概要
A single bill of materials can hold hundreds of components, each on its own path toward obsolescence, and evaluating that risk part by part is slow and error-prone. BOM Lifecycle Forecasts rolls the analysis up to the BOM level: upload your bill of materials and see what percentage stays Active, drifts to NRND, or reaches end-of-life at 2, 5, and 10 years out. The model uses Z2's lifecycle algorithm, derived from the CALCE methodology developed at the University of Maryland, with over 90% historical accuracy.
Most lifecycle data gives you one part's status at a time. That does not answer the question a program manager asks: how much of this design stays buildable in five years? BOM Lifecycle Forecasts aggregates the projected end-of-life date for every line and reports the share that is Active, NRND, and End of Life at each horizon, so a design that looks healthy today but leans on aging parts no longer hides that exposure. Z2 matches every BOM you upload against its 1B+ component database with no manual data collection: you bring the bill of materials, and the platform returns the lifecycle trajectory for the whole product.
The forecast runs on an algorithm developed by Peter Sandborn at the University of Maryland's Center for Advanced Life Cycle Engineering (CALCE), a broadly accepted method for estimating obsolescence that Z2 continuously refines. It weighs last-time-buy and discontinuance notices, the date a part was introduced, its technology generation and part family, market demand, part activity, and the number of active sites still producing it, combining them into a projected end-of-life date. Notices alone are not enough: roughly 30% of component discontinuations get no PCN, so the change lands with no notification at all. A forecast grounded in part activity and technology trends surfaces that hidden risk before it stalls production, with over 90% historical accuracy.
The value of a forward-looking forecast is timing. A bridge buy, a last-time buy, or qualifying a cross-reference all take months to execute. Seeing that 18% of a BOM is projected to reach end-of-life within five years, before the design is frozen, gives sourcing and engineering room to act while alternatives still exist and before the secondary market sets the price. Late awareness forces redesigns and premium last-minute buys; an early forecast turns obsolescence into a scheduled activity.
Forecast output is built to leave Part Risk Manager. Export a structured lifecycle report engineering can work line by line, then roll the same data into the high-level view leadership needs for program decisions. The forecast refreshes automatically whenever any part changes lifecycle status, so the report reflects the current BOM, not a one-time snapshot. Pre-built reports like High Lifecycle Risk Parts isolate the components driving the most exposure.
機能
BOM Lifecycle ForecastsはZ2DataのPart Risk Managerに搭載された機能の一つであり、the industry's largest component intelligence platform. Search and score 1B+ parts across obsolescence, compliance, sourcing, and supplier risk, all in one view.
よくあるご質問
Z2's lifecycle algorithm holds over 90% historical accuracy, measured against actual end-of-life outcomes for parts it previously projected. It is based on the obsolescence-estimation methodology developed by Peter Sandborn at the University of Maryland's CALCE program and continuously refined by Z2.
Notifications alone miss much obsolescence: roughly 30% of component discontinuations get no PCN, so engineers find out when stock runs out. The forecast also weighs introduction date, technology generation and part family, market demand, part activity, and the number of sites still producing the part, surfacing risk before a manufacturer formally announces it.
Yes. It is a capability within Part Risk Manager, Z2's component intelligence platform. You upload a BOM, it is automatically matched against the 1B+ database, and the forecast is generated alongside risk scoring, cross-reference search, compliance status, and pricing for every part.
