An Efficient Phase I Analysis of Linear Profiles with Application in Photo-Voltaic System

Abstract

In many manufacturing industries, quality of an item depends on different characteristics and their relationship may be modeled by profiles. For instance, in photo-voltaic (PV) system, output voltage is dependent on the capacitance level of capacitors, used in the Z-source inverter. Control chart is a dynamic tool that works under two different phases namely Phase I and Phase II. The unknown parameters are estimated in Phase I, while Phase II focuses on monitoring of the process using estimated control limits from Phase I. In this study, we have investigated Phase I monitoring of linear profile parameters under several sampling approaches including ranked set sampling (RSS), double RSS, median RSS (MRSS), double MRSS, extreme RSS (ERSS) and double ERSS. A comparative analysis on the performance of existing and proposed schemes is performed in terms of probability to signal. The results advocate that the proposed methods under different ranked set schemes offer superior detection abilities as compared to the existing schemes for varying shifts in profile parameters (intercept, slope and error variance). Moreover, a real application related to PV system is included to show the practical demonstration of the profile monitoring (for the output voltage in relation to capacitance level) under proposed schemes.