A Procedure and Program to Optimize Shuttle Mask Cost Advantage

1. A Procedure and Program to Optimize Shuttle Mask Cost Advantage Artur Balasinski 1) , J.Cetin1), W.Sachs-Baker1) A.Kahng2), and X.Xu2) 1) Cypress Semiconductor 2) University of California San Diego, CA, USA

2. Introduction • Shuttle or Multi-IP masks: A well-known recipe for reducing cost of mask component in new product development. • Simple concept, complex execution: • put multiple types of layers or products on one mask plate • process options have to be considered. • Immediate verification required: • Once the first mask is shipped, it is costly to change architecture of the set. • Visual verification fast and efficient • Simple algorithm: • mask layers lined up according to the price and field tone • subsequent layers placed on the masks with different grades. • Verification and enhancements: • layer pairing based not only on the price of the mask set, • but also on the cost of the setup, design, and fab-friendliness. • Manual pairing • reduce the count of orphan layers • matching rules to improve flexibility and fab-friendly architecture.

3. Why Are We Optimizing ? • IP distribution: • mask databases by layer and product • can have different shapes, sizes, mask grade requirements • Optimization needed to put as many non-redundant IP components on one plate as possible • Two basic flavors: • Multi-layer (NL-1P) • Multi-Product (1L-MP) • Mixtures also possible • Gets complicated for 30 masks per product Mask 1 High end Starting layer set Mask 2 Low end Starting product set

4. What Are We Optimizing ? • Not mask cost because mask cost [$] = const • IP placement cost: • what is the min cost of reticles to transfer layout pattern to wafer, • for one product • for a product family • multiple IP needed at the same time/plate to share placement cost • IP density on a mask: • Examples: • Simple: • 1 Product with N layers (1P-NL) on one mask: IPD = N (no orphans !) • M Products with 1 layer (1L-MP) on one mask: IPD = M (same flow !) • Real life: • M products with total of n1+n2+…nm layers on K masks: • IPD = (n1+n2+…nm)/ K • Why real life is complicated: IP placement for testchips costs more than for products

5. What Are We Optimizing ? • The higher the IPD, the lower the mask component cost, but • Mask cost is not the only one in the overall product development cost

6. How Are We Optimizing ? • Optimizing cost of IP placement: • Increase IPD until something breaks • Multi-component cost criteria: • First derivative: Manufacturing Setup Design cost may increase with IPD Placement cost decreases with IPD Question: Can cost reduction only depend on automated layer placement

7. What can increase with IPD ? • Setup, Design, and Manufacturing cost • single-event • distributed • As IPD increases: • Manufacturing cost up • predictable - low volume as mitigation • unpredictable - fab conditions • Setup cost often not included • database handling • frame planning • quality procedures • archiving • Design cost: • shuttle delays volume production • wasted effort for unproven products What this means: Full visibility on shuttle impact desired upfront

8. Example Low IPD Mask cost dominates Other components catch up after multiple weeks High IPD Design cost dominates Mask cost distributed Other cost increased due to higher complexity

9. Cumulative Cost Low IPD Total cost similar for low and high IPD Different ramp rate: use high IPD masks for short time only High IPD

10. Basic Algorithm for NL-1P How do we arrange layers on a mask plate ? Step 1: Decision making Do we want this product to run in mulit-layer format ? With how many layers per plate ? Output: N = number of layers per plate

11. Basic Algorithm for NL-1P Step 2: Execution Guidelines: - Design feedback - Product volume

12. Input GUI Input parameters: - Mask making restrictions - Scribe entries - Number of LPP - Reticle data (to be loaded) Hint: For best results, have a picture !

13. Output GUI 1 Simple example for 3 products with identical die sizes Picture: Layer name, blading, scribe to scale Price incentive displayed 1 Picture = 10000 Words Reticle Grade A1, Cost 29,000, Process 193-PSM-ARP

14. Output GUI 2 Mfg verification: 1. Number of exposures must not reduce stepper’s throughput 2. Other issues related to too frequent stepping must be avoided

15. Manual Optimization • Layer placement procedure: • good for majority of the layers • may not be optimal from the MFG, SET or DES standpoint • enhancements, limitations and additional rules for the layer placement: • layers with similar functions should be placed on one reticle, to enable single mask retapeout for design fixes, • non-critical layers OK with the critical ones even if their characteristics, e.g., field tone, are different. The exact guidelines provided by the maskshop, • layers with similar pattern densities should be placed on the same reticle, • individual layers from different products need large footprint so as not to reduce fab throughput. • Should provide data placement document. • These rules may not lend themselves to easy automation. While the basic layer combinations call for price-dependent layer pairing, this may not always be the best solution for product development.

16. Theoretical Case Unlimited placement required Any combination of masks and layers

17. Conclusions • Shuttle automation is making significant progress to optimize placement of multiple products on the masks. One consequence is complex data structure which impacts design and manufacturability. • Layer placement needs automated rules and manual verification to minimize the number of orphans and make the set manufacturing-friendly at the same time. • Algorithmic solutions aimed only at reduction of the mask cost may not provide optimal mask composition, due to many factors in the multi-parameter, integrated cost equation: setup, product line, risk of error and lost opportunity. • We developed and demonstrated the automated layer placement routine which can be useful in optimization of new product development.