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Optimal Productivity And Design Of Production Quantity Of A Manufacturing Industry
[Full Text]
AUTHOR(S)
Okolie Paul Chukwulozie, Oluwadare Benjamin Segun,Obika Echezona Nnaemeka,Nwadike Emmanuel Chinagorom, Olagunju Suraj Jare
KEYWORDS
Optimization, Prediction, Batch, Model, Raw Material, Surface Response Plot, Residual Plot.
ABSTRACT
The ever-increasing demand on engineers to lower production costs to withstand global competition has prompted engineers to look for rigorous methods of decision making such as optimization methods, to design and produce products and systems both economically and efficiently. This paper improved the batch production per month of Glass production, a case study of Beta Glass limited. Their production data was optimized using Response surface modeling tool to obtain the optimum production process of the raw materials. Response surface regression analysis was used to estimate the coefficient of the dependent variables using the production raw data with the coefficient of determination (R-sq.) being 100%, this shows the relationships of the variables.From the analysis, their production yield increased from 4,280 batches of bottles per month, to an optimal value of 5,340 batches of bottles per month.
REFERENCES
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[5] Okolie, P.C, Okafor, E.C, and Chinwuko, E.C. (2010),"Optimal production mix for Bread industries: A case study of selected Bakery Industries in Eastern Nigeria" Journal of Engineeringand Applied Science 5(6), pp.403-412.
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