Self-Organizing map in analysis of large-scale industrial systems

Publisher Summary This chapter discusses the characterization of industrial processes that is traditionally done based on analytic system models. The models may be constructed using knowledge based on physical phenomena and on assumptions of the system behavior. The measurement data and other types of information are typically stored in databases. In many practical situations, even minor knowledge about the characteristic behavior of the system might be useful. The chapter explores the self-organizing map (SOM), which is a powerful tool in visualization and analysis of high-dimensional data in engineering applications. The SOM maps the data on a two dimensional grid, which may be used as a base for various kinds of visual approaches like clustering, correlation, and novelty detection. In this chapter, the methods are discussed and applied to the analysis of hot rolling of steel, continuous pulping process, and technical data from world's pulp and paper mills.