In applied probability, an assemble-to-order system is a model of a warehouse operating a build to order policy where products are assembled from components only once an order has been made.
[1] Research typically focuses on finding good policies for inventory levels and on the impact of different configurations (such as having more shared parts).
[1] This case is a generalisation of the newsvendor model (which has only one component and one product).
In continuous time orders for products arrive according to a Poisson process and the time required to produce components are independent and identically distributed for each component.
Two problems typically studied in this system are to minimize the expected backlog of orders subject to a constraint on the component inventory, and to minimize the expected component inventory subject to constraints on the rate at which orders must be completed.