Application of Neuro-Fuzzy for Improving Volume Control in Water Canning Industry

Abstract

The computation minimization which is associated with neurofuzzy models and controllers may be installed in industrial programmable Logic controllers (PLC). The implementation of thermal sterilization is both model and control in order to validate the pilot plant of water canned industry. Volume control in beverage manufacturing companies requires that a certain measured volume be filled into specific container sizes to conform to already predetermined standard to ensure competitiveness in the industry. However, most industry does not have accurate and reliable monitoring mechanism capable of sensing when the canned bottles are not properly filled. This operational failure can be overcome by designing a model that will monitor and control the filling process thereby improving volume control in water canning industry using feedback Neuro-fuzzy control. MATLAB Software was used to carry out simulations to develop volume control in water canning industry with aims of improving operational mechanism of industry. The result of the research revealed the empirical data collected in Rancor Nig. Ltd., Enugu, Nigeria and feedback Neurofuzzy. This ANN model can then be trained with values generated from an already existing mathematical model to be able to monitor and control the filling of the cans. The result showed that volume control in water canning industry with and without feedback Neuro-fuzzy were 63cl and 50cl respectively. The volume increased by 13cl. With these results, it shows that using feedback Neuro-fuzzy gives a better result in terms of filling to the required volume of the bottle than when feedback Neuro-fuzzy is not used.