Evaluation and Prediction of Production Yields in Plastic Manufacturing Industry Using Artificial Neural Network

C., Akaolisa Chukwuebuka and Sunday, Iweriolor and M. C., Uzochukwukanma and C. D., Ezeliora and N., Ezeliora (2023) Evaluation and Prediction of Production Yields in Plastic Manufacturing Industry Using Artificial Neural Network. Journal of Engineering Research and Reports, 25 (11). pp. 106-122. ISSN 2582-2926

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Abstract

The study focused on the evaluation and prediction of a production yield in Finoplastika plastic manufacturing industry. The study investigates the need of prediction and continuous improvement of production plastic yield in manufacturing industries. The literature reveals the related research works in manufacturing industries and found a gap in application of predictive tools to appraise the plastic production yield in the case company. The use of artificial neural network serves as the method of data analysis applied to achieve the aim of this study. The application of artificial neural network for the predicted solutions of the response variables of 110mm waste plastic pipe, 20mm pressure plastic pipe, 50mm waste plastic pipe and 32mm pressure plastic pipe are 31149, 45171, 13412, and 12891 respectively. The results for predicted solutions are recommended to the case company and other plastic companies for their wider use and applicability in other to achieve their optimal results and to support decision making during, inventory system, production process, production planning and control.

Item Type: Article
Subjects: OA Open Library > Engineering
Depositing User: Unnamed user with email support@oaopenlibrary.com
Date Deposited: 28 Nov 2023 06:57
Last Modified: 28 Nov 2023 06:57
URI: http://archive.sdpublishers.com/id/eprint/2193

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