Problem statement: Although economic Xbar-R chart designs do guarantee the minimal operating cost, they typically have poor levels of statistical performance measures. The obvious limitation of the economic design is that the Type I error rate seems to be very high for many situations and will cause a large number of false alarms. This situation leads to an investigation of appropriate levels o...

This work presents an exponentially weighted moving average (EWMA)-based synthesised control scheme for a process with outliers. Based on experience, some processes occasionally have outliers. The use of traditional mean ( X ) and range (R) control charts (denoted as X=R) for monitoring process mean and variance leads to high-level false alarms. In this study, the fast-detection technique (EWMA...

This article investigates integrated maintenance, production, and product quality control policy for a supply chain consisting of single machine producing only one type product, main storage warehouse, multi-purchases warehouses. The variation the production rate its use over time impact manufacturing system’s degradation degree. Hence, is subject to random failure that directly affects product...

Usually, there are two phases in constructing a multivariate control chart. Phase I is to estimate the in-control process parameters and to establish control limits using historical data. Phase II is when the control limits are used to monitor the process. This paper focuses on determining the optimal number of samples in Phase I since number of samples affect the cost of quality control in pra...

Excessive variation in a manufacturing process is one of the major causes of a high defect rate and poor product quality. Therefore, quick detection of changes, especially increases in process variability, is essential for quality control. In modern manufacturing environments, most of the quality characteristics that have to be closely monitored are multivariate by the nature of the application...

Some quality control schemes have been developed when several related quality characteristics are to be monitored. The familiar multivariate process monitoring and control procedure is the Hotelling’s T 2 control chart for monitoring the mean vector of the process. It is a direct analog of the univariate shewhart x̄ chart. As in the case of univariate, the ARL improvements are very important par...