Obsolescence Forecasting Methodologies – An Overview

12 Aug 2013
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To successfully operate obsolescence management, the ability to forecast obsolescence events for parts that are needed to manufacture or sustain a product is essential. Past trends are a valid indicator of the future. As a consequence algorithms developed by using data mining based forecasts can be helpful for obsolescence forecasting. Generally, a distinction can be made between forecasting for parts with evolutionary parametric drivers and for parts without evolutionary parametric drivers.

Parts with Evolutionary Parametric Drivers

An evolutionary parametric driver is a parameter describing a part that evolves over time (e.g. memory size for memory chips). An advantage of forecasting is that there is an existing and well documented history of part introductions and discontinuances that can be used as a historical data base. This methodology is applicable to parts that have clearly identifiable evolutionary parametric drivers.

This method develops a product life cycle curve and can be used to measure a component’s maturity level with respect to the marketplace. Product life cycle curves generally divide the life cycle of a product into the following stages: introduction, growth, mature, decline, phase-out, and obsolescence. To generate the life cycle curve not only technological attributes (e.g. memory density, part supply voltage, package style), but also statistical analysis of sales data for the market are applied. Moreover, an overall risk factor regarding component risk, market share, manufacturer specific marketing behavior and market trends are involved.

Parts without Evolutionary Parametric Drivers

However, most parts do not have a clear evolutionary parametric driver, since they do not evolve over time (e.g. diodes, transistors, multiplexer, buffers). In this case algorithms are generated to predict the part`s procurement lifetime (the time a part was/ will be available for procurement from its original manufacturer) which is the time between introduction date and obsolescence date. For this purpose databases of previous obsolescence events and introduced parts that have not gone obsolete are used to estimate the predicted date of obsolescence. The part databases contain information about past introduction dates of all parts of a particular type and obsolescence dates, if obsolescence has occurred yet.

Although both forecasting methods are quite reliable indicators for the occurrence of obsolescence, there are some factors that cannot be taken into account. In some cases, particular technologies or parts may be displaced by some unforeseen new disruptive technology, thus accelerating the obsolescence of the existing parts faster than what the historical record would forecast. Furthermore, new solutions may appear that extend or create demand for specific technologies or parts. In addition, unpredictable factors like environmental influences, sudden economic changes or political restrictions complicate a guaranteed prediction of obsolescence.

Last modified on Monday, 12 August 2013 16:29
Lisa Schiermeier

Lisa Schiermeier is studying industrial engineering at the Deggendorf Institue of Technology (DIT). As an intern at ABSC GmbH, she gained insights into the comlexity of obsolescence management, how obsolescence occurs, how it can be handled and prevented in the future.

As an innovative full service system integrator in the fields of engineering services and IT services ABSC GmbH supports many international companies along their development and operation of business processes with complete solutions since over 20 years. ABSC creates customized and innovative obsolescence management concepts and provides competent, reliable and sustainable optimization of processes, projects and infrastructure. ABSC supports businesses as long-term partner for the definition and implementation of customer specific complete obsolescence management solutions and round off their range of services with specific seminars and events.

Website: www.obsolescence-management.net

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