Measurement system analysis using designed experiments with minimum α-β Risks and n

摘要

Quality and productivity improvement are most effective when they are an integral part of the product and process development cycle. The main object of this study is re-identifying the variability sources that lead to errors in the measurements made for the correct evaluation of whether the targeted quality standards are reached in quality assurance systems, as well as at re-establishing a model with designed experiments, by virtue of including laboratory factor as a measurement variability factor into the Measurement System Analysis (MSA) studies, whereby it is currently ignored. The measurement systems that need to be examined and kept under control, in order to set the extent to which the products meet the customers requirements and expectations, have been analyzed statistically. Besides, new producer (α)-consumer (β) risks and the required minimum sample size (n) for its design will also be identified. As for the business organization chosen for the application of the model, a new determined sample size with a, ft error probabilities has been identified as a result of the applications with the new model.