Day 3 AgendaReview of Day 2 Supply Chain CockpitHeuristicsOptimiser

Day 3 AgendaReview of Day 2 Supply Chain CockpitHeuristicsOptimiser

Day 2 AgendaReview of Day 2Supply Chain CockpitHeuristicsOptimiser

At the end of this Topic, You will be able toExplain the Supply Chain Cockpit functionalityUnderstand the function of Supply Chain Alert MonitorUnderstand the concept of Supply Chain Engineer

Supply Chain Cockpit Objectives

Supply Chain CockpitSupply Chain Alert MonitorSupply Chain Engineer

Supply Chain Cockpit Contents

Supply Chain CockpitSupply Chain Alert MonitorSupply Chain Engineer

Supply Chain Cockpit Contents

Supply Chain Cockpit (SCC) is the central control graphical user interface for modeling, navigation and monitoring of the supply chain covering other area such as demand planning, supply network planning, production planning, deployment planning and transportation planning.Navigate Through Supply ChainMaps / ZoomControl PanelLaunch Applications Focus on Relevant InformationFilters (work areas)Details for a selected objectInformation Retrieval and ResponseDrill-Down & BackQueriesAlertsFunctionalitySupply Chain Cockpit (SCC)

Highly configurable to the conditions within a wide variety of industries and business situationsIntuitive graphical user interface gives user maximum channel visibility to the entire Supply Chain NetworkIntegration with all APO modules through a consistent data model to ensure reliability and planning accuracyFast and direct access to specific information without jumping through multiple screensAn integrated, intelligent Alert Monitor provides specific decision support for problem resolution on all planning levelsSCC Benefits

Supply Chain EngineerModelingAlert MonitorAlert HandlingSupply Chain Engineer enables creating, changing and maintaining the supply chain model.Alert Monitor allows to monitor and manage exceptions and problems with the supply chain model.Navigation ComponentNavigation and Information retrievalSupply Chain Cockpit allows planners to view and navigate the model in subsets and track performanceSCC Components

SCC is the central point of access for all applications of APO and end users who perform various roles use this tool. User profiles allow for the filtering of information which is relevant for the users specific role.SCC Users

Supply Chain CockpitSupply Chain Alert MonitorSupply Chain Engineer

Supply Chain Cockpit Contents

Alert Monitor allows the user to monitor the plan, manage exceptions and problems in the supply chain. SNP planning alerts are exclusively generated through macros.Dynamic Alerts reflect current planning situation and is not suitable for large alert quantities (reduces the performance)Database Alerts reflects planning situation at the time of macros execution and the database alerts are generated in the background and the snapshot can be viewed.

Alert handling:Alert Monitor in SNP allows to display and also remove alerts for resources and location productsAlso the alerts can be configured to be sent over mail to the user.

Alert Monitor

Assignment of alert profile to SCC user profileSelection of alert typesObject selection variants via object typePriority variants (error, warning, information, etc..) with selection variants having thresholds.Alert Profile

Supply Chain CockpitSupply Chain Alert MonitorSupply Chain Engineer

Supply Chain Cockpit Contents

The network model represents a specific supply chain and consists of individual nodes and links. A model can have different planning versions. It is possible to create several models, each with different versions for simulation purposes.Supply Chain Engineer is used to create and maintain models, assign products, resources and PPM's to locations, create and maintain transportation lanes and perform mass maintenance of product attributesSupply Chain EngineerNetwork ControlsNetwork Maps

Pre-requisite is to have master data for locations, products, resources and other elements. Supply chain network is created by placing the locations on the map and creating a connective network with transportation lanes. The lane direction shows the direction of the product transportation flow.Next, we assign products, resources and PPMs to locations using drag and drop functionality. Quota arrangements are defined to determine the percentage of product that will be transported to other locations in the chain.Modelling a Supply Chain Network

Supply Chain Cockpit Vs Supply Chain EngineerThe Supply Chain Cockpit is used to navigate and monitor planning in supply chain models. Must reference a model AND a version A Supply Chain Engineer is used to design/construct a supply chain model. Must reference a modelPrerequisites for using a fully operational SCCCreate master dataCreate a supply chain model in the Supply Chain Engineer Specify version and model you want to work withTo see any transactional data, you must first do a planning runSCC vs. SCE

Exercise 3.1: Model Maintenance in the Supply Chain EngineerCreate Model Last Name_A01 and assign master data to it03.1 APO Supply Chain Cockpit_SCE.doc

Estimated time to completion: 45 minExercise 3.1 Model Maintenance through Supply Chain Engineer

Questions

Review of Day 2Supply Chain CockpitHeuristicsOptimiser

Day 3 Agenda

At the end of this Topic, You will be able toRelease a demand plan to SNPCreate Demand ManuallyRun the SNP heuristicCheck capacity Level capacityUnderstand what if scenarios

SNP Run Using Heuristics

SNP HeuristicsCapacity CheckCapacity LevelingHeuristics Content

SNP HeuristicsCapacity CheckCapacity Leveling

Heuristics Contents

The SNP heuristic performs requirements planning through the entire supply chain network to determine how to satisfy the customer and/or consumer demand.It is part of a repair-based planning process consisting of heuristic, capacity leveling, and deployment.

SNP Heuristic

One time period (bucket)

Demand at a location

Dependent demand at a location

Processing flow

SNP Heuristics

Demand AssignmentThe demand released from DP to each location included in the network.Requirements Planning Sequential planning for each location to determine sourcing requirements.It lumps all requirements for a given material/location combination into one demand for the period (or time bucket). Then, it determines the valid sources and quantity based on pre-defined percentages for each source.Heuristic plan may not be feasible as system assumes infinite capacity and does not consider component availability.Planner must adjust the plan by leveling resource capacity, one location at a time. After the heristics run, the planner checks transportation, handling, storage, and production resource capacity consumption, then levels capacity.Heuristic Demand Planning and Requirement Planning

Factors considered in HeuristicsTransportation Lanes - Movements allowed across the supply chainQuota Arrangements - Percentage of requirements allocated to supply sourcesLot Sizing - Lot for lot, fixed, target days supply, rounding profilesProduction Process Model CalendarsSafety stockScrapPPMsHeuristic considers demand at product/location level, checks inventory, stock in transit and firm production. The process generates demands for intermediate products and raw materials, and for finished productsSNP Heuristic Run

Input Parameters :VersionProducts - all or subsetLocations - for location run only Horizon - start date = current date

SNP Heuristic Run

SNP creates planned production and transport orders in the networkSNP Heuristic Run Scenario

Incoming Quotas

Multi-levelIncludes PPM explosion and performs SNP run for selected end products, components for all locationsPlanning is carried out for the locations specified.NetworkPerforms SNP run for selected products in all locationsPlanning is carried out for the entire network. Location Planning is carried out for the locations specifiedHeuristic Run Models

Data from live Cache is readNetting calculation completedTarget Stock calculatedTarget stock - projected stock = planned quantityLot sizing consideredProcurement type checkedSearch for PPMExplode PPMReceipts createdResource load calculatedHeuristic Processing

Exercise 3.2 : Planning Book Navigation SNP94 Build Selection ProfilesRefer 03.2 SNP Heuristics Selection Profile.doc

Estimated time to completion: 20 minExercise 3.2 Planning Book Navigation

Exercise 3.3: Create an Unconstrained Supply Plan for NOTEBOOKExecute Network and Multilevel Heuristics RunsRefer 03.3 SNP Heuristics run.doc

Estimated time to completion: 60 minExercise 3.3 Create an Unconstrained Supply Plan for NOTEBOOK

SNP HeuristicsCapacity CheckCapacity Leveling

Heuristics Contents

The Capacity Check enables the planner to view the impact of planned orders on resources and to quickly determine whether the plan is feasible or not. If there is a capacity overload situation, the planner has to do simulative planning by manipulating resource utilisation to balance resource usage. Once the changes are saved, the production plan or transportation plan becomes the basis for the daily production schedule.Capacity Check

Capacity is defined as 16 HrsTime Consumption for unit quantity is determined by PPMFor Quantity demand, Capacity Deficiency is Highlighted as overload as ratio of capacity consumed and capacity available in % termsCapacity Check Screen

SNP Heuristics Capacity Check Capacity Leveling

Heuristics Contents

Plan can be adjusted using the following methods Forward shift, Backward shift, Combination of bothIf time based capacity leveling option is chosen, various priority rules have to be chosen whether it is based on decreasing order quantity or increasing order quantitywhether it is based on decreasing or increasing stock range of coverage whether it is based on decreasing product priority or increasing product priorityCapacity Levelling

Modify resource master data Shift order quantities to an alternative resourceChange production and transportation ordersAlternative Methods

Exercise 3.4: Create a Constrained Supply Plan for NOTEBOOKExecute a Capacity Leveling Run against the Multilevel Heuristics Run resultsRefer 03.4 SNP Heuristics Capacity Leveling Run.docUse Resource YY_PL1_RES_NOTEBOOK in Location YY_PL1_OHIO

Estimated time to completion: 60 min

Exercise 3.4 Create a Constrained Supply Plan for NOTEBOOK

Planning Versions and What-If Scenarios

Heuristics Advantages and Drawbacks

Questions

Review of Day 2Supply Chain CockpitHeuristicsOptimiser

Day 3 Agenda

At the end of this Topic, You will be able toExplain the concept of OptimisationExplain how the SNP run is carried out using the SNP OptimiserDefine the relevant costs that are used by the SNP Optimiser to generate a supply planIdentify where the costs are maintainedDescribe how the costs influence the optimisation resultExplain the what-if process in SNP Optimiser

SNP Optimisation Objectives

Optimiser IntroductionSNP OptimiserSNP Optimiser RunSNP Optimiser Contents

Optimiser IntroductionSNP OptimiserSNP Optimiser Run

SNP Optimiser Contents

In constraint-based planning, production processes can be represented as optimisation models.A production model based on optimisation 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.

Optimisation based Planning Models

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?

Optimisation Parameters Decision Variables

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 two or more goals.Examples of Objective Functions:Minimise total production costsMinimise total material costsMaximise total sales revenueMinimise total inventory costsMinimise total lead time

Optimisation Parameters Objective Functions

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 bring common sense to a problems. For example, all inventory must be non-negative.Other examples of constraints:Market conditions/demandMaterial/suppliesCapacity/resourcesTransportation/logisticsPolicy/managerialOptimisation Parameters Constraints

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?F(x,y2)= ASteps for Constructing a Planning Model

Objective Functions, Decision Variables, Constraints in APO

Objectives

Decision Variables

Constraints

SNP, Distribution

& PP

Minimize Costs or Maximize revenue

Lateness

Production Lot Sizes

Transportation Lot Sizes

Purchase of Additional Capacities

Production Capacities

Transportation Capacities Handling Capacity

Due Dates

Safety Stock

Discrete Values

Production Lot Size, Transportation Lot Size,

Extra Shifts

DS

Lateness

Makespan

Setup Costs

Resource Allocation (Alternative Machines/Storage)

Start Dates

NOT Lot Sizes or Alternative Recipes

Time Constraints(maximal due date, shelf life Minimal production stages, campaign)

Due Dates

Setup Times,

Productivity

Resource network

Calendar

Shifts,

Effectiveness of receipts

Optimiser IntroductionSNP OptimiserSNP Optimiser Run

SNP Optimiser Contents

SNP Process Flow

The optimiser uses linear programming methods for planning, such that it simultaneously considers all relevant factors making the entire chain as a single problemThe objective of the optimiser is to find the optimal solution to an equation (target function) in which all the penalty factors defined simultaneously are considered. The objective may be to minimize costs or maximize profits.Since the optimiser assesses alternatives this way, it can determine the best feasible plan on the lowest cost.SNP Optimiser

ForecastsCustomers ordersSourcing, production &purchasing requirementsPriorities for demand types defined via costsControl costsPenalty costs$Goal: Minimize costsThe Optimisation result run does not include pegging of final orders back to the original individual demand because the demands are bucketed.The optimiserconsiders capacity across all locations. The optimiseralso considers all alternative capacity resources globally.The optimiserignores standard storage and transportation costs if product-specific costs have been maintained.The optimiserconsiders all types of capacity constraints, including transportation, production, handling, and storage constraints.Supply Network Optimisation

SNP Optimisation in a Nut Shell

Optimiser IntroductionSNP OptimiserSNP Optimiser Run

SNP Optimiser Contents

Linear Programming techniques:

Basic Solution: Generates a solution based on all available data. Simplex method with continuous variables.Discrete: Generates a solution based on all available data. Simplex method in which certain variables are discrete.Acceleration techniques:

Time Aggregation: Data is added according to times buckets. The nearest time bucket is solved first.Product Decomposition: Product groups are created and the problem is solved group by group.Priority Decomposition: Data are grouped and resolved by prioritizing the high priority problemsIncremental: A subset of products is selected before executing the optimiser.APO uses the standard ILOG solvers for OptimisationOptimisation Engine

Linear ProgrammingBasic SolveMixed Integer Linear ProgrammingDiscreteMeta heuristicsTime AggregationProduct DecompositionPriority DecompositionIncremental

Optimisation Methods

CostsDue date violationOptimiser Profile

SNP Optimiser Profile

Method to consider (Linear vs. Discrete)Constraints to considerProduction, Transportation, Storage, HandlingSafety StockLot sizes, etcTransport CapacityStorage CapacitySafety Stock ViolationHandling CapacityProduction CapacityOptimiser Profile (Cont.)

SNP Cost ProfileWeighs to different cost elements .Optimiser Cost Profile

Model considers the following costs:Higher non-delivery cost results inforced productionHigher relative storage cost results inmoving products from one location to another ahead of requirementHigher delay cost results incontrol lateness/build early scenariosMaximum delay used tocontrol number of days demand fill is delayed byTransportation cost used toprioritise source locationCosts are Interdependent!

Costs in the APO Environment (1 of 3)

To specify a site manufacturing priority: Production cost in preferred site Transportation cost from preferred siteTo influence inventory storage location: Relative storage costs between sitesTo ensure meeting inventory targets: Safety stock violation penalties

Costs in the APO Environment (2 of 3)

To meet delivery date early/lateMeet Early: Delay Cost Storage CostMeet Late: Maximum Delay Allowed Delay Cost Storage CostTo use stock before build Storage CostTo prioritise a site for downstream supplyVary Transportation CostCosts in the APO Environment (3 of 3)

Optimisation Total Costs

Planning VersionProductTime Bucket Profile Start/End DatesOptimiser profileCost ProfileModify Quota Arrangement FlagIndependent Product

Input Parameters for SNP Optimisation Run

Distribution PlanProduction PlanSNP Resulting CostsAlertsSNP Optimisation Run Results

Active Version at time T1Master data and transaction data for version 1Master data and transaction data for version 2Master data and transaction data for version 8Master data and transaction data for version 9Active Version at time T2Simulation Version 1Simulation Version 2Simulation Version 8Simulation Version 9Planning Version and What-If Scenarios

AdvantagesDisadvantagesConsiders entire supply chain as a single problemSimultaneously considers all resources and materials availabilityTakes production, transport, handling and storage costs into consideration

Results are difficult to interpretData maintenance is heavy and complicatedImportant to have accurate cost maintenanceMay propose changes to highly dynamic capacity variantsDifficult to modify proposed plan since interpretation and understanding the reasoning is toughBlack box effectRecommendations for UseSuitable for complex planning scenarios which uses cost as a basis for planningSNP Optimiser Advantages and Disadvantages

Questions

The components of a Supply Chain Cockpit are ___, ___ and ___Two kinds of alerts used by alert monitor are ___ and ___Creating, changing and maintaining the model is a function of Supply Chain CockpitSupply Chain EngineerAlert MonitorWhich of the following should reference a model AND a versionSupply Chain EngineerSupply Chain Cockpit

SCC Knowledge Check

Which of the following about Heuristics is NOT true?It lumps all requirements as demand into a single bucketIt assumes finite capacityResource capacity can be adjustedPPM Explosion is carried out by which of the following Heuristics method?LocationNetworkMulti-levelThe different methods of capacity leveling are ____, ____ and ____

SNP Heuristics Knowledge Check

Goals of Optimiser could be ______or ______State True or FalseOptimiser solution run takes place in APO itselfDiscrete solutions require separate settings in optimiser profileConstraints are defined in Optimiser Cost ProfileOptimiser solves for whole supply chainAcceleration techniques speed up solution finding processFor ensuring safety stock, production storage cost should be _____ than Safety Stock penaltyOptimiser suffers from _____ effectSNP Optimiser Knowledge Check

What are the functionalities of SCC?How is Alert handling done in SNP?What are the pre-requisites for modeling a supply chain network?What are the pre-requisites for using a fully operational SCC?

SCC Recap

What factors are considered during a Heuristics run?How do Quotas work in Heuristics?Differentiate between the types of Heuristics runs?How is Resource Capacity and Loading checked?Explain the concept of Capacity LevelingSNP Heuristics Recap

What are decision variables,objective functions and constraints?What is the basis for Optimiser Run?What are the various acceleration techniques and why are they used?Describe Optimiser profile and Optimiser Cost profileWhat are the output results of the Optimiser?SNP Optimiser Recap

End of Day 3 Q & A

Supply chain cockpit is the control centre for modeling, navigation and monitoring of supply chainSupply chain engineer enables creating, changing and maintaining modelsAlert monitor allows monitoring and managing exceptions and problems in the supply chainHeuristics produces plans assuming infinite capacityThree methods in Heuristics Location, Network and Multi level can be utilizedCapacity leveling adjusts capacity by shifting demand backward or forward or bothEnd of Day 3 Lessons Learned

Optimiser works on linear programming algorithmsOptimiser solves whole supply chain as a single problemWeightage of costs is defined in optimiser cost profileConstraints are defined in Optimiser profileRelative costs between locations or transportation lanes define prioritiesWhat If Scenarios can be done by using multiple planning versions for the same modelEnd of Day 3 Lessons Learned (Cont.)

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Additional Information:*Note: Have students use their last name suffixed with their unique 3 digit alphanumeric course code to name their Models

Exercise Data Naming Convention:The 3 digit alphanumeric suffix is used to create unique data for each student.The alpha character will designate the course. (The Character A will be used by the instructor for both DP and SNP). For the DP session the alpha character is D, and for the SNP session the alpha character is S.Each student will be assigned a 2 digit numeric code as their unique identifier.Example:DESK-Desktop PC for Instructor in DP or SNP: PL1_RES_DESK_A01DESK-Desktop PC for DP Student 01: PL1_RES_DESK_D01DESK-Desktop PC for SNP Student 01: PL1_RES_DESK_S01

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Additional Information:For step 11.1 the instructor should lead the students through an interactive demo of SNP Planning Book navigation. (The students should be login into APO and following along in their planning books during the demo). Script 11.1 is meant to be used as a guide and is not exhaustive of what should be covered in this section.

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This section will introduce the broad concept of mathematical Optimisation. Mathematical Optimisation is the application of mathematical methods to a group of decisions and constraints to find the best possible combination of decisions as measured by a benchmark goal.Mathematical Optimisation is usually the foundation which an APS is built upon. While the algorithms and heuristics are too complex to discuss, we will learn how to solve simple problems.The main difference between Material Requirements Planning (MRP) and constraint-based planning (CBP) is that MRP assumes infinite resource capacities while CBP explicitly takes physical, processes and other constraints into consideration.

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Every Optimisation model must have decision variable. Without it, there is no decision to make and nothing to optimise.Decisions are the root of the problem. Typically, decisions take the form of resource allocation.

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If a production process has no limiting constraints, then it would produce an infinite amount of systems goal and purpose. This would mean infinite revenue. Is this possible?In the theory of mathematical programming, limiting constraints are also referred to as binding constraints. In this class, we use bottlenecks and limiting constraints interchangeably.Note that while eliminating the existing/current constraint(s) improves the process, it may not necessarily make the entire system of production processes most efficient.

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Perform VAT or similar analysis to understand the physical process and then decide what are the decision variables, constraints and its objective function.

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Key Message(s):Select the solution method you want to use to optimise your supply network planning:Basic SolveThe optimiser creates an optimal solution based on all available data. This method is the normal simplex method in which all the variables are continuous.DiscreteThe optimiser creates an optimal solution based on all available data. This method is the same as Basic Solve, except that some variables can be made discrete through the profiles. Transportation can be made discrete through the lot size profile, and Production is made discrete through the production process model.Time AggregationThe optimiser speeds up the solution process by grouping data according to time buckets, solving the problem for the earliest time bucket first, then proceeding sequentially through the remaining time buckets.Product DecompositionThe optimiser speeds up the solution process by building groups of products, and solving the problem one product group at a time according to the specifications in the Window size field of the SNP Optimiser profile.Priority DecompositionThe optimiser speeds up the solution process by grouping according to priorities. The optimiser solves the highest priority problem first, then proceeds sequentially through the remaining prioritised groups.IncrementalThis method enables you to select a subset of products before performing the Optimisation run. Note: The aggregation and decomposition methods speed up the Optimisation process, but they do not necessarily produce the optimal solution.

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Key Message(s):The SNP optimiserconsiders all constraints activated in this profile during the SNP Optimisation run. The following constraints can be switch on: Penalty for safety stock violation Storage capacity (resource type S for the location) Transportation capacity (resource type T for a transportation lane) Material-dependent transportation capacity (resource type T for a transportation lane/material) Handling capacity (resource type H for the location) Lot size limit (material master) Production capacity (resource type P for the location)

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The costs and penalties considered in the Optimisation run have various affects on the results of the run. Some examples are described in this slide.

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Key Message(s):Several parameters need to be set at the start of an SNP Optimisation run:Planning VersionProduct - if planning individual product Time Bucket Profile - to define the bucketing of the data for planningStart/End Dates - to define the planning horizonOptimiser profile Cost profileModify Quota Arrangement flag - to indicate you want the system to determine an optimised quota arrangement based on the products you entered on this screen.Independent of Product flag - to indicate that quota arrangements should be created independently of the product.Select both Modify quota arrangements and Product-independent if you want the system to determine an optimised quota arrangement for all products defined in the model for the planning version you specified on this screen. Result: The system modifies the quota arrangements defined in the SCE. Or, if no quota arrangement is defined, the optimiser creates quota arrangements. The optimiser overwrites the quota arrangements defined in the SCE, but only for the time period specified for the Optimisation run. Additional Information:

Key Message(s):SNP Resulting CostsThe total costs associated with the replenishment solution proposed by the system; the total costs are broken down in the remaining entries in the results screen and are described in this table, including:Total production costsTotal storage costsTotal costs incurred as a result of a requirement to expand storage capacity.Total penalty costs incurred because the safety stock level fell below the specified requirement for safety stockTotal transportation costsTotal costs incurred as a result of a requirement to expand the handling capacity of one or more resources.Total costs incurred as a result of a requirement to expand the transportation resource capacity.Total costs incurred as a result of a requirement to expand the production resource capacity.Total penalty costs incurred as a result of a delivery that is late.Total penalty costs incurred as a result of a delivery of a product that is less than the quantity ordered.Additional Information:Key Message(s):

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Answers to Knowledge Check

Supply Chain Engineer, Alert Monitor and Navigation ComponentDatabase and DynamicSupply Chain EngineerSupply Chain CockpitAnswers to Knowledge Check

bcForward, Backward and Both Forward and Backward

Answers to Knowledge Check

1. Cost Minimisation , Profit Maximisation2. a. False. Goes to ILOG for solution determination and results are returned to APO. b. True c. False d. True e. True3. Less4. Black box Key Message(s):

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