Új kockázatalapú szabályozó kártyák tervezése, kiválasztása és folyamathoz illesztése

Though statistical control charts are widely used tools for quality (conformity) control, they have some shortcomings: these control charts are designed on reliability base instead of risk base; they do not take the consequences of decisions into account. In addition the applicability of most control charts is confined to normality. Reducing these decision failures can be important in case of food industry. The data is obtained from measurements that are subject to uncertainty, and this uncertainty can lead to incorrect decision. This paper proposes a solution for practical specialist to choose and fit the right control chart to the analyzed process. The suggested method makes it possible to minimize the effects of the measurement uncertainty. This application determines the optimal bounds of the acceptance region and the control rules of the chosen chart considering the cost of decision errors and measurement uncertainty. In this paper we present the applicability of this control chart fitting method through a practical example, which is a cartridge filling process

Új kockázatalapú szabályozó kártyák tervezése, kiválasztása és folyamathoz illesztése

Though statistical control charts are widely used tools for quality (conformity) control, they have some shortcomings: these control charts are designed on reliability base instead of risk base; they do not take the consequences of decisions into account. In addition the applicability of most control charts is confined to normality. Reducing these decision failures can be important in case of food industry. The data is obtained from measurements that are subject to uncertainty, and this uncertainty can lead to incorrect decision. This paper proposes a solution for practical specialist to choose and fit the right control chart to the analyzed process. The suggested method makes it possible to minimize the effects of the measurement uncertainty. This application determines the optimal bounds of the acceptance region and the control rules of the chosen chart considering the cost of decision errors and measurement uncertainty. In this paper we present the applicability of this control chart fitting method through a practical example, which is a cartridge filling process