Several modifications and enhancements to control charts in increasing the performance of small and moderate process shifts have been introduced in the quality control charting techniques. In this paper, a new hybrid control chart for monitoring process location is proposed by combining two homogeneously weighted moving average (HWMA) control charts. The hybrid homogeneously weighted moving average (HHWMA) statistic is derived using two smoothing constants λ 1 and λ 2. The average run length (ARL) and the standard deviation of the run length (SDRL) values of the HHWMA control chart are obtained and compared with some existing control charts for monitoring small and moderate shifts in the process location. The results of study show that the HHWMA control chart outperforms the existing control charts in many situations. The application of the HHWMA chart is demonstrated using a simulated data. K E Y W O R D S average run length (ARL), control chart, homogeneously weighted moving average (HWMA), hybrid homogeneously weighted moving average (HHWMA), process monitoring

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Purpose The purpose of this paper is to propose a double exponentially weighted moving average control chart using repetitive sampling (RS-DEWMA) for a normally distributed process variable to improve the efficiency of detecting small process mean shift. Design/methodology/approach The algorithm for the implementation of the proposed chart is developed and the formulae for the in-control and out-of-control average run lengths (ARLs) are derived. Tables of ARLs are presented for various process mean shift. The performance of the proposed chart is investigated in terms of the average run-length for small process mean shift and compared with the existing DEWMA control chart. Numerical examples are given as illustration of the design and implementation of the proposed chart. Findings The proposed control chart is more efficient than the existing DEWMA control chart in the detection of small process mean shifts as it consistently gives smaller ARL values and quickly detects the process shift. However, the performance of the proposed chart relatively deteriorates for large smoothing constants. Practical implications The application of repetitive sampling in the control chart literature is gaining wide acceptability. The design and implementation of the RS-DEWMA control chart offers a new approach in the detection of small process mean shift by process control personnel. Originality/value This paper fills a gap in the literature by examining the performance of the repetitive sampling DEWMA control chart. The use of repetitive sampling technique in the control chart is discussed in the literature, however, its use based on the DEWMA statistic has not been considered in this context.

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The double exponentially weighted moving average (DEWMA) control chart has been observed to be more sensitive than the exponentially weighted moving average (EWMA) control chart for process monitoring assuming that the quality characteristic follows the normal distribution. In this paper, the DEWMA control chart is proposed for monitoring quality characteristics that follow the exponential distribution using variable transformation technique. The in-control and out-of-control average run lengths (ARLs) of the proposed control chart is obtained for equal and unequal smoothing constants. The performance of the proposed control chart with equal and unequal smoothing constants was investigated and compared with recent existing control charts in terms of the out-of-control average run lengths. Real life example is given to demonstrate the application of the proposed chart. The findings show that the performance of the proposed control chart outweighs existing control charts in the monitoring of process parameter when the quality variable follows exponential distribution for all shift sizes.