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http://hdl.handle.net/1942/35037
Title: | A conceptual approach to retrofit modular concepts into batch reactor setups at Janssen through a data-analysis of the operation records | Authors: | van Bussel, Michiel | Advisors: | BRAEKEN, Leen VAN GOOL, Dennis |
Issue Date: | 2021 | Publisher: | UHasselt | Abstract: | At present, a major part of the batch reactors at the multipurpose plant of Janssen in Geel is fully equipped with a similar setup of static process equipment. However, future trends in the pharmaceutical industry have heightened the need for more complex and flexible manufacturing capabilities. An upcoming investment at Janssen prompts the opportunity for this thesis to investigate modular concepts for nine reactor setups to realize a more flexible design, higher equipment utilization and additionally reduce the upcoming investment cost for new equipment. In this thesis, a data-analysis of records from the reactor’s operating system is performed to locate potential modularization options. The data is analyzed in Excel through mapping all operational phases per reactor by examining the duration and frequency of executions of all operational phases of the year 2020 as an approach to evaluate the equipment utilization. Results of this thesis indicate potential modularization options for distillation, reflux and separation. The small number of separations facilitates the use of an external modular separation system. In addition, the potential implementation of modular condenser systems is feasible due to the lower utilization of the condensers in four reactors. Consequently, two modular equipment setups are proposed respectively following an asset optimization mindset and an asset reduction mindset. Ultimately, a cost reduction of respectively 6.63% and 1.54% is observed relative to the complete revamp of the equipment. | Notes: | master in de industriële wetenschappen: chemie | Document URI: | http://hdl.handle.net/1942/35037 | Category: | T2 | Type: | Theses and Dissertations |
Appears in Collections: | Master theses |
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838b23f8-53b5-4720-b3af-f0d29ea111f5.pdf | 3.79 MB | Adobe PDF | View/Open | |
c199ecfb-7eeb-4b24-8e66-72c4b7f09fd1.pdf | 490.75 kB | Adobe PDF | View/Open |
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