The process capability analysis helps in quantifying the process variability and assists manufacturing by reducing the variability. The process capability of a manufacturing process can be assessed through the computation of various process capability ratios. The fundamental assumption in process capability studies is that, the underlying distribution of quality characteristic is normal and plotted distribution follows a normal curve. This assumption sometimes needs to be validated. The proposed Kurtosis-based approach helps to understand whether the distribution under study is symmetrical and follows the normal curve or not, which reduces the volume of the computations required as compared to the usual method of analysis. The median for each sample containing number of sub-samples is located graphically, which helps to study the online behavior pattern of the process. The proposed graphical approach is simple and easy to understand. The new method creates the awareness of process management in shop floor operators. Using the quality characteristics of observations, a cumulative frequency table is prepared, and the mean and standard deviation are obtained. The paper deals extensively with the proposed method of the Kurtosis-based process capability analysis.

The usual method of process capability analysis involves large computations and requires more time. The usual method of process capability analysis uses range and average range, which is more sensitive and affects by fluctuation of sampling and is not a stable measure of dispersion (Elhance and Elhance, 2003, p. 9.6). The process capability computation by using grand average and average range (usual method) is called short-term process capability and by using pooled data, it is called long-term process capability. It is observed that short-term process capability (usual method) severely over estimates the process capability (Elhance and Elhance, 2003, p. 9.6). Estimation of process capability by long-term method involves large computations and requires more time. To overcome these limitations and the difficulties in finding grand mean and limitations of range, kurtosis-based normality test and process capability analysis is proposed.

Process capability is an inherent variation of the product turned out by the process. It provides the quantified prediction of the process adequacy and refers to the uniformity of the process. It is a measurement with respect to the inherent precision of a manufacturing process. Process capability analysis is a measurement of quality performance capability of the process with given factors and under statistical control conditions. The process capability can be measured and analyzed through the computations of various process capability indices by analytical methods. Graphical approach can be used to measure the process capability and thus makes it easier to assess the variability of the manufacturing process with less computation and time.

Management Research Journal, Kurtosis-based Normality Test, Process Capability Analysis, Long-term Process Capability, Manufacturing Organization, Process Management, Quality-improvement Programs, Process Capability Ratio, Operations Management, Innovatibe Designs, Meso-Kurtic Curve.