Skip to main content

Optimal replacement with minimal repair policy for a system operating over a random time horizon

Buy Article:

$54.08 plus tax (Refund Policy)

Abstract:

Purpose ‐ This paper aims to investigate the optimization of the replacement with minimal repair policy for a system which experiences a time horizon of random length. Under such policy system replacement occurs at multiples of some period while minimal repair is performed at system failure between two successive replacements. Design/methodology/approach ‐ The objective function is the expected total cost composed of minimal repairs and replacements costs. A simple and compact expression is derived for the expected total costs and conditions under which an optimal replacement period exits are given. For sake of illustration, a numerical example is provided. Findings ‐ The paper finds that by the recent great technological development, the life cycle of present products is seen to be reduced more and more. This has motivated the development of maintenance optimization models for systems which experience an exact finite time horizon. Originality/value ‐ To ensure the benefits from the improved technologies, the information concerning the technological change must be taken into account. Such information is based on technological forecasting and difficult to obtain and merely rely on uncertainties.

Keywords: Optimization; Optimization techniques; Preventive maintenance; Reliability; Reliability management

Document Type: Research Article

DOI: http://dx.doi.org/10.1108/13552511111180203

Publication date: October 25, 2011

mcb/154/2011/00000017/00000004/art00006
dcterms_title,dcterms_description,pub_keyword
6
5
20
40
5

Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more