Engineering Your Supply Chain for Exponential Growth

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Larry Sladewski, Senior Director of Materials at NVIDIA and Intrigo, will give you an update on NVIDIA's supply chain initiative. This presentation will focus on critical operations and the need to dynamically reallocate build plans, WIP, and inventory across the supply chain. [Presented at the 2012 SAP Summit on Suppy Chain Management in Palo Alto, CA]

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Engineering Your Supply Chain for Exponential Growth

  1. 1. Engineering Your Supply Chain for Exponential Growth July 25, 2012
  2. 2. 2Agenda NVIDIA overview Intrigo overview State of the industry Business problem CODE solution overview Complete Optimized Data EngineNVIDIA Confidential July 25, 2012 SAP Supply Chain Summit
  3. 3. NVIDIA Facts 3 Founded in 1993 Jen-Hsun Huang is co-founder, president, and CEO Listed with NASDAQ in 1999, under the symbol NVDA Invented the GPU in 1999, more than one billion shipped to date FY12: $4 billion in revenue 7,500 employees worldwide 5,000 patents issued, allowed or filed Headquartered in Santa Clara, CANVIDIA Confidential July 25, 2012 SAP Supply Chain Summit
  4. 4. 4From Super Phones to Super CarsNVIDIA Confidential July 25, 2012 SAP Supply Chain Summit
  5. 5. 5Core Technologies and Brands GPU Mobile Cloud GeForce® Tegra® VGX ™Quadro® , Tesla® GeForce® GRIDNVIDIA Confidential July 25, 2012 SAP Supply Chain Summit
  6. 6. 6 About Intrigo We are a Premier Enterprise Consultancy, focused on orchestrating Customer Value Networks at the confluence of Demand, Supply and Innovation. Respond Supply Demand SenseOUR SERVICESAdvisory Re-architect the planning processes Create Usability / workflow re-model Source: AMR Enterprise Architecture and Software components Implementation Complete turnkey implementation Innovate Assemble to deliver Support Offshore project/engineering delivery Planning Analytics NVIDIA Confidential July 25, 2012 SAP Supply Chain Summit
  7. 7. 7Intrigo Systems’ Clients“The ability of Intrigo’s leadership team to executein a complex, multi-party environment directlycontributed to the success of our project." -- John Hanna, Director - iPlan Project, Clorox “Intrigos deep industry domain knowledge and their expertise in SAP made for an effective implementation of our Business Systems. Their commitment and focus to making us successful make Intrigo a key partner for Aptina.” -- Joe Passarello, CFO, Aptina ImagingNVIDIA Confidential July 25, 2012 SAP Supply Chain Summit
  8. 8. Outsourced Manufacturing 8 NVIDIA selects proven subcontractors and processes Capacity is allocated through a forecast : commit communication cycle NVIDIA may invest in testers and custom hardware Vendor process stability and execution are monitoredNVIDIA Confidential July 25, 2012 SAP Supply Chain Summit
  9. 9. 9Capacity Alignment NVIDIA provides an annual Vendors respond with an annual forecast to vendors capacity commitmentEvery month, NVIDIA provides a Vendors respond with a commitment to 6-month rolling forecast the 6-month planNVIDIA places purchase orders Vendors respond with acknowledgements as required and delivery commitments Weekly meetings review loading flexibility, WIP, delivery status, and action plans Quarterly Business Reviews scrutinize goals and develop improvement plans NVIDIA Confidential July 25, 2012 SAP Supply Chain Summit
  10. 10. 10State of Supply Chain Planning in the Semiconductor Industry• Discrete vs. attribute-based part numbers• Multiple postponement points• Optimization planning models • Long lead time materials (finished wafers) • Capacity-constrained, high value materials • Test equipment, allocation to multiple subcons, cost• Heuristic planning models • Order-based planning (customer centric models)• Lead time assumptions for fabless firms are vagueNVIDIA Confidential July 25, 2012 SAP Supply Chain Summit
  11. 11. Supply : Demand Planning Cycle 11 SAP/ APO Field Sales System Customer / Sales Forecast Monthly Cycle Boards Supply Fiscal Sales Plan Planning commits supply to specific dates, recorded in SAP Demand Chips Supply APODemand Planning (Sales & Business SystemUnits) place a demand on Operations NVIDIA Confidential July 25, 2012 SAP Supply Chain Summit
  12. 12. 12Supply Chain Planning Evolution GATP with product Inventory forecasting and allocation (SAP APO) supply-demand alignmentDemand planning (SAP APO with BO dashboards)(SAP APO) Postponement planning 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 VMI deployment CODE FCD improvements • Constrained planning • Optimized planning • Scenario planningUnconstrained supply plans(SAP APO – PPDS heuristics) 12-month supply commit Aggregate wafer Planning NVIDIA Confidential July 25, 2012 SAP Supply Chain Summit
  13. 13. 13Business Problem NVIDIAs business has grown more complex Our ability to project, manage and optimize our wafer supply has entered the critical path of our growth Existing spreadsheet-driven processes cannot scale to the growth of our business (market segments, number of SKUs, product complexity) Today’s focus is to align supply to marketing demand by SKU Tomorrow, beyond alignment, we want to employ production plans optimized for flexibility and efficiencyNVIDIA Confidential July 25, 2012 SAP Supply Chain Summit
  14. 14. Planning Priorities for System Development 14(Summer 2011) Excel Excel MANUFACTURING STEP Complete Scenario Optimized Integrated Planning Planning TO BE PLANNED Planning Planning Planning Planning single user multi user Wafer Production done 1 3 10 16 - (GPU, interposer) Post Fab Wafer Processing 2 4 12 17 - (bump, sort, backgrind) Assembly BOM Components done 8 - - - (substrates, interposer die) Assembly Services done 5 15 19 - (die mounted into a package) Post Assembly Validation done 6 14 20 - (ATE, burn-in) Configuration done 7 11 18 - (SLT, tape & reel) FG BOM Components done 13 - - - (kitted memory) Logistics 9 21 - - (factories, hubs, EOQ) Excel planning on a single user system Excel planning using a shared drive Complete planning: all data elements visible in the system, must have at least MRP II capabilities Scenario planning: extracting data from the system, manipulating data in a structured way, and saving results Optimized planning: system generated best answers for problems contained within the Chip Ops silo Integrated planning: active links with Sales, BU, & Finance tools; i.e., mutual plans re-align at least daily NVIDIA Confidential July 25, 2012 SAP Supply Chain Summit
  15. 15. Wafer Planning in Multi-User Excel 15Supply–demandmatching occursin APO. It doesnot optimize andis a deterministicmodel.Supply anddemand are Shared Driveconsolidated at Folder forthe wafer level Virgin Dataand the globallocation level. Shared Drive 18 files pulled Folder for Data out of systems Cleaning of record. Workbooks Large files exceed 50,000 Shared Drive rows. Folder for One workbook Calculation & per file is Analytics archived each Workbooks week. NVIDIA Confidential July 25, 2012 SAP Supply Chain Summit
  16. 16. Functionality Comparisons- Business 16(Fall 2011) Criteria SAP i2/JDA Data input / management Satisfactory Satisfactory-excellent Engine – LP TBD – may not be needed Excellent Engine – heuristics Satisfactory Satisfactory Integration with SAP ERP Excellent Satisfactory Scenario management Satisfactory Satisfactory-excellent Analytics Satisfactory-excellent Satisfactory i2 is the better product in terms of core functionality required for Chips Planning APO has seamless integration with our SAP ERP system A custom user interface ‘skin’ will be required for APO to ensure data input accuracy A custom report writer for analytics will be required for APO Add-ons to the APO LP Optimizer may be required (TBD) NVIDIA Confidential July 25, 2012 SAP Supply Chain Summit
  17. 17. Risk Factors- IT Judgment 17(Fall 2011) Criteria SAP / Intrigo i2/JDA Perceived quality of solution Medium Low (‘completeness’ of functionality) Implementation experience Medium Low (semiconductor industry) Financial viability of vendor Low Low Integration challenges Low Low-Medium Vendor ‘depth’ of bench Medium Low-Medium Overall risk of moving forward with Medium Low vendor i2 has the LP Optimization, Scenario Analyzer and Planning Data user interface deployed in multiple semiconductor companies. But we have no i2 expertise in house and we have to manage the seamless integration with SAP . SAP has less semiconductor experience than i2 and a user interface ‘skin’ that needs to be custom-developed for ease of use. TCO is significantly less than i2. NVIDIA Confidential July 25, 2012 SAP Supply Chain Summit
  18. 18. 18Design Guiding Principles• NVIDIA challenges are vanilla • Manufacturing flows are “typical” semiconductor, including binning• Goals: no planning in Excel & improve the data quality• Master data must be capable of being easily maintained • Planning rules maintained in Business language • Transparent for other NVIDIA teams to use• Results must be explainable to executive management• Models must enable postponement strategies & buffers• Scenario & bridge analysis support will be requiredNVIDIA Confidential July 25, 2012 SAP Supply Chain Summit
  19. 19. 19 Planning Solution Overview Wafer allocation byOptimization product: for wafer constrained for planning backend planning Backend planning to determine PFG supply: assembly starts & constraint for SLT PFG starts to planning support the forecast SLT planning to Projected determine PFG finished goods starts for demand for order signal commitments NVIDIA Confidential July 25, 2012 SAP Supply Chain Summit
  20. 20. 20 Planning Solution Overview Wafer allocation byOptimizationWafer Planning by SAP APO product: for wafer constrained for planning Optimizer backend planning Backend planning to determine Backend planning byPFG supply: assembly starts & SAP APO constraint for SLT PFG starts to Optimizer planning support the forecast SLT planning to Projected Backend SLT planning by determine PFG finished goods starts for demand for order SAP CTM commitments signal NVIDIA Confidential July 25, 2012 SAP Supply Chain Summit
  21. 21. 21 Planning Solution Overview Wafer allocation byOptimizationWafer Planning by SAP APO product: for wafer constrained for planning Optimizer backend planning Backend planning to determine Backend planning byPFG supply: SAP APO Custom UI assembly starts for Data constraint for SLT & Management PFG starts to Optimizer planning support the forecast SLT planning to Projected Backend SLT planning by determine PFG finished goods starts for demand for order SAP CTM commitments signal NVIDIA Confidential July 25, 2012 SAP Supply Chain Summit
  22. 22. Reference Model Example 22 Fab Bump Sort Assy Test SLT Un bumped Unsorted Wafer Sorted Wafer Die FG Back Assembly PFG/FG Wafer grind Backgrinded Tape Die & Reel Three supply plans are generated: Fab to die (2 year horizon) Die to FG (1 year horizon) SLT / T&R ad hoc runs (4 week horizon) Focus on data, priorities, rules, and system generated supply plans Modular locations- easily added or removed as supply chain evolves NVIDIA Confidential July 25, 2012 SAP Supply Chain Summit
  23. 23. 23 CODE Inputs & Outputs DATA OPTIMIZER RESULTSInventory Strategies Unconstrained SupplyProduct Priorities FG Supply CommitDemand CODEProduct Data Die/Capacity Max Supply SAP PlatformCapacity Scenarios – What-if’sMaterials Execution InstructionsFactory Loading Strategies NVIDIA Confidential July 25, 2012 SAP Supply Chain Summit
  24. 24. 24Business Rules for Planning • Ease of maintenance • Excel like interface • Demand segmentation priorityPriorities • Master data scenario management • BOM priority • Time phased data • Subcon loading priority • Yields • Resource availability • Resource consumption • Time phase priorities • Product • SKU selection • Demand segmentation Rules • Lean rule • BOM • BOM downbinning • Routing • Max and Min volume constraintsStrategies • Buffer stock • Subcon quota • Product substitutionNVIDIA Confidential July 25, 2012 SAP Supply Chain Summit
  25. 25. 25 Planning Data Flow Overview Input Screens Planning Data APO Planning Engine Management Tool Build Rules Build Strategies Time Phased Data Data RepositoryECC Master Data transfer Publish to Output APO Master Data transfer APO Planning Engine Data Warehouse APO Master Data transfer Transaction Data Planning Results Core Interface Standard SAP component to transfer planning input data (Master & Transaction Data) and output data (planning results) Execution instructions to subcon ECC Confirmations from subcon NVIDIA Confidential July 25, 2012 SAP Supply Chain Summit
  26. 26. 26Planning Scenarios Overview POR version Wafer capacity-constrained version Wafer Plan Wafer capacity-unconstrained version Backend material and capacity-constrained version Backend material-constrained, capacity-unconstrained version Backend Plan Backend constrained, push production SLT material and capacity-constrained version SLT Plan SLT material-constrained, capacity-unconstrained version Scenario solves as per the requirementNVIDIA Confidential July 25, 2012 SAP Supply Chain Summit
  27. 27. Problem Data Set 27 Engine: SAP SNP Optimizer Solve Type: linear Horizon: 2 years Cost Model: relative cost model engine NVIDIA Confidential July 25, 2012 SAP Supply Chain Summit
  28. 28. 28 Thank YouNVIDIA Confidential July 25, 2012 SAP Supply Chain Summit

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