A Predictive Quality Inspection Framework for the Manufacturing Process in the Context of Industry 4.0.

The purpose of this research is to develop an innovative software framework with AI capabilities to predict the quality of automobiles at the end of the production line. By utilizing machine learning techniques, this framework aims to prevent defective vehicles from reaching customers, thus enhancing production efficiency, reducing costs, and shortening the manufacturing time of automobiles. The principal results demonstrate that the predictive quality inspection framework significantly improves defect detection and supports personalized road tests.

The spatial distribution of congener-specific human PCB concentrations in a PCB-polluted region.

Serum PCB congener concentrations were measured in 602 adults living near a PCB pollution source in eastern Slovakia. We created isoconcentration maps for 21 PCB congeners by geocoding each participant's place of residence and kriging. Concentrations of PCB congeners were inversely associated with the distance of the participants' residence from the source of pollution.