Advanced Planning and Scheduling

1. Advanced Planning and Scheduling References • Errington, “APS - a powerful emerging technology,” 1997 • i2 technology product information • Adexa product information • i2 FP training materials

2. Outline • Introduction to APS • Implementation of APS • APS solutions • Example of APS planning engine - FP

3. Traditional Divided Process Prod./Res. Planning MASTER Demand M. Sched. RCCP MPS MRP CRP DRP EXECUTION DISTRIBUTION Detailed Scheduling Demand Mangmt.

4. Divisions of the Complex Problem • Division by planning time horizon • long-term/strategic, medium-term/tactical, and short-term/operational • Division by different constraint concerns • material constraint / capacity constraint • manufacturing constraint / distribution constraint • Division by different detail levels • master production scheduling / detailed scheduling • strategic capacity planning / detailed resource planning • demand promising / due date quote

5. Deficiencies of the Traditional Process • Divisions to simplify the software • complexity is minimized by breaking up the problem • local optimums do not sum up to a global optimum • burden is shifted to human planner • Divisions lead to iteration • only part of the whole problem is considered by each planning tool • plan results and problems are propagated among tools • iteration is needed to achieve a better plan quality • Manual iteration is impractical • manual effect analyses of changes made • manual judgement to make changes

6. Drivers of New Planning System • Computing power has changed • hardware capability has advanced dramatically • software design has advanced significantly • friendly user graphical interfaces • Planning problem has changed • 1980’s competitive drivers - TQM and JIT • 1990’s competitive drivers - responsiveness and flexibility • accurate, real-time, dynamic planning capabilities required • Planning process must change • BPR/TOC • enhancing the competitiveness instead of automating the business process

7. Supply Chain Optimization / Foundation of eB:Advanced Planning and Scheduling (APS) • Is a redesign of the overall planning process that integrates the process across several dimensions • Addresses the whole planning problem directly, rather than dealing with small parts of the problem separately

8. Concurrent Planning Demand Forecast / Customer Orders Available Production Capacity Raw Materials Procurement / Supplier Lead Times Planning Engine Resources Customer Due Dates Inventory Levels Distribution/ Warehouse Routing Optimal Plan

9. Integrated Planning

10. The Integration of APS • Integrating master and execution planning • Integrating material and capacity • Integrating manual and automated planning • Making order promising dynamic and real-time

11. What is New in the APS • Memory-based processing and advanced algorithms to compute sophisticated production and distribution plans that consider multiple constraints • Synchronize constrained resources and materials flow to a detailed level • Quick re-plans by including the latest information • Rule-based logic allows users to capture their business and production strategies and priority • “What-if” analysis to support decision making process

12. Focuses of APS • Supply chain planning • Include some features of MRPII & ERP • Develop plan for multiple facilities, suppliers, and logistics • Goal: determine what to make and where to make, not individual operations • Multi-plant scheduling • Allocate order over multiple facility and develop schedule • Plant scheduling • Develop detailed operation or job schedules • Consider both materials and components requirements

13. Approaches of APS • Constraint-based planning: • Heuristic engine: rely on the forward and backward scheduling to balance orders against the resources • Theory of constraints engine: identify resource bottlenecks and then prioritize activities to minimize the bottlenecks • Simulation engine: model shop floor, process local heuristic scheduling rule, and generate statistical output about the flow through work centers • Knowledge-based engine: use implicit rules about customer demand, work flow, resources, and constraints to balance incoming orders against delivery dates

14. Approaches of APS (cont’d) • Optimizer engine: use mathematical programming and branching techniques to minimize scheduling and resource conflicts in meeting individual customer orders • Network-based planning • Work from top-down starting from customer order • Schedule one customer order at a time, resolve materials and capacity issues concurrently on every operations

15. Outline • Introduction to APS • Implementation of APS • APS solutions • Example of APS planning engine - FP

16. Selecting the Software • Criteria: • Focus: distribution? manufacturing? type of industries? • Maturity and support • Feature: all key system constraints considered? • Integration: easy? Seamless? • Technology: latest software technology used? • Platform: flexible? • Price: % of revenue? • Best way: use a small, but representative, set of data including all the key elements, then ask vendors to create prototypes for demo

17. Implementation of APS • Business reengineering (?) • Develop a model of manufacturing system using the constructs provided by the packages • Integrate with the existing systems and data cleaning • Customize • Including second-party reporting software, special rules, nonstandard feature • Train users and individuals for maintaining the system

18. Shop Floor Schedule Product Demand BOM / Recipe / Formula / Drawing Resource Routing / Process Labor Characteristics Inventory Status SOP, HEALTH, WORK Instructions Resource Allocation Production Dispatching Document Control Data Collection / Acquisition Labor Management WIP Status / Traceability Product Tracking Quality Management Performance Analysis Process Management Maintenance Management Costing Product Definition Process Definition Human Resources Standard Operation Procedure Inventory Management Purchasing Distribution Production Planning Forecasting Shop Floor Operation Scheduling ERP/APS MES Order Status / Completions Resource Status / Usage Labor Status Usage Material Status / Usage Actual BOM / Recipe Actual Routing / Process Product Traceability Scrap / Waste Interactions between ERP/APS and MES

19. SCP solution garbage garbage Issues of Implementing APS Solutions • APS ready? sound enterprise information system required (not necessary an enormous ERP system) • APS solution is not a software package, it’s a way of doing business and it’s a universal way (everyone including your competitors). • Are your competitive advantage compromised by implementation of SCP solutions?

20. Outline • Introduction to APS • Implementation of APS • APS solutions • Example of APS planning engine - FP

21. Gartner: Process IndustryGartner Group : Magic Quadrant in Oct.’99 Challengers Leaders Manugistics Ability to Execute SCT/Fygr i2 JD Edward Adexa Logility SAP LPA Mercia Aspen Tech Demand Mgmt As of 9/30/99 Niche Players Visionaries Completeness of Vision

22. Gartner: Discrete IndustryGartner Group : Magic Quadrant in Oct.’99 Challengers Leaders i2 Ability to Execute Manugistics Synquest Baan Adexa Peoplesoft STG Logility Web Plan LPA Thru-Put Mercia JD Edwards Aspen Tech Demand Mgmt As of 9/30/99 Niche Players Visionaries Completeness of Vision

23. i2 TradeMatrix™ Solutions Overview DesignPartners Direct Material Suppliers ProductDevelopment Product Development/Engineering Customers Customer Management Supply Chain Planning Procurement Manufacturing Service Management Marketing / Sales / Administration Indirect Material Suppliers Fulfillment Logistics Providers

24. i2 TradeMatrix™ Solutions • For product development: Design Solution • collaborated design and development for low cost, low risk and short time-to-market • For procurement: Buy Solution • efficient sourcing, negotiation, collaboration and ordering • For supply chain planning: Plan Solution • Efficient conversion of raw material into customer-ready product offerings • For customer management: Sell Solution • marketing, selling, customer collaboration, order processing and monitoring • For order promising and logistics: Fulfill Solution • intelligently commitments to customer order and requests • For service planning and scheduling: Service Solution • Increase of customer satisfaction and revenue with minimum investment

25. Supplychain& masterplanning demand fulfillment months year + weeks hours days i2 TradeMatrix™ Plan Solutions execution operational tactical strategic strategic business&network planning messaging and data integration buy manufacturing planning command& control scheduling make move transportation configu ration distribution/inventory planning store sell demand planning/ inventory&sop planning

26. i2 TradeMatrix™ Plan Solution Portfolio Planning Long Term Forecast Transition Triggers Strategic Planning - Capacity Expansion - Network Planning - Inventory Planning - Capacity Allocation Capacity Plan Constrained Forecast Optimal Portfolio Transition Planning Transition Plans Capacity Allocations Master Planning - Demand/Supply Match - Logistics Optimization - Allocations Management Customer Management - eCommerce - eConfig - eMarketing - eCare - Collaboration Demand Fulfillment - Order Promising - Orders Fulfillment - Internet Fulfillment - Allocations Mgmt. - Forecast Netting Demand Plan Allocations ATP Demand Planning Collaboration Netted Forecast Orders (New/Changed) Collaboration Actual Starts Order Status Request Starts/Outs Factory Planning Factory Planning MES Data Lot Due Dates Real Time Dispatching MES Order Entry

27. MCP RDS MCP Raw Matl Supplier Supplier Raw Matl Supplier OEM MCP RDS Supplier MCP RDS Raw Matl Supplier MFG MCP Mfg Raw Matl Supplier MCP Supplier Raw Matl Supplier MFG MCP Raw Matl Supplier E-Malls Supplier Raw Matl Supplier E-Shops OEM Supplier Raw Matl Supplier Retail Outlet Infomediary Adexa iCollaborationTM Solution Business Consumer Channel Intermediaries CDP CSP GSP Direct Channel Home/Business Consumer SCP GRA Channel Resellers Home Consumer Aggregators Metamediary

28. Adexa iCollaboration Suite Strategic PDP - Product Development Planner GSP - Global Strategic Planner SCP - Supply Chain Planner CSP - Collaborative Supply Planner CDP - Collaborative Demand Planner MCP - Material and Capacity Planner Single Data Model Business Intelligence RDS - Reactive Dynamic Scheduler GRA - Global Real-Time ATP CEP - Collaborative Enterprise Planner Operational SCC - Supply Chain Controller Supply Chain Execution Enterprise Resource Planning Product Design Management Customer Relationship Management Product Configurator Transaction Systems

29. Customers Sales Central Planning Site Planning/ Scheduling Demand Planning SCP MPS Demand Promising Adexa CDP Adexa SCP Order Promising Adexa CDP Adexa MCP Adexa GRA Supply Chain Planning Adexa SCP Demand Entry Order Promising Order Execution Data Warehouse Adexa GRA Adexa GRA Adexa MCP Total Supply Chain Management Virtual Supply Chain Management Enterprise Supply Chain Management Site Planning & Scheduling Adexa Supply Chain Solution

30. Functionality i2 Adexa Strategic Planning Allocation Planner / Profit Optimizer GSP Demand Planning DP CDP Demand Promising DF(AATP/CTP) GRA Enterprise Integrated Planning MP SCP Manufacturing Planning FP MCP/RDS Solution Components of i2 and Adexa

31. Strategic Planning • Profit optimization - maximizing revenue while minimizing cost • Capacity expansion and allocation • efficient capacity investment • capacity balancing • most profitable product mix • Distribution network planning • determination of subcontracting, sourcing, and other alternatives • locations and capacity for distribution centers, plants, and other facilities based on projected demand • “What-if” scenario simulation • stochastic (Monte Carlo) simulation by i2

32. Issues of Demand Planning • Most unreliable info in planning activities: demand forecast • Bullwhip effect: fluctuation propagates and magnified through supply chain • Risk pooling: aggregating demand for less fluctuation of demand forecast but how? • Different perspectives of demand: customer, technology, sales region, etc • Uses of demand forecast: for material planning? or capacity allocation?

33. Demand Planning • Statistical forecast techniques are standard • Multi-dimensional “slice-and-die” analysis to provide different views for various divisions of the company: on-line analytic processing (OLAP) technology

34. Demand Promising • ATP (available-to-promise) and CTP (capable-to-promise) • Access to delivery dates and order/quote status • Reservation of inventory and planned production for new orders • Distributed, global, real time • Can match supply and demand based on options • Can trigger re-plan at SCP/MCP level

35. ATP and AATP • ATP • the uncommitted portion of inventory • the end item supply that can be used to quote/promise/reschedule orders • Traditional ATP practice (FCFS) • low margin demand consume all available resources • nothing available for emergency order or high priority customer • AATP = Allocated Available to Promise • AATP is ATP allocated by different demand perspectives • AATP provides a mechanism to reserve supply • Allocation rules need to be defined by users

36. Capable to Promise (CTP ) • Extend the end item representation to include multiple levels of BOM as modeled in MP • Provide a real time mechanism to promise order by searching • End item • Raw material / WIP considering capacity constraints • alternate routings • alternate parts • alternate resources

37. Enterprise Integrated Planning • Enterprise-wide planning • Simultaneous material, manufacturing, and distribution planning • Synchronizes planning for multiple plants and other facilities, dynamically managing inter-plant dependencies • User-defined attributes and business rules • Integration with lower levels of planning. • Enterprise-wide “what-if” analysis • Synchronization with demand planning • Synchronization with demand promising

38. Manufacturing Planning • Plans for manufacturing operations subject to both material and capacity constraints • MCP(Materials and capacity planning) vs. FP(Factory planner) • MCP: balancing and scheduling • FP: infinite capacity planning(ICP) and finite capacity planning(FCP) • RDS (Reactive dynamic scheduling) vs. FP • RDS:continuous capacity profile, sequence dependent setups, batch resources, secondary resources • FP: detailed scheduling

39. Outline • Introduction to APS • Implementation of APS • APS solutions • Example of APS planning engine - FP

40. FP - Concept Step -1 Run Infinite Capacity Plan a. Will identify Material and Capacity problems b. Fix Material problems Step - 2 Run Finite Capacity Plan - CAO a. Will attempt to fix Capacity problems Step - 3 Run Advanced Scheduler

41. FP - Planning Flow Construct Manufacturing Model to identify critical constrained resources ICP FCP (CAO) to synchronize the flow Adv. Schedule/Finish

42. Infinite Capacity Planning Inventory Assignment Backward Schedule Forward Schedule Planned Start Time

43. Inventory Assignment • Step 1: Sort Demand Orders • Due Date • Priority Points (the more, the earlier) • Quantity (the smaller, the earlier) These factors can be considered in any order

44. Inventory Assignment - Example

45. A B C D Inventory Assignment • Step 2: BOM (bill of materials) explosion PART SEQUENCE A B C D

46. Inventory Assignment • Step 3: Assign Inventory • Iterate through part sequence and post demands • Assign inventory to each demand order • Create Manufacturing Orders Planned Quantity = Required Quantity - Total Inventory - WIP

47. Inventory Assignment - Example

48. Inventory Assignment - Example (cont’d)

49. Backward Schedule • Definition : Latest Possible Start Time(LPST) • the latest date a manufacturing task can begin and still complete on time • Calculation : • LPST = Due Date - (Setup+Run+Cool Down) • Each manufacturing task will have an LPST

50. Example LPST Table Top Order_1-MFG00002 Table Table Assembly LPST Order_1-MFG00000 Order_1 Due Date = 3/15/95 LPST Legs Order_1-MFG00001 Backward Scheduling