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Optimization Of Process Parameters Research Articles

Feed manufacturing faces enormous challenges and with the demand permanently quality feed increasing gradually, it becomes essential to enhance the processes during a feed mill. This text provides a quick overview of the various processes in feed manufacturing and identifies the critical process parameters. Five critical parameters are identified where the assembly rate is that the output parameter. Mash feed size, steam temperature; conditioning time and feed rate are the input parameters. Artificial neural network is that the methodology which is employed to optimize the method parameters. Root mean squared error and coefficient of determination and computation time are used as performance measures and it's observed that Polak–Ribiere conjugate gradient backpropagation training function with log sigmoid – pure linear transfer function combination provided good results among the various available alternatives. The method parameters are then optimized using the acceptable ideal settings of neural network parameters. This model is extremely useful for the prediction of production rate for 1 specific recipe during a feed mill. "A research article is a primary source...that is, it reports the methods and results of an original study performed by the authors. The kind of study may vary (it could have been an experiment, survey, interview, etc.), but in all cases, raw data have been collected and analyzed by the authors, and conclusions drawn from the results of that analysis. Research articles follow a particular format. Look for a brief introduction will often include a review of the existing literature on the topic studied, and explain the rationale of the author's study. This is important because it demonstrates that the authors are aware of exisiting studies, and are planning to contribute to this existing body of research in a meaningful way (that is, they're not just doing what others have already done)."