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Maintenance and Warranty Concepts

  • Minjae Park
  • Hoang Pham
Chapter
Part of the Springer Series in Reliability Engineering book series (RELIABILITY)

Abstract

In general, a warranty is an obligation attached to products that require the manufacturer to provide compensation for customer (buyer) according to the warranty terms when the warranted products fail to perform their intended functions. A warranty is important to the manufacturer as well as the customer of any commercial product since it provides protection to both parties. As for the customer, a warranty provides a resource for dealing with items that fail due to the uncertainty of the product’s performance and unreliable products. For the manufacturer, it provides protection since the warranty terms explicitly limit the responsibility of a manufacturer in terms of both time and type of product failure. Because of the role of the warranty, manufacturers have developed various types of warranty policies to grab the interest of the customers. However, manufacturers cannot extend the warranty period without limit and maximize warranty benefits because of the cost related to it. Many researchers have studied in the last several decades on various warranty modeling and policies along with its maintenance policies. This chapter focuses on the developments of warranty modeling with various maintenance policies as well as the methodologies with various aspects that can be used to derive the mathematical warranty modeling. The concepts of warranty and review of the overall information about the warranty policy such as warranty’s role, concept and different types will be discussed. The basic mathematical maintenance concepts including counting processes such as renewal process, quasi-renewal process, non-homogeneous Poisson process, compound and marked Poisson process and bivariate exponential distribution also will be provided.

Keywords

Preventive Maintenance Replacement Policy Warranty Period Maintenance Policy Minimal Repair 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  1. 1.Department of Industrial and Systems EngineeringRutgers UniversityPiscatawayUSA
  2. 2.College of Business AdministrationHongik UniversitySeoulKorea

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