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...

Process monitoring through control charts is a quite popular practice in statistical process control. This study is planned for monitoring the process dispersion parameter using exponentially weighted moving average (EWMA) control chart scheme. Most of the EWMA dispersion charts that have been proposed are based on the assumption that the parent distribution of the quality characteristic is nor...

Today for the expedition of the identification and timely correction of process deviations, it is necessary to use advanced techniques to minimize the costs of production of defective products. In this way control charts as one of the important tools for the statistical process control in combination with modern tools such as artificial neural networks have been used. The artificial neural netw...

Monitoring disturbances in process dispersion using control chart is mostly based on the assumption that quality characteristic follows normal distribution, which not case many real-life situations. This paper proposes a set of new charts homogeneously weighted moving average (HWMA) scheme, for efficient detection shifts standard deviation (σ). These are variety σ estimators and investigated as...

Due to competition in the market, organization must have quality improvement program. Statistical quality control and especially control charts are proven quality improvement techniques. Control charts are based on the quality characteristics measurement in the course of time. There are some situations such as measurement error, sophisticated measurement instruments, costly skilled inspectors, ...

Attribute control charts (e.g., charts for counts and proportions) have discrete jumps in the quantities plotted on the charts, which means that the chart designer has only a discrete set of unique control limits to choose from when designing a chart. These charts have a small set of in-control Average Run Lengths (ARLs) from which to determine the appropriate control scheme. In a chart with ra...

Statistical process control is an excellent quality assurance tool to improve the quality of manufacture and ultimately scores on end-customer satisfaction. SPC uses process monitoring charts to record the key quality characteristics (KQCs) of the component in manufacture. This paper elaborates on one such KQC of the manufacturing of a connecting rod of an internal combustion engine. Here th...