Abstract

Current challenges for (bio-)chemical industry require shorter project lead times. To reduce the lead time, the concept of module-based plant design was developed. Suitable equipment modules are selected from an equipment module database instead of time-consuming tailor-made equipment design. The quality of module-based plant design strongly depends on the quality of the equipment module database. An equipment module database should contain the least number of equipment modules covering as many industrial applications as possible. Hence, the generation of an equipment module database is a maximum coverage problem known from other disciplines, such as facility location. Within this work, the corresponding maximum coverage problem is formulated and solved by a randomized greedy algorithm. The approach for the generation of an equipment module database presented is exemplarily applied for liquid/liquid heat transfer applications provided by Evonik. It is shown, that less equipment modules are required for the same coverage of applications if the equipment module database is generated based on the maximum coverage problem than based on the existing methodology presented by Eilermann et al. (2017). Additionally, less computational effort is required.

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