System element obsolescence replacement optimization via life cycle cost forecasting

    Research output: Contribution to journalArticlepeer-review

    4 Scopus citations

    Abstract

    Both commercial and noncommercial systems must manage their system effectiveness through the acquisition and operational stages of their life cycles. Once the system design baseline is defined and instantiated, then the challenge is to affordably sustain the physical system elements (SEs), which evolve in response to changing external influences. These influences may include frequent asynchronous SE obsolescence (hardware and software), increased functional requirements, or even external system regulatory changes (i.e., security, import and export laws, and safety standards). This paper specifically addresses the influence of SE obsolescence within a system life cycle. It proposes a model to optimize for the affordability of changes through a defined system life cycle by forecasting SE revisions. Firstly, each system element is described by a unique SE life cycle curve, and secondly, this curve forecasts the possible obsolescence revision sequences through a selected system life cycle. Models are proposed for the system element life cycle curve and the obsolescence revision sequencing. These models are particularly useful in situations where the SEs are independent of one another within a defined system context. In this way, optimized SE changes can be deployed to maximize the operational effectiveness of the system through its life cycle.

    Original languageEnglish
    Article number6226836
    Pages (from-to)1394-1401
    Number of pages8
    JournalIEEE Transactions on Components, Packaging and Manufacturing Technology
    Volume2
    Issue number8
    DOIs
    StatePublished - 2012

    Keywords

    • Cost optimization
    • diminishing manufacturing sources and material shortages (DMSMS)
    • obsolescence
    • system life cycle
    • system refresh

    Fingerprint

    Dive into the research topics of 'System element obsolescence replacement optimization via life cycle cost forecasting'. Together they form a unique fingerprint.

    Cite this