Optimising the Gaussian-distributed filling process parameters Online publication date: Thu, 17-Jul-2008
by Mohammed H. Hassan
International Journal of Agile Systems and Management (IJASM), Vol. 3, No. 1/2, 2008
Abstract: A filling production system is that characterised by two contradicting nonconforming cost components. The first component is that incurred when the product specification exceeds the upper tolerance limit, called an overfill cost, whereas the second cost component is contributed when the product specification falls below the lower tolerance limit, called an underfill cost. The ratio of the two cost components affects to a high extent the choice of the process parameters, especially the process location parameter that minimises the overall costs. The work in this research is devoted to finding the filling process's optimum parameters; namely the process's mean and variance, considering a Gaussian-distributed process. Firstly, the process's variance is considered constant; and searching for the optimal process mean parameter takes place. An analytical, closed form, solution model is developed that realises such target. The developed model is ended up with a graph that can simply be used by concerned engineers and practitioners. The assumption of a constant process variance is then relaxed; and the developed model is extended to involve the variance reduction cost. An algorithm is introduced to solve the extended model that optimises the filling process' mean and variance.
Online publication date: Thu, 17-Jul-2008
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