- Title
- Reconfigurable smart factory for drug packing in healthcare industry 4.0
- Creator
- Wan, Jiafu; Tang, Shenglong; Li, Di; Imran, Muhammad; Zhang, Chunhua
- Date
- 2019
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/183066
- Identifier
- vital:16258
- Identifier
-
https://doi.org/10.1109/TII.2018.2843811
- Identifier
- ISBN:1551-3203 (ISSN)
- Abstract
- Industry 4.0, which exploits cyber-physical systems and represents digital transformation of manufacturing, is deeply affecting healthcare as well as other traditional production sector. To accommodate the increasing demand of agility, flexibility, and low cost in healthcare sector, a data-driven reconfigurable production mode of Smart Factory for pharmaceutical manufacturing is proposed in this paper. The architecture of the Smart Factory is consisted of three primary layers, namely perception layer, deployment layer, and executing layer. A Manufacturing's Semantics Ontology based knowledgebase is introduced in the perception layer, which is responsible for plan scheduling of pharmaceutical production. The reconfigurable plans are generated from the production demand of drugs as well as the information statement of low-level machine resources. To further functionality reconfiguration and low-level controlling, the IEC 61499 standard is also introduced for functionality modeling and machine controlling. We verify the proposed method with an experiment of demand-based drug packing production, which reflects the feasibility and adequate flexibility of the proposed method. © 2005-2012 IEEE. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Muhammad Imran" is provided in this record**
- Publisher
- IEEE Computer Society
- Relation
- IEEE Transactions on Industrial Informatics Vol. 15, no. 1 (2019), p. 507-516
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- Copyright 3203 © 2018 IEEE
- Subject
- 40 Engineering; 46 Information and Computing Sciences; Cyber-physical systems (CPS); Healthcare industry 4.0; IEC 61499; Ontology; Reconfiguration; Smart factory
- Reviewed
- Funder
- This work was supported in part by the National Key Research and Development Program of China under Grant 2017YFE0101000; in part by the Science and Technology Program of Guangzhou, China (201802030005); and in part by the Key Program of Natural Science Foundation of Guangdong Province under Grant 2017B030311008 Paper no. TII-18-0944.
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