Estimating the number of product failures: a theoretical approach

Warning The system is temporarily closed to updates for reporting purpose.

Amniattalab, Ayda (2018) Estimating the number of product failures: a theoretical approach. [Thesis]

[thumbnail of 10208137_AydaAmniattalab.pdf] PDF
10208137_AydaAmniattalab.pdf

Download (12MB)

Abstract

In this thesis, we propose a stochastic process describing the total number of failed items under warranty over time. This stochastic process consists of a sales process represented by a stochastic point process and a process count­ing the total random number of repairs applied to an arbitrary item of this product. Combining these two stochastic processes yields a representation of the counting process of the total random number of failed items returned to the manufacturer within their warranty period. To fit the proposed parametric model to a large data set we need to estimate separately the intensity measure of both the failure and sales process. To estimate the intensity measure of the cumulative sales process we use some well known parametric functions and apply linear regression techniques. Also, under the assumption that a repair does not change the age of the particular item of the product it can be shown that the counting process of failures is a non-homogenous Poisson process and so we need to estimate the cdf of the time to the first failure. Since our data set is censored we apply the Maximum Likelihood principle for censored data and use as a parametric class the class of Weibull distributions. Our approach serves as an alternative to the time series based approaches for cases where item tracking information is available.
Item Type: Thesis
Uncontrolled Keywords: Stochastic point processes. -- Time series. -- Linear regression. -- Maximum likelihood. -- Censored data. -- Stokastik nokta süreçleri. -- Zaman serileri. -- Doğrusal regresyon. --Maksimum olabilirlik. -- Sansürlü veri.
Subjects: T Technology > T Technology (General) > T055.4-60.8 Industrial engineering. Management engineering
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Industrial Engineering
Faculty of Engineering and Natural Sciences
Depositing User: IC-Cataloging
Date Deposited: 02 Oct 2018 09:30
Last Modified: 26 Apr 2022 10:25
URI: https://research.sabanciuniv.edu/id/eprint/36585

Actions (login required)

View Item
View Item