation or improvement by empirical data input are necessary in order to critically analyze the model quality and make adjustments if necessary
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