Warranty Cost Models using Accelerated Life Tests on Dagum Distribution

Eman A El-Dessouky Nassef

doi:10.3844/jmssp.2020.148.160

Abstract

Warranty one of the main factors which effect on the decision to purchase any product whether it is non repairable or repairable, therefore, in market the manufacturers can compete by using warranty service. The cost of warranty are wanted to predict which are mirrored on the price and profitability of products. To achieve this goal, the research is concerned with predicting the cost of the two common types of warranty models which are free rebate warranty and pro-rata rebate warranty when The lifetime of items is assumed to follow Dagum distribution. The constant stress partially accelerated life tests based on type II censoring is used. Maximum likelihood method is used to estimate the model parameters and acceleration factor of lifetime distribution from the test data. Confidence Interval for the model parameters are constructed using normal approximation and bootstrap method. Finally, Some numerical illustrations are provided.

Highlights

IntroductionManufacturer need to predict the price of claims due to failures in the course of a specific period, which known as warranty length
According to competitive markets, products are bought with warranty
In a constant stress Partially Accelerated Life Testing (PALT), the total sample size n of test units is divided into two parts such that: 1. n items randomly chosen among n test items sampled are allocated to accelerated condition and the remaining are allocated to normal use condition, where is the proportion of test items

Summary

Introduction

Manufacturer need to predict the price of claims due to failures in the course of a specific period, which known as warranty length. These costs are fluctuated due to many factors such as: Probability density characteristic of failure time distribution, duration of warranty period, type of warranty policy, average cost of replacement or repair. Some of them used Accelerated life testing in predicting warranty cost models as: Yang (2010; Zhao and Xie, 2017), when life time distribution is Weibull distribution. Accelerated Life Testing (ALT) is a method for estimating the reliability of products at normal operating conditions from the failure data obtained at the severe conditions.

Test Procedure

The lifetimes Ti and Xj are mutually statisticallyindependent

Bootstrap Method

Conclusion