Abstract:

Many technologies have life cycles that are shorter than the life cycle of the product or system they are in. Life cycle mismatches caused by the obsolescence of technology can result in large life cycle costs for long field life systems, such as aircraft, ships, communications infrastructure, power plant and grid management, and military systems. This paper addresses DMSMS (Diminishing Manufacturing Sources and Materials Shortages) obsolescence, which is defined as the loss of the ability to procure a technology or part from its original manufacturer. Forecasting when technologies and specific parts will become unavailable (non-procurable) is a key enabler for pro-active DMSMS management and strategic life cycle planning for long field life systems. This paper presents a methodology for generating algorithms that can be used to predict the obsolescence dates for electronic parts that do not have clear evolutionary parametric drivers. The method is based on the calculation of procurement lifetime using databases of previous obsolescence events and introduced parts that have not gone obsolete. The methodology has been demonstrated on a range of different electronic parts and for the trending of specific part attributes.

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