Approach for the characterization of industrial process tasks as basis for the generation and application of an equipment module database

Abstract

Module-based plant design opens up the opportunity for the (bio-)chemical industry to reduce lead times, which is crucial for future competitiveness. Equipment modules are designed once such that they can cover a wide range of process tasks and conditions. The time-consuming equipment design step is replaced by selecting the most suitable equipment module from an equipment module database so that engineering work is reused. It is the aim of this work to develop a structured approach for the determination of features to characterize industrial process tasks. On the one hand, these characteristic features determined are required for the generation of an equipment module database based on cluster analysis of industrial process tasks (Eilermann et al., 2017). On the other hand, the characteristic features are a measure for similarity of process tasks and support the selection of the same equipment module for similar tasks. Thereby, reuse of engineering is enabled. The approach for the determination of characteristic features presented is based on those used in data mining, whereas the quality of the characteristic features is traded off against the computational effort required. The approach developed is exemplarily applied to industrial liquid/liquid heat exchanger and condenser tasks kindly provided by Evonik.