Achieving process intensification form the application of a phenomena based synthesis, Design and intensification methodology

Publication: ResearchConference abstract for conference – Annual report year: 2012

View graph of relations

Process Intensification/Process Systems Engineering.

Process intensification (PI) is a means by which one can achieve a more efficient and sustainable chemical process. Major success in the area of PI has been achieved by Eastman chemicals [1] which in 1984 intensified the process for the manufacture of methyl acetate by replacing with one single reactive distillation column the multi-step process which consisted of one reactor, extractive distillation, liquid-liquid separation and azeotropic distillation. However, except for reactive distillation and dividing wall columns, the implementation of PI still faces challenges [2] because the identification and design of intensified processes is not simple [3]. Lutze et al [3] has developed a systematic PI synthesis/design method at the unit operations (Unit-Ops) level, where the search space is based on a knowledge-base of existing PI equipment. Siirola [4] has proposed a task-based approach known as the means-ends analysis. A limitation with the means-ends analysis is that it becomes difficult to apply if too many corrective tasks should be identified and replaced and if too many alternatives should be considered From the above PI methods, the starting point is knowledge of existing Unit-Ops and therefore a limitation arising from their application is that they are able to generate new integrations/combinations of intensified equipment but are unable to generate novel PI solutions employing new Unit-Ops. Therefore, incentives exist for a more systematic, efficient and flexible PI methodology covering a wider range of applications which is able to find truly innovative and predictive solutions, not only using knowledge of the existing methods at the Unit-Ops level but also operating at a lower level of aggregation (that is, the phenomena level). This enables the use of apriori knowledge of the Unit-Ops as well as the possibility to design new Unit-Ops. A first version for a phenomena-based synthesis/design (PhenPI) methodology has been developed [5] in which a process flowsheet is generated through the use of involved phenomena such as mixing, phase transition and phase separation [5]. In principle, generating processes from phenomena leads to a large number of process options and therefore, an efficient solution procedure for the evaluation of these process options is needed. To manage this complexity, the PhenPI methodology uses a decomposition based solution approach which breaks down the complex mathematical synthesis/design problem into manageable sub-problems (6 steps). It allows the generation of PI options and their subsequent stepwise reduction of the search space and identification of the best intensified process option. In step-1, the problem definition of the process to be intensified, the process scenario (batch or continuous) and constraints are defined. In step-2, the process is analysed based on the base case design and the flowsheet is converted into a task and phenomena based flowsheet. In step-3, analysis of the process at the task and phenomena level and the use of different tools such as analysis of pure component and mixture properties are used to identify limitations/bottlenecks of the process. From this data, desirable tasks and suitable phenomena are identified to overcome these limitations/bottlenecks and for the processing of tasks in the most efficient manner. In step-4, the involved phenomena are aggregated and/or connected using a set of connectivity rules based on the operating windows of each phenomenon. Based on this, a large number of flowsheet options are generated which are subsequently screened for feasibility by applying logical and structural constraints. In step-5, the remaining flowsheet options are fast screened by constraints for feasibility and for performance using a set of PI performance metrics. The most promising phenomena-based options are transformed into a unit-operation based flowsheet using a set of rules. In step-6, the most promising unit-operation based options from step-5 are optimized in order to identify the best process option. In this paper the PhenPI methodology is presented in detail and highlighted by its application to the production of methyl acetate in order to identify the best PI option with respect to sustainability and other processes requiring reaction-separation processing tasks. It will be shown that the PhenPI methodology systematically not only generates the reactive distillation option proposed by Siirola but also other alternatives which have not been previously considered.
Original languageEnglish
Publication date2012
StatePublished

Conference

ConferenceANQUE ICCE 2012
CountrySpain
CitySevilla
Period24/06/1227/06/12
Internet addresshttp://www.anqueicce2012.org/en/index.htm

Bibliographical note

Oral presentation.

References:
[1] V. H. Agreda, L. R. Partin & W. H. Heise . High-purity methyl acetate via reactive distillation. Chem. Eng. Prog. 1986 (2) 40–46
[2] J. Harmsen. Process intensification in the petrochemicals industry: Drivers and hurdles for commercial implementation. Chem. Eng. Process. 2010 (49) 70–73
[3] P. Lutze, A. Román-Martinez, J. M. Woodley & R. Gani. A systematic synthesis and design methodology to achieve process intensification in (bio) chemical processes. Comput. Chem. Eng. 2012 (36) 189– 207
[4] Jeffrey J. Siirola. Strategic process synthesis: Advances in the hierarchical approach. Comput. Chem. Eng. 1996, Supplement 2 (20) S1637-S1643
[5] P. Lutze, R. Gani & J. M. Woodley. Phenomena-based Process Synthesis and Design to achieve Process Intensification. Comp. Aided Chem. Eng. 2011 (29) 221–225

Download as:
Download as PDF
Select render style:
APAAuthorCBEHarvardMLAStandardVancouverShortLong
PDF
Download as HTML
Select render style:
APAAuthorCBEHarvardMLAStandardVancouverShortLong
HTML
Download as Word
Select render style:
APAAuthorCBEHarvardMLAStandardVancouverShortLong
Word

ID: 9988849