Fundamentals of SCP/PP (Supply Chain Planner / Plant Planner)

Fundamentals of SCP/PP(Supply Chain Planner / Plant Planner)

Supply Chain / Plant Planner Basics • Overview of SCP/PP and APS • Getting Started with PP • Building the PP Data Model • Building the SCP Data Model • Balancing and Scheduling Details • Viewing and Analyzing the Model

What is Supply Chain / Plant Planner? • One of Adexa’s Application Modules for Multiple / single site planning using APS technology • Produces an optimized plant level production plan and schedule by simultaneously considering all given constraints such as capacity and material constraints • SCP/ PP also consider three competing management objectives: • Utilization • WIP / Cycle Time • Responsiveness

Plant Planner Main Input/Output commitments forecast contracts planned finish dates customer orders Considerations Drivers PP model material constraints priorities capacity constraints PP Mgmt. obj. capacity plan Detailed Input/Output wip status dispatch lists shop status purchase requirements bottleneck identification Purpose: Single-site planning

Visualizing the Manufacturing Environment • PP is a “Modeling Environment” and it is the customer’s decision as what they want to model in terms of: • detail (routings, resources) • material (key material or all) • etc. Raw Material / Inventory Customer & forecast demand

What is APS • APS: Advanced Planning and Scheduling • A new technology, not an MRP II or ERP Manufacturing System • In memory data processing • Simultaneously considers a wide range of constraints • Material availability • Machine and labor capacity • Due date • Inventory safety stock level • Cost • Distribution requirements (e.g. availability of vehicle) • Sequencing for setup or thru-put efficiency • etc

ERP Manufacturing involves ... APS is not MRP/ERP • Reading and writing to disk space • Infinite capacity and material availability assumptions • Purchase orders simply based on due dates • One location planning

Supply Chain / Plant Planner Basics • Overview of SCP/PP and APS • Getting Started with PP • Building the PP Data Model • Building the SCP Data Model • Balancing and Scheduling Details • Viewing and Analyzing the Model Appendix A: List of Acronyms

Steps in PP Planning 1.1. Start Adexa Applications application with GUI and advanced algorithms 1.2. Run a Script a series to TCL/UCL commands which imports data from external systems and creates a model 1.3. Create a Model logical representation of the Supply Chain environment (generated with the script) that can be solved with the Adexa Applications algorithm 1.4. Generate a Plan use Adexa Applications’ algorithm to “balance” and “schedule” to create a supply chain plan 1.5. Analyze the Plan use Adexa Application’s GUI to analyze the plan 1.6. Publish the Plan commit the Plan to production

1.1. Start Adexa Applications: PP PP/SCP is a “modelling environment” which is composed of: • a GUI • a planning algorithm • Initially, it contains no data

1.2. Run a Script • An Adexa script is a series of TCL/UCL commands that initialises a model by importing the data and creating the links between the data object instances. • Usually, the data will come from another system (e.g. MFGPro, SAP, Oracle, etc.). Therefore, variables are used to acquire whatever data is in the external system, rather than hard-coded values

1.2. Run a Script • be impractical and intolerably time-consuming • have to be updated whenever data is changed • It would be possible to create a model by entering data through the GUI, but it would:

1.3. Create a Model • Result of running the script: • Imported Demand information will create “Short Demands” • Imported WIP information will create “Unscheduled Work Orders” • In this example there is no existing supply information that has been imported (no outstanding purchase order)

1.3. Create a Model • At this point (after importing the data into memory through the use of a script) the model has been built • An Adexa model (developed with a TCL/UCL script, by an Adexa/Partner Consultant) is a representation of the • customer’s supply chain environment • A model can then be solved using Adexa’s built-in algorithm

1.4. Generate a Plan First Step of Solving: Balance Balancing essentially creates work-orders as would be needed and by default it would assume an ideal world (no capacity or material constraints) Balance

1.4. Generate a Plan • After Balancing, we should have work orders to fulfil the existing demand (although the work orders are unscheduled)

Schedule 1.4. Generate a Plan • Second Step of Solving: Scheduling • Scheduling schedules the work orders (considering distribution, capacity, and material constraints), resulting in a work order release schedule and a transportation plan (only for SCP/SP) with • start times for work orders • end times for work orders • when work orders can be shipped/distributed to other sites/locations (SCP/SP)

1.4. Generate a Plan • Now we have scheduled work orders • Probably we have some problems (such as early/late work orders, late demand/supply, etc.)

SFS Sequencer Resources Demand/ Supply Links BOM Work Orders Problem Sources com@location 1.5. Analyze the Plan We can now do analysis and/or “publish” the plan

1.5. Analyze the Plan Once the system has generated a plan, how do I analyse it?

1.5. Analyze the Plan

Import Data Plan Analyze Publish 1.6. Publish the Plan Publishing the plan may involve: • distributing case-files of the model to individual planners • running reports from the model and distributing the reports to execute the plan • exporting data from the plan to other external systems • Distribute Model • Distribute Reports • Export Data • Start Application • Run script • Balance • Schedule • Work Order Scheduler • Resource Scheduler • Bill of Process • Com@Loc Graph • Distribution Map • Measurements Window • etc.

Plant Planner Interface

Control Panel Icons • Planning Balance All - Creates supply for all manufactured and purchased commodities to balance all demand in PP Schedule All - Schedules all work orders in PP SFS - Launches SFS. Note: SFS shares much of the same data resident in PP

Cont’d - Control Panel Icons • Analysis Tools Com@location Graph - displays projected inventory balance graphically for selected commodities@locations BoM Explosion - displays single or multi-level BoM & process explosion Connections - pegging between all supply and demand by commodity@location Resource Scheduler - view of load and capacity for each resource by time period Synchronization - shows relationship between supplying and consuming work-orders Work Order Scheduler - displays and allows edits to work order schedule information

Problems Summary • give us a starting point in analyzing the model • contained useful information • drill down capability • easy viewing

Loading an PP Factory Model

Loading/Saving a Case • The Adexa data model can be created by either • running an import script • loading a “case” which has previously been loaded and saved • A case can be saved with a user-provided file name and archived for later reference • Usual method is to load the data model with the most current extracts from the ERP, MES, and other support systems by executing a script

Solving a PP Factory Model (Balancing & Scheduling Basics)

Planning and Scheduling Objectives • Balance tradeoffs between competing management objectives: • utilization • responsiveness • cycle time (WiP) • Consider demand priorities and due dates • Respect both capacity (capacity of production and distribution resources) and material constraints • Consider any other criteria with the use of Adexa “Plug-in Business Rules”

Balancing: Supply and Demand • Once the data model has been created/loaded into PP, the plan can be balanced and scheduled • PP balances supply and demand by creating • planned manufacturing work orders • purchase material requisitions • All supply and demand is soft allocated

Scheduling: Supply • The PP scheduling process assigns start and finish dates/times for all work orders. • The scheduling process can be either constrained (capacity and/or material) or unconstrained • All demands are assigned a planned completion date/planned arrival date based upon the allocation/distribution and scheduling process • Scheduling is driven by both the demand due date and priority

Scripting (TCL/UCL)

Tool Command Language (TCL) and User Command Language (UCL) • TCL is a scripting language for controlling and extending applications • Provides generic programming facilities such as variables, loops and procedures • Provides interfaces to Adexa Applications • User Command Language (UCL) is the Adexa specific extension of TCL to access the data model

Data Objects & Attributes

Data Objects • The previous slide shows ALL the data objects in PP • For each data object, there is a: • name on the previous data-model tree • window within the application (accessible from the data pull-down menu-bar in PP), where you can see the “instances” of that object • set of UCL commands, where the first “word” corresponds to that object. For example: • Commodity object: com • Demand object: demand • Work Order object: lot • Step Sequence object: step_seq • etc.

Data Objects Identifiers • Adexa Applications uses an object oriented data model • Each object consists of an identifier attribute (primary key) and one or more other attributes • The identifiers for each element within an object must be unique Example 1: Each commodity must have a unique ID such as the finished goods code or engineering part number. Example 2: Each route must have a unique ID. The distribution route ID could be the way to transport a product from one location to another location: air_LA_ATL

Cont’d - Data Object Identifiers • Object Oriented terminology vs. Relational database terms: • Table = Object • Row = Instance • Column = Attribute • Primary Key = Object Identifier

User Defined Attributes • Objects in the data model support user-defined attributes • User defined attributes can be used to maintain any information beyond standard PP requirements • Example: • Which planner is responsible to plan a particular commodity • Engineering revision number, specified at the routing or BoM object • Name of carrier, specified at resource or operation object • For each user-defined attribute, you provide a: • Name • Description • Type of value(including: float, integer, string, date, duration, etc.) • Range: Maximum and minimum values can be specified to prevent illogical values

Supply Chain / Plant Planner Basics • Overview of SCP/PP and APS • Getting Started with PP • Building the PP Data Model • Building the SCP Data Model • Balancing and Scheduling Details • Viewing and Analyzing the Model

Building the PP Data Model • Scheduling Horizon and Period Managers • Resource Capacity • Manufacturing Resources • Commodities • BoMs • Manufacturing Routings • Production Methods • Demand • Management Objectives

The PP Model

Building the PP Model • In this Chapter we will work through the data model by adding a new commodity@location and all necessary data to support the production of that product. • PLEASE NOTE: We will be using the GUI to add the data. But in reality, on a day-to-day basis, all data will be imported from other external systems through the use of a UCL script. • Normally, the GUI will be used for analysis purposes • We will use the GUI to ensure that we are all comfortable with the objects and their meaning

Time-Related Objects

Today 4 months from today Specify Planning Horizon • A starting and ending date define the planning horizon • The start is normally the time and date when information is extracted from the supporting (MES, ERP, or other) systems • The end date needs to encompass the due date of the last demand plus a cushion for any demand that cannot be scheduled by the due date

Today 4 months from today Bucketizing Time with the Period Manager Object • The period manager slices the horizon into discrete periods • These periods may be of any duration and can be of variable length • Example: 14 periods of 1 day each, followed by 6 periods of 1 week each, followed by 2 periods of 1-month each

3/31/98 3/31/99 Horizon Start 1 2 3 4 5 6 7 8 9 10 11 Horizon End Periods Specify Planning Horizon and Period Managers • PP checks the total capacity within the boundaries of the period manager only. If the total capacity used is less than the total capacity available within each period, the constraint is satisfied. • Use smaller periods near the start of the horizon and larger periods further out . • Period managers are also used to aggregate data by time; The analysis tools within PP aggregate data based on the Period Manager.

Fundamentals of SCP/PP (Supply Chain Planner / Plant Planner)