Controle on-line para o número de não-conformidades em um ítem inspecionado

The on-line processes control for attributes consists of inspecting a single item at every m produced ones. If the examined item is conforming, the production continues; otherwise, the process stops for adjustment. However, in many practical situations, the interest consist of monitoring the number of non-conformities among the examined items. In this case, if the number of non-conformities is higher than an upper control limit, the process needs to be stopped and some adjustment is required. The contribution of this paper is to propose a control system for the number of nonconforming of the inspected item. Employing properties of an ergodic Markov chain, an expression for the expected cost per item of the control system was obtained and it will be minimized by two parameters: the sampling interval and the upper limit control of the non-conformities of the examined item. Numerical examples illustrate the proposed procedure

Ajuste preventivo versus ajuste corretivo no controle on-line de processo do número de não-conformidades num item inspecionado

In production lines, the entire process is bound to unexpected happenings which may cost losing the production quality. Thus, it means losses to the manufacturer. Identify such causes and remove them is the task of the processing management. The on-line control system consists of periodic inspection of every month produced item. Once any of those items is quali ed as not t, it is admitted that a change in the fraction of the items occurred, and then the process is stopped for adjustments. This work is an extension of Quinino & Ho (2010) and has as objective main to make the monitoramento in a process through the control on-line of quality for the number of non-conformities about the inspected item. The strategy of decision to verify if the process is under control, is directly associated to the limits of the graphic control of non-conformities of the process. A policy of preventive adjustments is incorporated in order to enlarge the conforming fraction of the process. With the help of the R software, a sensibility analysis of the proposed model is done showing in which situations it is most interesting to execute the preventive adjustment