the most well-known uni-arribute control chart used to monitor the number of nonconformities per unit is the shewhart type c-chart. in this paper, a new method is proposed in an attempt to reduce the false alarm rate in the c-chart. to do this, the decision on beliefs (dob) concept is first uti [1] corresponding author e-mail: [email protected]   lized to design an iterat...

The reliability data is getting used to monitor and improve the quality of products or services. Nowadays, most of products or services are the results of processes with dependent stages referred to as multi-stage process. In these processes, the quality characteristics are affected by the quality characteristics in the previous stages, called as cascade property. In some cases, it is not possi...

multivariate control charts such as hotelling`s t^ 2 and x^ 2 are commonly used for monitoring several related quality characteristics. these control charts use correlation structure that exists between quality characteristics in an attempt to improve monitoring. the purpose of this article is to discuss some issues related to the g chart proposed by levinson et al. [9] for detecting shifts in ...

In some statistical process monitoring applications, quality of a process or product is described by more than one ordinal factors called ordinal multivariate process. To show the relationship between these factors, an ordinal contingency table is used and modeled with ordinal log-linear model. In this paper, a new control charts based on ordinal-normal statistic is developed to monitor the ord...

This paper puts forward a novel concept of tetrahedron model of chart cartography error analysis and quality control which is necessary for introducing user to the former triangle model of error analysis and quality control, i.e. Reality-Producer-Chart-User. For the human being, high quality does not necessarily represent high accuracy, but represent a concept that what is fit for use. Classica...

Traditionally, the statistical quality control techniques utilize either an attributes or variables product quality measure. Recently, some methods such as three-level control chart have been developed for monitoring multi attribute processes. Control chart usually has three design parameters: the sample size (n), the sampling interval (h) and the control limit coefficient (k).The design parame...

Most of the inventory control models assume that quality defect never happens, which means production process is perfect. However, in real manufacturing processes, the production process starts its operation in the in-control state; but after a period of time, shifts to the out-of-control state because of occurrence of some disturbances. In this paper, in order to approach the model to real man...

In high quality industrial processes, the control chart is design based on cumulative count of conforming (CCC) items is very useful. In this paper, the performance of CCC-r chart with variable sampling intervals (CCC-rVSI chart) in the presence ofinspectionerrors isinvestigated. The efficiency of CCC-rVSI chart is compared with CCC-r chart with fixed sampling interval (CC...

Control charts are one of the most important tools in statistical process control that lead to improve quality processes and ensure required quality levels. In traditional control charts, all data should be exactly known, whereas there are many quality characteristics that cannot be expressed in numerical scale, such as characteristics for appearance, softness, and color. Fuzzy sets theory is a...