Maximizing system availability through joint decision on component redundancy and spares inventory

Wei Xie, Haitao Liao, Tongdan Jin

Research output: Contribution to journalArticle

60 Citations (Scopus)

Abstract

For a repairable k-out-of-n:G system consisting of line-replaceable units, its operational availability depends on component reliability, its redundancy level, and spare parts availability. As a result, it is important to consider redundancy allocation and spare parts provisioning simultaneously in maximizing the system's operational availability. In prior studies, however, these important aspects are often handled separately in the areas of reliability engineering and spare parts logistics. In this paper, we study a collection of operational availability maximization problems, in which the component redundancy and the spares stocking quantities are to be determined simultaneously under economic and physical constraints. To solve this type of problem, continuous-time Markov chain models are developed first for a single repairable k-out-of-n:G system under different shut-off rules, and some important properties of the corresponding operational availability and spare parts availability are derived. Then, we extend the models to series systems consisting of multiple repairable k-out-of-n:G subsystems. The related optimization problems are reformulated as binary integer linear programs and solved using a branch-and-bound method. Numerical examples, including a real-world application of automatic test equipment, are presented to illustrate this integrated product-service solution and to offer valuable managerial insights.

Original languageEnglish (US)
Pages (from-to)164-176
Number of pages13
JournalEuropean Journal of Operational Research
Volume237
Issue number1
DOIs
StatePublished - Aug 16 2014

Fingerprint

Redundancy
Spare Parts
Availability
Branch and bound method
Series System
Branch and Bound Method
Markov Chain Model
Continuous-time Markov Chain
Integer Program
Real-world Applications
Linear Program
Markov processes
Logistics
Subsystem
Economics
Binary
Optimization Problem
Engineering
Numerical Examples
Unit

Keywords

  • Operational availability
  • Performance-based contracting
  • Redundancy allocation
  • Repairable k-out-of-n: G system
  • Spare parts logistics

ASJC Scopus subject areas

  • Management Science and Operations Research
  • Modeling and Simulation
  • Information Systems and Management

Cite this

Maximizing system availability through joint decision on component redundancy and spares inventory. / Xie, Wei; Liao, Haitao; Jin, Tongdan.

In: European Journal of Operational Research, Vol. 237, No. 1, 16.08.2014, p. 164-176.

Research output: Contribution to journalArticle

@article{0754d15ab4fc4729affe8cf092203686,
title = "Maximizing system availability through joint decision on component redundancy and spares inventory",
abstract = "For a repairable k-out-of-n:G system consisting of line-replaceable units, its operational availability depends on component reliability, its redundancy level, and spare parts availability. As a result, it is important to consider redundancy allocation and spare parts provisioning simultaneously in maximizing the system's operational availability. In prior studies, however, these important aspects are often handled separately in the areas of reliability engineering and spare parts logistics. In this paper, we study a collection of operational availability maximization problems, in which the component redundancy and the spares stocking quantities are to be determined simultaneously under economic and physical constraints. To solve this type of problem, continuous-time Markov chain models are developed first for a single repairable k-out-of-n:G system under different shut-off rules, and some important properties of the corresponding operational availability and spare parts availability are derived. Then, we extend the models to series systems consisting of multiple repairable k-out-of-n:G subsystems. The related optimization problems are reformulated as binary integer linear programs and solved using a branch-and-bound method. Numerical examples, including a real-world application of automatic test equipment, are presented to illustrate this integrated product-service solution and to offer valuable managerial insights.",
keywords = "Operational availability, Performance-based contracting, Redundancy allocation, Repairable k-out-of-n: G system, Spare parts logistics",
author = "Wei Xie and Haitao Liao and Tongdan Jin",
year = "2014",
month = "8",
day = "16",
doi = "10.1016/j.ejor.2014.02.031",
language = "English (US)",
volume = "237",
pages = "164--176",
journal = "European Journal of Operational Research",
issn = "0377-2217",
publisher = "Elsevier",
number = "1",

}

TY - JOUR

T1 - Maximizing system availability through joint decision on component redundancy and spares inventory

AU - Xie, Wei

AU - Liao, Haitao

AU - Jin, Tongdan

PY - 2014/8/16

Y1 - 2014/8/16

N2 - For a repairable k-out-of-n:G system consisting of line-replaceable units, its operational availability depends on component reliability, its redundancy level, and spare parts availability. As a result, it is important to consider redundancy allocation and spare parts provisioning simultaneously in maximizing the system's operational availability. In prior studies, however, these important aspects are often handled separately in the areas of reliability engineering and spare parts logistics. In this paper, we study a collection of operational availability maximization problems, in which the component redundancy and the spares stocking quantities are to be determined simultaneously under economic and physical constraints. To solve this type of problem, continuous-time Markov chain models are developed first for a single repairable k-out-of-n:G system under different shut-off rules, and some important properties of the corresponding operational availability and spare parts availability are derived. Then, we extend the models to series systems consisting of multiple repairable k-out-of-n:G subsystems. The related optimization problems are reformulated as binary integer linear programs and solved using a branch-and-bound method. Numerical examples, including a real-world application of automatic test equipment, are presented to illustrate this integrated product-service solution and to offer valuable managerial insights.

AB - For a repairable k-out-of-n:G system consisting of line-replaceable units, its operational availability depends on component reliability, its redundancy level, and spare parts availability. As a result, it is important to consider redundancy allocation and spare parts provisioning simultaneously in maximizing the system's operational availability. In prior studies, however, these important aspects are often handled separately in the areas of reliability engineering and spare parts logistics. In this paper, we study a collection of operational availability maximization problems, in which the component redundancy and the spares stocking quantities are to be determined simultaneously under economic and physical constraints. To solve this type of problem, continuous-time Markov chain models are developed first for a single repairable k-out-of-n:G system under different shut-off rules, and some important properties of the corresponding operational availability and spare parts availability are derived. Then, we extend the models to series systems consisting of multiple repairable k-out-of-n:G subsystems. The related optimization problems are reformulated as binary integer linear programs and solved using a branch-and-bound method. Numerical examples, including a real-world application of automatic test equipment, are presented to illustrate this integrated product-service solution and to offer valuable managerial insights.

KW - Operational availability

KW - Performance-based contracting

KW - Redundancy allocation

KW - Repairable k-out-of-n: G system

KW - Spare parts logistics

UR - http://www.scopus.com/inward/record.url?scp=84898811513&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84898811513&partnerID=8YFLogxK

U2 - 10.1016/j.ejor.2014.02.031

DO - 10.1016/j.ejor.2014.02.031

M3 - Article

AN - SCOPUS:84898811513

VL - 237

SP - 164

EP - 176

JO - European Journal of Operational Research

JF - European Journal of Operational Research

SN - 0377-2217

IS - 1

ER -