Joint economic design of X̄ and R control charts for processes subject to two independent assignable causes

A model for the joint economic design of X̄ and R control charts is developed. This model assumes that the process is subject to two assignable causes. One assignable cause shifts the process mean; the other shifts the process variance. The occurrence of the assignable cause of one kind does not block the occurrence of the assignable cause of another kind. Consequently, a second process parameter can go out-of-control after the first process parameter has gone out-of-control. A numerical study of the cost surface to the model considered has revealed that it is convex, at least in the interest region.

Joint X̄ and R charts with variable parameters

Recent studies have shown that the X̄chart with variable parameters (Vp X̄ chart) detects process shifts faster than the traditional X̄ chart. This article extends these studies for processes that are monitored by both, X̄ and R charts. Basically, the X̄ and R values establish if the control should or should not be relaxed. When the X̄ and R values fall in the central region the control is relaxed because one will wait more to take the next sample and/or the next sample will be smaller than usual. When the X̄ or R values fall in the warning region the control is tightened because one will wait less to take the next sample and the next sample will be larger than usual. The action limits are also made variable. This paper proposes to draw the action limits (for both charts) wider than usual, when the control is relaxed and narrower than usual when the control is tightened. The Vp feature improves the joint X̄ and R control chart performance in terms of the speed with which the process mean and/or variance shifts are detected. © 1998 IIE.

Stress levels and quality of sleep in subjects with temporomandibular joint dysfunction

Purpose: The aim of this study was to test the association between quality of sleep and stress in individuals with temporomandibular disorder (TMD). Methods: The study sample consisted of 354 adult subjects (males and females) from the municipality of Piacatu, São Paulo state, in the Southeast region of Brazil. Data were collected using the Fonseca’s Questionnaire to record the level of TMD, the Pittsburgh Sleep Quality Index (PSQI) to assess quality of sleep and the Social Readjustment Rating Scale (SRRS) to record stress level. The data were analyzed by the software Epi Info 2000 version 3.2 using a chi-square test at the 0.05 level of significance. Results: One hundred and eighty (50.8%) subjects had some level of TMD. The statistical analysis showed a significant relationship between the three stress scores and the presence or absence of sleep disorders, considering an overall PSQI score > 5 as an indicator of a subject with sleep problems (P<0.01). Conclusion: Both quality of sleep and stress levels were associated with TMD in this sample.