Customer experience sharing from ITE
Yield Rate:
Benefits and help from using iSTART-TEK products: The main reason for choosing iSTART-TEK is its strong price competitiveness and flexible support services, such as customized features. Particularly for the memory repair function of the mature 8-inch process, the initial statistical raw yield rate was about 90%, with 50% of SRAMs having repair design, the failure recovery rate reached 97%, the overall yield increased by 3%, and the area increased by 0.3%. It also supports a variety of testing interfaces, allowing ITE to choose JTAG or Basic I/O interfaces according to product needs. In addition, iSTART-TEK’s EDA tools are easy to learn and can be quickly integrated into ITE ‘s design process, effectively reducing the customer return issues of DPPM and helping ITE improve the rigor of testing.
Application field:
The chips of ITE are mainly used in PC and NB control chips, as well as image processing (Video Bridge) and system-on-chip (SoC), all of which require a large amount of SRAM.
Customer experience sharing from Rafael Micro
Yield Rate:
Benefits and help from using iSTART-TEK products: In the wafer manufacturing process, memory defects are an inevitable issue. For small and medium-sized IC design houses, developing related testing processes on their own is not only costly but also technically demanding. By adopting iSTART-TEK’s EDA tool START, Rafael Micro has become more flexible in chip design and development, and has focused on the development of the wireless communication field. iSTART-TEK’s MBIST can automatically screen out IC Memory Defects during mass production testing, and MBISR can repair these defects, reducing the defective products caused by memory defects by 30%. This greatly improves the yield of SoC and the control of the testing process.
Application field:
Rafael Micro focuses on the field of wireless communication, and its products include TV tuners and the Internet of Things (IoT). TV tuners need a large amount of SRAM for video transmission; with the vigorous development of AI and the Internet of Things, the storage of networked information also requires a large amount of SRAM.