Modelling of temperature distribution of printed circuit boards

Abstract

This article analyzes process automation information systems in terms of the production and use of data and information for decision making. It examines how the data needed for decisions can be supplemented in addition to measurements using modeling. The article deals in detail with the production of data by modeling. From the measured physical data, it presents the advantages of temperature distribution modeling for the production of PCB (Printed Circuit Board) using temperature measurement data. It discusses the modeling of the distribution of temperature as one of the most important process parameters, examining, among other things, its physical and electrical engineering modeling and points out the possibilities of mathematical modeling. Demonstrates the benefits of newer information gene-rated by modeling in making the right decisions. After classifying the mathematical models, it presents the inverse distance-weighted modeling procedure through a concrete example. The article emphasizes the importance of verifying the modeled values, taking into account the methods and using the values obtained by measurements.