Using multi-dimensional scaling and hierarchical clustering to improve the process in a hot-dip galvanizing line

An application for the scheduling coils of a Hot-Dip Galvanizing Line is presented. In this case, a multi-dimensional scaling is used for the creation of a bidimensional coil map from the most significant parameters of the coils: chemical composition, dimensions, process's parameters, etc. This map shows the group degree and the existing distances between the coils so that the human expert can interact with the software to decide which are the more suitable groups of classification and to detect those coils that could be problematic within the industrial process. After that, a hierarchical clustering is utilized to find local clusters with similar dissimilarities to introduce theminto the scheduling list. These combined methods can help in the generation of more effective sequences as well as in the prevention and reduction of the number of contingencies that habitually take place in the plant.

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