Attribute np Control Charts using Resampling Systems for Monitoring Non-Conforming Items using Exponentiated Half Logistic Distribution

Abstract

This paper is centred on a binary classification problem in which it is desired to assign a new object with multivariate features to one of two distinct populations as based on historical sets of samples from two populations. A linear discriminant analysis framework has been proposed, called the minimised sum of deviations by proportion (MSDP) to model the binary classification problem. In the MSDP formulation, the sum of the proportion of exterior deviations is minimised subject to the group separation constraints, the normalisation constraint, the upper bound constraints on proportions of exterior deviations and the sign unrestriction vis-à-vis the non-negativity constraints. The two-phase method in linear programming is adopted as a solution technique to generate the discriminant function. The decision rule on group-membership prediction is constructed using the apparent error rate. The performance of the MSDP has been compared with some existing linear discriminant models using a previously published dataset on road casualties. The MSDP model was more promising and well suited for the imbalanced dataset on road casualties.

Control charts using half-normal and half-exponential power distributions using repetitive sampling

“…Additionally, Jeyadurga et al 23 applied the concept of RSS to life data distributions and constructed an ACC for the Pareto distribution of the second kind. Tanveer et al 24 focused on the development and evaluation of the ACC using resampling techniques (Repetitive sampling and multiple dependent state) for monitoring non-conforming items under the exponentiated half-logistic distribution. The derived formulas, extensive ARL tables, real-life example, and simulation study collectively highlight the effectiveness of the proposed control chart in detecting assignable causes in a timely manner.…”

“…Recently, Saleh et al 26 proposed that repetitive sampling methods can be useful, however, when monitoring with count data. More information on the use of control charts can be seen in Lee et al 21 , Tanveer et al 24 , Elal-Olivero et al 27 , Naveed et al 28 and Rao et al 29 , 30 .…”

Performance of attribute control charts for monitoring the shape parameter of modified power function distribution in the presence of measurement error

“…Jeyadurga et al 24 constructed the 𝑛𝑝 CC using repetitive sampling using Pareto distribution of second kind. More work using TTLT can be seen in Rosaiah et al, 25 Balamurali and Jeyadurga, 26 Rao et al, 27 Aslam et al, 19 Kowsalya et al, 28 Tanveer et al, 29 Adeoti and Ogundipe, 30 Aslam et al, 31 Zaka et al, 32 Riffat and Azam (2021) and Zaka et al 32 The Power function distribution (PFD) developed by Dallas 33 is widely utilized in Engineering, health risk assessments and environmental because of its simplicity in expression and easy to fit for many processes. Over the complicated probability models Meniconi and Barry 34 presented PFD as a better to fit in many real life situations.…”