Purpose
You use lot size planning to specify which demand quantities are to be made available in which buckets (periods). You can choose to do one of the following:
To procure or produce the exact demand quantities of a product. The order size corresponds to the demand quantity.
The main advantage of this method is the low storage costs. Its disadvantages include high costs for procurement and setup.
To group several product demand quantities from consecutive buckets into larger procurement lots or production lots. With this method, procurement or production is done in advance and you can make use of the economy of scale cost savings.
The advantages of this method include low procurement and setup costs. Its main disadvantage is the high storage costs.
The SNP optimizer uses all the costs to determine the optimal (most cost-effective) procurement lot sizes, production lot sizes, and transportation lot sizes. For finite capacity planning with the SNP optimizer, both costs and available capacities are relevant for lot size planning.
Increased setup consumption and/or higher setup costs can be taken into account during planning or rough-cut planning in Supply Network Planning (SNP) for integration with the subsequent Production Planning and Detailed Scheduling (for example, SAP APO Production Planning and Detailed Scheduling, PP/DS
). This makes it easier for Production Planning and Detailed Scheduling to create feasible plans.
Prerequisites
The prerequisites for lot size planning are the same as those for general optimization-based planning:
Lot Size Planning for Production
When using the SNP optimizer for lot size planning in production, you can model both setup consumption and setup costs in the system. You can also influence lot size planning by defining minimum lot sizes, maximum lot sizes, and discrete (integer value) lot sizes.
Setup Consumption
You can choose any of the following three options for modeling setup consumption in the system:
If the past setup consumption amount per bucket is known to you, you can model setup consumption by reducing the available capacity of the production resource accordingly. If the setup consumption remains the same across all buckets, you can reduce the rate of the resource utilization in resource master data. For example, for a setup consumption of 20%, enter a bucket capacity utilization rate of 80%.
If setup consumption varies across the different buckets, you can reduce the standard capacity for individual buckets accordingly.
In this instance, you can choose the linear optimization method for the optimization run, meaning that discretization is not required.
If the setup consumption level is not known but setup consumption is relatively low in comparison to bucket capacity, you can define setup consumption in the PPM as a fixed bucket resource consumption.
In order for the optimizer to be able to take into account the fixed resource consumption defined in the PPM, you must define a discretization horizon in the
Fixed Material and Resource Consumption
field
of the SNP optimizer profile. You also have to choose the discrete optimization method in this profile.If the setup consumption level is not known and setup consumption is relatively high in comparison to bucket capacity, you can run cross-period lot size planning. For more information, see Cross-Period Lot Size Planning .
Setup Costs
The optimizer primarily uses setup and storage costs as a basis for determining optimal lot sizes and lot numbers. If setup costs are high and storage costs low, the optimizer is most likely to plan large lots whereas if setup costs are low and storage costs high, it will plan small lots.
You can define the setup costs as fixed costs within the PPM cost function (choose the Maintenance
pushbutton near the Cost Profile
field and enter the setup costs in the Fixed costs
field). You must also choose the discrete optimization method in the SNP optimizer profile and enter a discretization horizon in the PPM Execution
field within the Discrete Constraints
tab.
If you want to perform sequence-dependent lot-size planning, the optimizer takes into account setup transitions, setup costs, and setup times that you have defined in a setup matrix. This allows you to optimize your setup costs. For more information, see Sequence-Dependent Lot-Size Planning .
Integration
If you have integrated SNP and PP/DS planning (the SNP PPM and PP/DS PPM are linked), the optimizer takes into account setup statuses from PP/DS. This means that the optimizer does not take into account setup consumption and setup costs if a PP/DS order for the associated PP/DS PPM already exists in the corresponding bucket. If you want to have this integration, you must set the Cross-Period Lot Size Planning
indicator (for Cross-Period Lot Size Planning ) or the Lot Size Planning: Not Cross-Period
indicator (if your lot size planning is not cross-period) on the Integration
tab page in the SNP optimizer profile.
Minimum and Maximum Lot Sizes
If, due to technical constraints for instance, a minimum or maximum lot size is required for your production (for example, at least one entire tank of active ingredient must be produced), you can define minimum and maximum lot sizes.You can choose one of the following two options for defining these minimum and maximum lot sizes:
You define the minimum and maximum lot size in the PPM.
You define the minimum lot size on the
Lot Size
tab page in location product master data in conjunction with theFixed Lot Size
orLot-for-Lot
lot-sizing procedure. The SNP optimizer takes these settings into account for integration purposes (with PP/DS, for example). The minimum lot size defined in the product master applies to all the PPMs that use this product as the header material. If the minimum lot size in the product master is larger than the minimum lot size in the PPM, the optimizer takes into account the value from the product master. The maximum lot size defined in the product master has no relevance for the SNP optimizer.Fixed lot size: The SNP optimizer considers the value you specified for the fixed lot size as the minimum lot size. Per PPM execution, the PPM output quantity (the output component quantity) is the same as this fixed lot size.
Lot-for-lot: The optimizer takes into account the minimum lot size defined in the location product master as the minimum lot size.
In order for the SNP optimizer to be able to take into account the minimum lot sizes defined in the PPM or location product master, you must also choose the discrete optimization method in the SNP optimizer profile and enter a discretization horizon in the Minimum PPM Lot Size
field within the Discrete Constraints
tab. The optimizer also takes into account the maximum PPM lot size defined in the PPM when the linear optimization method has been chosen. For this, you must set the Maximum PPM Lot Size
indicator from the General Constraints
tab of the SNP optimizer profile.
Discrete (Integer Value) Lot Sizes
If, due to technical constraints for instance, you can only produce integer multiples of a lot (for example, you can only produce entire tanks of active ingredient and not 1.5 tanks), you can set the Discretization
indicator in the PPM. In order for the optimizer to be able to consider this indicator, you must also choose the discrete optimization method in the SNP optimizer profile and enter a discretization horizon in the Integral PPMs
field within the Discrete Constraints
tab. If you do this, the optimizer always plans production in integer multiples of the output component quantity.
Defining a fixed lot size or lot-for-lot in the Lot Size
tab of the location product master data for integration reasons (with PP/DS, for instance) has the following implications:
Fixed lot size: Per PPM execution, the SNP optimizer always sets the output quantity in the PPM to the value you entered for the fixed lot size.
Lot-for-lot: Every time the PPM is executed, the SNP optimizer sets the output quantity in the PPM to the value you entered in the
Rounding Value
field (on theLot Size
tab page) of the location product master.
The quantity of input components and amount of resource consumption are adjusted accordingly. Since you can also use the lot sizes defined in the location product master when creating PP/DS orders, you can plan with greater precision.
Lot Size Planning for Transportation
Fixed Means of Transport Costs
As with setup costs for production, the SNP optimizer primarily uses fixed means of transport costs as a basis for determining optimal transportation lot sizes. If these costs are high, the optimizer is most likely to plan larger transportation lots (meaning less shipments; once every two weeks, for example).
You can define these fixed means of transport costs in the Means of Transport
section of the transportation lane. In the CostFunctn
field, specify a transportation cost function, for which you have defined fixed costs. You must also choose the discrete optimization method in the SNP optimizer profile and enter a discretization horizon in the Means of Transport
field within the Discrete Constraints
tab.
Minimum and Maximum Lot Sizes
You can define minimum and maximum lot sizes for transportation in the SNP lot size profile (transportation lanes). You then specify this lot size profile for a particular product in the Product-Specific Means of Transport
section of the transportation lane. You can thus define minimum and maximum transportation lot sizes for specific products.
In order for the optimizer to be able to consider the defined minimum lot size, you must choose the discrete optimization method in the SNP optimizer profile and enter a discretization horizon in the Minimum Transport Lot Size
field within the Discrete Constraints
tab. If you set the Maximum Transportation Lot Size
indicator of the General Constraints
tab page in the SNP optimizer profile, the SNP optimizer also takes the maximum transportation lot size into account when the linear optimization method is chosen.
Discrete (Integer Value) Transportation Lots and Means of Transport
If you only want to transport integer multiples of a transport lot size (entire pallets of a product only, for example), you can define that you want the optimizer to take this into account during planning, by choosing the discrete optimization method in the SNP optimizer profile and by entering a discretization horizon in the Integral Transport Lots
field of the Discrete Constraints
tab. You usually define the transportation lot size as a rounding value in the SNP lot size profile (transportation lanes). Alternatively however, you can set in the Maintain Global SNP Settings
activity in Customizing for SNP that the optimizer is to use the rounding value defined in the destination location’s location product master as the transportation lot size.
Similarly, you can define that you want the optimizer to plan means of transport only in integer values, by only scheduling whole trucks for a shipment, for example. To do this, enter a discretization horizon in the Integral Means of Transport
field.
Lot Size Planning for Procurement
Fixed Procurement Costs
As with setup costs for production and fixed means of transport costs for transportation, the SNP optimizer primarily uses fixed procurement costs as a basis for determining optimal lot sizes for procurement. If these costs are high, the optimizer is most likely to plan large procurement lots (meaning less procurement operations; once every two weeks, for example).
You can define these fixed procurement costs on the Procurement
tab page of the location product master. In the Cost function
field, specify a procurement cost function, for which you have defined fixed costs. You must also choose the discrete optimization method in the SNP optimizer profile and enter a discretization horizon in the Procurement Quantity
field on the Discrete Constraints
tab page.
Minimum, Maximum, and Integral Lot Sizes
At present, the SNP optimizer cannot take into account minimum, maximum, and integer value procurement lot sizes during lot size planning. However, there is a workaround for modeling these lot size constraints:
First create your supplier as a location in your model
Create a transportation lane between the supplier and the demand location
You can now model the procurement lot size constraints as transportation lot size constraints (see the section on
Lot Size Planning for Transportation
)
See also:
For more information about optimization-based planning and its execution, see:
