(188j) A Methodology to Generate Modular Equipment for an Equipment Database in Module-Based Plant Design
AIChE Annual Meeting
2016
2016 AIChE Annual Meeting
Computing and Systems Technology Division
Interactive Session: Systems and Process Design
Monday, November 14, 2016 - 3:45pm to 5:45pm
Although of central importance in module-based plant design, an applicable equipment database has not been developed, yet. Therefore, in this contribution a methodology for equipment database generation is presented, that has been developed within a research project funded by the German Federal Ministry for Economic Affairs and Energy (BMWi). The modular equipment stored in the equipment database needs to match with industrial demand in order to be competitive with the individual equipment design. The methodology developed starts from industrial heat exchanger applications prepared by the project partner Evonik Industries AG. Process applications are grouped in a cluster analysis according to a set of defining features. For each of these groups a representative heat exchanger is selected. Therefore, a set of shell and tube heat exchangers is generated in a sampling step. From this set a heat exchanger is selected to be the representative, which covers most of the applications within the considered group of process applications. The representative heat exchangers are stored in the equipment database. To apply the generated equipment database, the stored modular heat exchangers are used to set up a heat exchanger network. The results are compared to conventional heat exchanger network design in terms of energy efficiency and costs.
The results show, that most of the industrial applications can be covered by a significantly reduced number of heat exchangers. Applying modular equipment in heat exchanger networks may lead to increased investment costs. However, it could be shown exemplarily that the energy efficiency is being improved.
Acknowledgment
The German Federal Ministry for Economic Affairs and Energy (BMWi) is acknowledged for funding this research as part of the ENPRO initiative.
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