The automation of industrial processes has been one of the greatest innovations in the industrial sector. It allows faster and accurate operations of production processes while producing more outputs than old manual production techniques. In the beverage industry, this innovation was also well embraced, especially to improve its bottling processes. However it has been proven that a continuous optimization of automation techniques using advanced and current trend of automation is the only way industrial companies will survive in a very competitive market. This becomes more challenging for small to medium scale enterprises (SMEs) which are not always keen in adopting new technologies by fear of overspending their little revenues. By doing so, SMEs are exposing themselves to limited growth and vulnerable lifecycle in this fast growing automation world. The main contribution of this study was to develop practical and affordable applications that will optimize the bottling process of a SME beverage plant by combining its existing production resources to basic principles of the current trend of automation, Industry 4.0 (I40). This research enabled the small beverage industry to achieve higher production rate, better delivery time and easy access of plant information through production forecast using linear regression, predictive maintenance using speed vibration sensor and decentralization of production monitoring via cloud applications. The existing plant Siemens S7-1200 programmable logic controller (PLC) and ZENON supervisory control and data acquisition (SCADA) system were used to program the optimized process with very few additional resources. This study also opened doors for automation in SMEs, in general, to use I40 in their production processes with available means and limited cost. / School of Computing / M.Tech (Engineering, Electrical)
Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:unisa/oai:uir.unisa.ac.za:10500/25772 |
Date | 08 1900 |
Creators | Kiangala, Kahiomba Sonia |
Contributors | Wang, Z. |
Source Sets | South African National ETD Portal |
Language | English |
Detected Language | English |
Type | Dissertation |
Format | 1 online resource (viii, 134 leaves) : illustrations, graphs (color), application/pdf |
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