Demand Fulfilment and ATP

A decision support tool for the order promising process with product homogeneity requirements in hybrid Make-To-Stock and Make-To-Order environments. Application to a ceramic tile company

“…In the literature methods for ATP calculation and consumption can be found in Fogarty, Blackstone and Hoffmann (1991). Kilger and Meyr (2008) affirm that ATP is expressed in terms of items storage at the decoupling point: finished goods in MTS, components in ATO and raw materials in MTO. Besides ATO and MTO companies checking the ATP of items at the decoupling point, they need to check if there is enough uncommitted production capacity (CTP) for either assembly or producing FG, respectively, to fulfil customer orders.…”

“…Hence ATP may be linked to existing products, while CTP relates to the capacity to produce (Framinan & Leisten, 2009). However, CTP is often included in ATP functionalities (Kilger & Schneeweiss, 2000).…”

Simulation of Allocation Policies for a Serial Inventory System Under Advance Demand Information

“…Available to Promise (ATP) is an alternative to ADI that addresses order fulfilment problems. Kilger and Meyr (2008) have proposed an ATP search method to allocate orders to customers. Meyr (2009) further proposes ATP allocation for different customer classes with the basic idea that ATP is held back in anticipation of later arriving, more profitable orders even if a less profitable order already requests the product stock.…”

Managing stock‐outs effectively with order fulfilment systems

“…Allocation decisions are based on a penalty cost parameter that includes costs for backlogging, early allocation and order denial. Kilger and Schneeweiss (2000) give an overview of the order allocation functions provided by commercial order fulfilment systems. They point out that order allocation is typically performed on the basis of a set of heuristic allocation rules that can be customized to accommodate company specific requirements.…”

“…Pre‐allocation of available to promise inventory to distinct classes of customers or individual customers can be employed to mitigate the problems associated with myopic allocation mechanisms. Commercial order fulfilment systems provide so‐called “allocation planning” functions, which apply certain rules to pre‐allocate available to promise quantities to sales regions and customer classes (Kilger and Schneeweiss, 2000). A typical pre‐allocation scheme would, for example, employ a fixed split policy to first allocate overall available to promise quantities to sales regions and would then assign the regional quantities to individual customers or customer classes based on customer priorities.…”