sap optimization
DESCRIPTION
SAP OptimizationTRANSCRIPT
Optimization
Supply Chain Planning Using Optimization
Optimization
Introduction to Optimization Models
Optimization
Optimization-Based Planning Models
• In constraint-based planning, production processes can be represented as optimization models.
• A production model based on optimization consists of Objective Function(s), Decision Variables, and constraints based on market conditions, physical processes, and resources/capacity.
• These kinds of models are usually called mathematical programs.
Optimization
Decision Variables
• Decisions variable are the independent variables of the problem. Typically, decisions take the form of Production lot sizes, Transport lot sizes, Purchase of additional capacities and so on.
• Examples of Decisions Variables:– How much do we invest in new machines?– How much do we spend in labor?– How many units to make?– Repair or replace?
Optimization
Objective Functions
• The Objective Function is the single benchmark for evaluating all combinations of decisions that satisfy the constraints. It usually represents a quantifiable goal, and sometimes 2 or more goals.
• Examples of Objective Functions:– Minimize total production costs– Minimize total material costs– Maximize total sales revenue– Minimize total inventory costs– Minimize total lead time
Optimization
Constraints
• Constraints represent limitations on which decision can be made and how decisions can be made. For example, the production capacity is 5000 Units/day.
• Constraints are also used to apply business rules when solving a problem. For example, all inventory must be non-negative.
• Other examples of constraints:– Market conditions/demand– Material/supplies– Capacity/resources– Transportation/logistics– Policy/managerial
Optimization
Steps for Constructing a Planning Model
• Typically, a simplified production model comes from performing VAT analysis on the existing production process that we want to model.
– What are the decisions variables?
– What are the constraints?
– What is the objective function?
Optimization
Objectives DecisionVariables
Constraints
SNP,Distribution& PP
Lateness,Storage Costs,Transportation Costs,Production Costs,Purchase of additional CapacitiesProduction Resources,Transportation (Fleets)Products
LatenessProduction Lot SizesTransportation Lot SizesPurchase of AdditionalCapacities
Production CapacitiesTransportation CapacitiesHandling CapacityDue DatesSafety StockDiscrete ValuesProduction Lot Size,Transportation Lot Size,Extra Shifts
DS LatenessMakespanSetup Costs
Resource Allocation(AlternativeMachines/Storage)Start DatesNOT Lot Sizes orAlternative Recipes
Time Constraints (maximal duedate, shelf life – Minimalproduction stages, campaign)Due DatesSetup Times,ProductivityResource networkCalendarShifts,Effectivity of receipts
Objective Functions, Decision Variables, Constraints in APO
Optimization
SNP Optimization
One time period (bucket)
Demand at a location
Dependent demand at a location
Processing flow
Optimization
Optimization of the Network
ForecastsCustomers orders
ForecastsCustomers orders
Sourcing production &purchasing
requirements
Sourcing production &purchasing
requirements
Priorities for:demand typesdefined viacosts
Control costsPenalty costs
$
Goal: Minimize costs
Goal: Maximize Profits*
Optimization
Optimization Methods
• Linear Programming– Continuous Linear Optimization Problems
• Primal Simplex Method• Dual Simplex Method• Interior Point Method
– Discrete Linear Optimization Problems• Mixed Integer Linear Programming
• Prioritization
• Decomposition
• Vertical Aggregated Planning
• Horizontal Aggregated Planning
Optimization
Optimization Methods
• Discretization
– Discretization until a certain date*
– Detailed Discretization for different restrictions for daily, weekly, or monthly buckets*
– Maintain discretization in PPM or transportation lane individually
Optimization
• Decision Variables– Production lot sizes– Transportation lot sizes– Capacity increase
• Objectives– Lateness – Storage costs – Transportation costs – Production costs– Penalty for increasing
capacity– Penalty cost for not
maintaining safety stock*– Penalty cost for late or
non delivery*
Optimization Parameters
• Constraints– Production capacities– Transportation capacities– Handling capacity– Due dates (demands)– Safety stock– Discrete Values
• Production Lot Size• Transportation Lot Size
Optimization
Cost Maintenance function
$
UseUse this function to maintain all costs used by the Optimizer and assigned to the master data from a single point of access. If you maintain the costs using this function, the master data for the selected planning version is automatically updated.
IntegrationThis function integrates costs assigned to PPM, Resource, and Product master data. These costs include Production, Handling, Storage, Transportation, Procurement, and Delay/Non-Delivery costs.
Optimization
Optimizer Profile
30
Costs Due date violation
Optimization
Optimizer Profile
A
A BCD
Storage CapacityTransport Capacity
Handling Capacity
Production Capacity
Safety Stock Violation
Determines which constraints are
considered
Other Constraints
Optimization
SNP Cost Profile
A
A BCD
$0 1 2 x
Penalty for fallingbelow the minimum
safety stock limit
Penalty for fallingbelow the minimum
safety stock limit
Optimization
Optimization Bound Profile*
• Specifies the time buckets where the new plan is constrained by an upper and lower limit on the allowable change.
• For example, you change the plans in the first month only within 10% of the original value. The basis for the change is the last optimization run for the same planning area
Optimization
Optimization Run - Interactive Planning Desktop
• Range of location products can be selected.
• Predefined Optimizer profiles can be selected
• Changes to the predefined profiles is allowed
Optimization
Costs in the APO Environment (I)
• Model considers the following costs:– Higher non-delivery cost results in:
• forced production– Higher relative storage cost results in:
• moving products from one location to another ahead of requirement
– Higher delay cost results in:• control lateness/build early scenarios
– Maximum delay used to:• control number of days demand fill is delayed by
– Transportation cost used to:• prioritize source location
• Costs are Interdependent!
Optimization
Costs in the APO Environment (II)
• To specify a site manufacturing priority: Production cost in preferred site Transportation cost from preferred site
• To influence inventory storage location: Relative storage costs between sites
• To ensure meeting inventory targets: Safety stock violation penalties
Optimization
Costs in the APO Environment (III)
• To meet delivery date early/late– Meet Early:
Delay Cost Storage Cost
– Meet Late: Maximum Delay Allowed Delay Cost Storage Cost
• To use stock before build Storage Cost
• To prioritize a site for downstream supply– Vary Transportation Cost
Optimization
SNP Decisions
Optimization
Optimization Total Costs
Total Cost (Sum Total) Source of cost data
Production PPM
Storage Resource
Production resource expansion Resource
Storage expansion Resource
Penalty cost for safety stock Cost Profile
Transport cost Resource
Transport capacity expansion Resource
Penalty for non-delivery Master data
Handling capacity expansion Resource
Procurement costs Master data
Delay Penalty Master data
Optimization
Relevant Costs for the Optimizer
Resource costs Standard (variant 1) Increase (variant 2)
Additional costs
ProductionTransportTransport (mat)StorageStorage (mat)Handling
(X)X
(X)X
XX
X
X
PPM-header: Variable costs
Safety stock: Penalty (cost profile)
Material priority: Late delivery (penalty)
Non delivery (penalty)
Optimization
Product Master Data: Global Data
• Penalty Costs for Requirements and Customer Forecast– Penalty costs for non-delivery– Penalty costs for delayed delivery– Maximum allowed delay (in days)
$
Salesorder
Fore-cast
30
Optimization
Input Parameters for SNP Optimization Run
• Planning Version
• Level ID
• Product and Location
• Planning Book and Data View
• Planning Start and End Date
• Optimizer and Cost Profile
• Optimizer Bound Profile
• Modify Quota Arrangement
Optimization
SNP Optimization Run Results
• Distribution Plan
• Production Plan
• SNP Resulting Costs
• Alerts