IBM e-business

Choices: Design Level Packaging Options: Tests: Organization, Addressing, etc. Wafer Sorts (quality) Tests Results: Reliability: Pass/Fail (random) Speed Sort: Random test results
Execution (daily/weekly):
Take corrective actions Track service and inventory levels
Determine causes for discrepancies
Check if inventory and service levels are within acceptable ranges
Demand Model based on a Martingale method for forecast updates
Ft ,s = µ s + ∑ as −r ε r
r =s −n
t+L s =t t+L s =t
t
Ds = µ s +
r =s −n
∑ρ
s
s−r
ε r = µ s + Γs − n , s
Model: Framework
A multi-echelon system
FAB Sector 1
FAB Sector 2
FAB Sector 3
FAB Sector 4
Wafer Test Device inventory
Forecast Bias Forecast Error Test (sort) Mark Module inventory Ship
Module Stock
Environment: Market Conditions & Trends
Moore’s law continues to hold (i.e. 50% cost reduction in every 18 months) Seasonal gyrations in demand/supply balance Power in hands of customers Increasingly stringent service requirements (JIT, shorter order-to-delivery cycle times) Contracts becoming common Constructive partnerships are rare Product life cycles are short and prices decline fast Commodity products have low margins
Sandy Anderson, Tracey Pilkinton, George Wood IBM Microelectronics Division Burlington, Vermont
Environment: Semiconductor manufacturing/distribution supply chain has a global multi-echelon structure...
Assess product profitability, market potential to determine future strategy Determine strategy for build-plan, based on uncertainty in demand Assess trade-offs between obsolescence risk and customer service
Inventory Value Profile
140000 120000 Inventory ($) 100000 80000 60000 40000 20000 0 -200 -100 0 100 Tim e (days) 200 300 400
Model: Tactical Analysis during the Product Lifecycle
Model: Demand and Inventory Control
Total Lifecycle modeling with - weekly forecast updates - daily orders, receipts and sales - periodic updates of market size
= Mfg/Assembly/Test location
= Physical stocking location
Environment: Semiconductor Part Proliferation
Wafer Mfg & Test Die Stock
Bond & Assembly
Burn-In, Test & Sort
Environment: Bond, Assembly & Test
Multiple objectives: Minimize unit production costs Meet service commitments at module stock Maximize quarterly profit Keep lines running smoothly Conflicting operations strategies: Build to order vs. build to plan Minimize lot size vs. minimize setups Limit number of part numbers vs. offer as many parts as possible Constraints: Mfg bottleneck (e.g. tester equipment) Long lead time parts (e.g. lead frames)
Order-up-to level is state-dependent and forecast dependent
S t = ∑ Ft ,s + z Var[∑ Γt ,s ]
Model: Lifecycle Analysis at the Design Stage
Determine appropriate inventory policies at the device and module levels at different stages of the lifecycle to achieve service targets Evaluate Tradeoffs between obsolescence risk and customer service Determine overall profitability of product Estimate value of required investments as a function of time
Wafer Test Bond and Assembly Test Module Substock Card Final Stock
Die Stock
Module Final Stock
Card Assembly
typically 1.5-3 months
typically 1-2 weeks
typinment: Wafer Fabrication
Objectives: Reduce cycle times & WIP inventory Improve yields (very significant cost driver) Meet service commitments at die stock Maximize process learning Minimize unit production costs (Achieve high capacity utilization) Maximize quarterly vs. long-term profit Conflicting operations strategies: Start only what is needed vs. fill the line to capacity (Push vs. Pull) Keep lots moving vs. allow engineering holds Many Complex constraints
Environment: Inventory Management
Planning (monthly/quarterly):
Set target service levels: “x% to customer request date”
Are these targets consistent? Set target inventory levels: “y DOS at module finished stock”
Bond & Assembly
Model: Assumptions
A system in series (at least 8 echelons) Single product, single location at each echelon Non-stationary parameters: Demand is random and has time varying distribution Lead times are random and have time varying distribution Manufacturing yields are random and have time varying distribution Costs are deterministic and time varying Market prices are deterministic and time varying Inventory management is done through a non-stationary order-up-to policy at each echelon Life cycle of a product is relatively short and random (careful inventory obsolescence management is required) Objective: Minimize overall inventory (FGI+WIP) and achieve a target customer service Customer service: On time shipment to customer request date