Johnson, DB;
Bogle, IDL;
(2019)
A quantitative risk analysis approach to a process sequence under uncertainty - A case study.
Computers & Chemical Engineering
, 126
pp. 1-21.
10.1016/j.compchemeng.2019.03.039.
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Abstract
Process plants for the manufacture of pharmaceutical products often need to be designed and built quickly to make the most of available patent life which necessitates using uncertain or unavailable data. It is common that pilot plant equipment and data are available and new data can be generated if they are important. We present a model based approach to risk analysis to aid design for pharmaceutical processes which combines systematic modelling procedures with Hammersley sampling based uncertainty analysis and sensitivity analysis used to quantify predicted performance uncertainty and to identify key uncertainty contributions. The main contribution of the paper is the demonstration of the methodology on an industrial case study where the process flowsheet was fixed and some pilot data was available. Expected performance was improved by considering the propagation of uncertainty over the whole process. The case study results indicate the importance of considering uncertainty systematically and quantitatively. The methodology showed the opportunity to improve process performance potential through considering uncertainty systematically.
| Type: | Article |
|---|---|
| Title: | A quantitative risk analysis approach to a process sequence under uncertainty - A case study |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.compchemeng.2019.03.039 |
| Publisher version: | https://doi.org/10.1016/j.compchemeng.2019.03.039 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | pharmaceutical processing; risk analysis; uncertainty; design |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices UCL > Provost and Vice Provost Offices > VP: Research |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10104902 |
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