Intended learning outcomes: Explain available-to-promise (ATP) and the determination of ATP quantities. Produce an overview on the techniques of multilevel available-to-promise (MLATP) and capable-to-promise (CTP).
For the short-term planning of customer orders (here see Figure 5.1.3.1) the detailed resource requirements calculation must answer the question of whether a given quantity of a product will be available at a given time. The way to do this is by using predictive simulation with the available-to-promise or capable-to-promise procedures, which use some of the detailed planning techniques discussed in Section 5.3. This way is even necessary when customer orders are not covered by long-term or medium-term demand forecasts. The available times will not be known until all the resource requirements are covered, possibly through new planned orders, which then leads to confirmation and to approval of the customer order.
(Order) backlog is all the customer orders received but not yet shipped. Sometimes referred to as open customer orders (cf. [ASCM22]).
Available-to-promise (ATP) is the uncommitted — that is not yet assigned to an open customer order — portion of a company’s inventory and planned production (cf. [ASCM22]).
The ATP quantity is maintained in the master schedule to support customer-order promising. It is normally calculated for each event or each period in which an MPS receipt is scheduled ([ASCM22]). However, it is cumulative ATP that is of practical importance. Figure 5.3.5.1 illustrates the definition and calculation of discrete ATP and cumulative ATP.
Fig. 5.3.5.1 Determination of ATP quantities.
We will begin formal calculation of ATP quantities with some definitions:
For i = 1, 2, …, let
.... ATPi º ATP of period i.
.... ATP_Ci º cumulative ATP of period i.
.... MPSi º MPS quantity of the period i.
.... QAi º quantity allocated to customer orders in period i.
Now, let ATP_C0 and ATP0 be equal to the physical inventory. According to the definition above, the following algorithm, done subsequently for i = 1, 2, …, yields the ATP quantities.
ATP_Ci = ATP_Ci-1 + MPSi – QAi .
j = i
While ATP_Cj < ATP_Cj–1 and j>0, revise the ATP quantities as follows:
.... ATP_Cj–1 = ATP_Cj
.... ATPj = 0.
.... j = j–1
end (while).
If j > 0, then ATPj = ATP_Cj – ATP_Cj–1 .
If j = 0, then ATP0 = ATP_C0 .
In our example, for the product PR, seven units are available-to-promise from stock. Two additional units become available-to-promise in period 2.
Determining ATP quantities supports decision making regarding whether and for which due dates an order can be accepted. For make-to-stock-products, order promising is a direct consequence of comparing the order quantity with the ATP quantities. For more detailed information on availability and calculating projected available inventory, see Section 12.1.A small exercise: Taking the example in Figure 5.3.5.1, determine whether 8 units can be promised for period 1. Also, how would you promise delivery of an urgent order of 10 units to an impatient customer waiting on the phone for your answer?
For make-to-order or assemble-to-order products, the processes are more complicated than in the calculation shown above, and cannot be shown in a simple overview. Two options are discussed in depth below, and references are given for more detailed information.
For components with insufficient inventory, the multilevel available-to-promise (MLATP) check uses an explosion of product structures by means of the MRP technique according to Sections 5.3.2 and 12.3. Thereby, the lead-time offset of the dependent demand is a lot-size independent production lead time (variant 1 in Figure 12.3.3.1).
The capable-to-promise (CTP) technique develops the classic MRP technique for checking availability by adding in not just stock levels but also capacity and other resources, possibly even for suppliers. For determining the timing of dependent demand, routing sheets are used, and the production lead times can be selected according to the lot size (variant 2 in Figure 12.3.3.1). For availability testing of the capacities, the classical order-oriented finite loading according to Section 5.3.4 and 14.3.2 or finite forward scheduling according to Section 15.2.2 can be applied.
It is evident that MLATP gives quicker results, but CTP gives more accurate results.
Course section 5.3: Subsections and their intended learning outcomes
5.3 Introduction to Detailed Planning and Execution
Intended learning outcomes: Disclose basic principles of materials management, scheduling and capacity management concepts. Produce an overview of materials management, scheduling and capacity management techniques. Differentiate between available-to-promise and capable-to-promise.
5.3.1 Basic Principles of Materials Management Concepts
Intended learning outcomes: Present the objectives of materials management. Differentiate between deterministic materials management and stochastic materials management. Differentiate between independent demand and dependent demand. Produce an overview on quasi-deterministic materials management, fill rate, stockout, backorder.
5.3.1b The Cumulative Fill Rate
Intended learning outcomes: Explain and experience the cumulative fill rate.
5.3.2 Overview of Materials Management Techniques — Kanban, Order Point Technique, Cumulative Production Figures Principle (CPFP).
Intended learning outcomes: Disclose the basic classification of detailed planning techniques in materials management. Produce an overview on techniques such as Kanban, order point technique, and CPFP (cumulative production figures principle).
5.3.2b Overview of Materials Management Techniques — Customer Order and Material Requirements Planning (MRP)
Intended learning outcomes: Explain the additional classification for unique demand or demand for high-cost items with a discontinuous demand pattern. Produce an overview on techniques such as Kanban, order point technique, CPFP (cumulative production figures principle), and MRP (material requirements planning).
5.3.3 Basic Principles of Scheduling and Capacity Management Concepts
Intended learning outcomes: Present the objectives of the tasks as well as the overall objective of scheduling and capacity management. Describe the vicious circle caused when capacity bottlenecks prolong the planned production lead-time.
5.3.3b The Overall Objective of Scheduling and Capacity Management
Intended learning outcomes: Present the overall objective of scheduling and capacity management. Disclose to which extent capacity can be stored.
5.3.4 Infinite Loading and Finite Loading
Intended learning outcomes: Differentiate between infinite loading and finite loading. Explain the classification of techniques for capacity management in dependency upon flexibility of capacity and flexibility of order due date.
5.3.4b Overview of Scheduling and Capacity Management Techniques
Intended learning outcomes: Produce an overview on order-oriented infinite loading, order-wise infinite and finite loading, operations-oriented and order-oriented finite loading, constraint-oriented finite loading, load-oriented order release (Loor), capacity-oriented materials management (Corma).
5.3.5 Available-to-Promise (ATP) and Capable-to-Promise (CTP)
Intended learning outcomes: Explain available-to-promise (ATP) and the determination of ATP quantities. Produce an overview on the techniques of multilevel available-to-promise (MLATP) and capable-to-promise (CTP).
