Academic Journal
Industry 4.0 in Action: Digitalisation of a Continuous Process Manufacturing for Formulated Products
| Title: | Industry 4.0 in Action: Digitalisation of a Continuous Process Manufacturing for Formulated Products |
|---|---|
| Authors: | D. Ntamo, E. Lopez-Montero, J. Mack, C. Omar, M.I. Highett, D. Moss, N. Mitchell, P. Soulatintork, P.Z. Moghadam, M. Zandi |
| Source: | Digital Chemical Engineering, Vol 3, Iss , Pp 100025- (2022) |
| Publisher Information: | Elsevier, 2022. |
| Publication Year: | 2022 |
| Collection: | LCC:Chemical engineering LCC:Information technology |
| Subject Terms: | Digital Twin, Smart Manufacturing, Continuous manufacturing, Formulated Products, Digital Chemical Industry, Data visualisation, Chemical engineering, TP155-156, Information technology, T58.5-58.64 |
| More Details: | The pharmaceutical industry is going through a significant change to adopt smart manufacturing for more integrated supply chains and improved sustainability. Today's competitive market demands have put pressure on healthcare systems to take a comprehensive assessment of the drug life cycle, its environmental effect, industrial use of energy and resources, supply chain, and impact on end-users. The exploitation of emerging Industry 4.0 technologies will allow a sustainable process design and personalised health care system through the realisation of digital twins, which could transform the pharmaceutical sector to be more flexible, robust, adaptive, and smart. A significant level of research and development has been applied to pharmaceutical manufacturing especially in existing, outdated design and scale-up paradigms in isolated unit operations. However, addressing the key challenges in pharmaceutical manufacturing requires whole systems approaches to incorporate Industry 4.0 concepts.This paper aims to share the latest development of an advanced digital twin of a continuous wet granulation and tableting process at The University of Sheffield. These include the delivery of a digital platform consisting of an Advanced Process Control system (APC), mechanistic model platform and industrial IoT platform for data analytics and visualisation. The combined solution aligns with the concepts of Industry 4.0 by providing a digital twin, cloud integration, sophisticated statistical, as well as hybrid and mechanistic models. The models are in turn, used for soft-sensors, Model Predictive Control and Optimisation algorithms to predict and control product Quality Attributes. The potential application of digital twins in the pharmaceutical industry will also be explored. |
| Document Type: | article |
| File Description: | electronic resource |
| Language: | English |
| ISSN: | 2772-5081 |
| Relation: | http://www.sciencedirect.com/science/article/pii/S2772508122000163; https://doaj.org/toc/2772-5081 |
| DOI: | 10.1016/j.dche.2022.100025 |
| Access URL: | https://doaj.org/article/51fcb4d17ca54f31a43d701a47dcfa3d |
| Accession Number: | edsdoj.51fcb4d17ca54f31a43d701a47dcfa3d |
| Database: | Directory of Open Access Journals |
| ISSN: | 27725081 |
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| DOI: | 10.1016/j.dche.2022.100025 |
| Published in: | Digital Chemical Engineering |
| Language: | English |