Slow India may lose Cricket wafer fab
By Peter Clarke, EETimes Europe
January 31, 2017
Cricket Semiconductor, an analog and power pure-play foundry project that was being prepared for touch down in India, is running late and could end up being constructed in a different country.
The plan, announced in 2015, was for Cricket to break ground for an analog and power circuit wafer fab in 2016 – with Indore in Madhya Pradesh as the likely location – and that it would begin producing chips in 2018.
"The project has taken longer than we had anticipated, and it may continue to move at a pace that is slower than our preference," Lou Hutter, a former Texas Instruments executive working on the project, said in email correspondence with EE Times Europe.
E-mail This Article | Printer-Friendly Page |
Related News
- Could India's Analog Wafer Fab be Moving South?
- State of Madhya Pradesh, Cricket Semiconductor and IESA working towards India's first specialty fab
- India fab decision likely this quarter
- Tower bids to build 300-mm wafer fab in India
- Foundry Revenue Is Forecasted to Drop by 4% YoY for 2023 Due to Slow Inventory Consumption and Falling Wafer Input from Customers, Says TrendForce
Breaking News
- Thalia's AMALIA 24.2 introduces pioneering estimated parasitics feature to reduce PEX iterations by at least 30%
- TSMC plans 1.6nm process for 2026
- Qualitas Semiconductor Partners with TUV Rheinland Korea to Enhance ISO 26262 Functional Safety Management System
- M31 has successfully launched MIPI C/D PHY Combo IP on the advanced TSMC 5nm process
- Ceva multi-protocol wireless IP could simplify IoT MCU and SoC development
Most Popular
- Controversial former Arm China CEO founds RISC-V chip startup
- Siemens collaborates with TSMC on design tool certifications for the foundry's newest processes and other enablement milestones
- Credo at TSMC 2024 North America Technology Symposium
- Synopsys Accelerates Next-Level Chip Innovation on TSMC Advanced Processes
- Kalray Joins Arm Total Design, Extending Collaboration with Arm on Accelerated AI Processing