Enabling energy‐efficient manufacturing of pharmaceutical solid oral dosage forms via integrated techno‐economic analysis and advanced process modeling. Issue 4 (16th July 2022)

• Record Type: Journal Article
• Authors: Sampat, Chaitanya; Kotamarthy, Lalith; Bhalode, Pooja; Chen, Yingjie; Dan, Ashley; Parvani, Sania; Dholakia, Zeal; Singh, Ravendra; Glasser, Benjamin J.; Ierapetritou, Marianthi; Ramachandran, Rohit
• Other Names: Malkani Haresh guestEditor.; Korambath Prakashan guestEditor.
• Is Part Of: Journal of advanced manufacturing and processing. Volume 4:Issue 4(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-07-16
• Subjects: advanced process models -- energy efficiency -- Industry 4.0 -- smart manufacturing -- techno‐economic analysis; Chemical engineering -- Periodicals; Manufacturing processes -- Technological innovations -- Periodicals; Manufacturing processes; Electronic journals; Periodicals; 660
• DOI: 10.1002/amp2.10136
• Languages: English
• ISSNs: 2637-403X

Abstract

Abstract: The global pharmaceutical industry is a trillion‐dollar market. However, the pharmaceutical sector often lags in manufacturing innovation and automation which limits its potential to maximize energy efficiency. The integration of techno‐economic analysis (TEA) with advanced process models as part of an overarching smart manufacturing platform, can help industries create business models, which can be adapted for manufacturing to reduce energy consumption and operating costs while ensuring product quality which can further enable a more sustainable process operation. In this study, a rational design of experiment on three unit‐operations (wet granulation, drying, and milling) was performed on a batch (case 1) and continuous (case 2) pharmaceutical process to obtain experimental data. Process models for predicting product quality and energy efficiency of each of the three‐unit operations were developed. The experimental data were used to validate the models and good agreement was observed. The energy consumption of each unit operation was calculated using statistical models relating the power consumption and the process parameters. The developed process models and energy models were further integrated into a TEA framework, which quantified the energy and monetary cost of manufacturing for both batch and continuous manufacturing cases. With this integrated framework, energy costs savings of ~33% was obtained in the continuous manufacturing process (case 2) over the batch process (case 1).