The McCabe–Thiele Method: A Centenary Tribute to an Emblem of Chemical Engineering and Engineering Epistemology

This essay is a tribute to the McCabe–Thiele method, which was first published 100 years ago in this journal. We argue that the McCabe–Thiele method has become an emblem of chemical engineering, as it establishes a balance that simultaneously enables prediction and understanding, making it also emblematic of engineering epistemology. The McCabe–Thiele method is analyzed here by going through its most important aspects: the historical background, the model assumptions and how these enable predictions and understanding, as well as the question of novelty. We argue that the remarkably long-lasting success of the McCabe–Thiele method is due to how it creates understanding through its graphical approach, and we identify elements of engineering epistemology that make it emblematic in a quite general sense. Finally, we briefly discuss the future role of the McCabe–Thiele method, considering that machine learning will change the way distillations are designed.

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Publication Details

Journal
Industrial & Engineering Chemistry Research
Published
2025-09-16
DOI
https://doi.org/10.1021/acs.iecr.5c02730
Citations
1
Primary Topic
Reservoir Engineering and Simulation Methods
Type
article
Field-Weighted Citation Impact
1.15
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article

The McCabe–Thiele Method: A Centenary Tribute to an Emblem of Chemical Engineering and Engineering Epistemology

Hans Hasse, Johannes Lenhard, Fabian Jirasek, J. H. Heiss
1 citations
Industrial & Engineering Chemistry Research
Reservoir Engineering and Simulation Methods
1.15
article

The McCabe–Thiele Method: A Centenary Tribute to an Emblem of Chemical Engineering and Engineering Epistemology

Hans Hasse, Johannes Lenhard, Fabian Jirasek, J. H. Heiss
article en
1 citations

Abstract

This essay is a tribute to the McCabe–Thiele method, which was first published 100 years ago in this journal. We argue that the McCabe–Thiele method has become an emblem of chemical engineering, as it establishes a balance that simultaneously enables prediction and understanding, making it also emblematic of engineering epistemology. The McCabe–Thiele method is analyzed here by going through its most important aspects: the historical background, the model assumptions and how these enable predictions and understanding, as well as the question of novelty. We argue that the remarkably long-lasting success of the McCabe–Thiele method is due to how it creates understanding through its graphical approach, and we identify elements of engineering epistemology that make it emblematic in a quite general sense. Finally, we briefly discuss the future role of the McCabe–Thiele method, considering that machine learning will change the way distillations are designed.

Industrial & Engineering Chemistry ResearchVol. 64(39)
Institute of Philosophy (RU), European Thermodynamics (United Kingdom) (GB), Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau (DE)
Openalex Percentile: Top 19%
Reservoir Engineering and Simulation Methods
1.15
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