Development of a Paint Application System Morphological Matrix for Enable Prediction of Restoration Paint Coating Quality on Car Body Parts

Increasing the efficiency of the bodywork service by ensuring the necessary conditions for obtaining high-quality paintwork is an important component of car service systems that provide bodywork restoration services. Improving the quality of the paintwork of repaired car body parts leads to a reduction in the costs of car service systems and an increase in their operating efficiency. As a result of the analysis of technologies for restoring the paintwork of car body parts, a scheme of the surface preparation process for painting was developed, consisting of the technological process operations for restoring the paintwork. If we assume that all preparatory operations for applying the paintwork are performed qualitatively, then it is possible to describe the paintwork application system by determining its significant parameters and, based on the morphological analysis method, develop a morphological matrix describing this system. The morphological matrix of the paintwork application system consists of morphological structures and morphological features by which this system is described. The gradation of quantitative variants of morphological features was determined using the method of quantitative assessments. The combination of individual variants of all morphological features forms a new morphological structure of the paint and varnish application system. That is, the morphological matrix allows describing all existing, as well as form new, more effective structures of paint and varnish application systems. This matrix is used to predict the quality of the paint and varnish coating on body parts to be repaired, taking into account the initial parameters of the paint and varnish application system. To determine the most significant morphological features of the system, it is necessary to conduct an examination of at least 20 systems of different morphological structure and use the Farrar-Glober algorithm to determine independent parameters and select the most significant ones among them.