| Autor: |
Atul Chhabra, Bharath Nandakumar, Anil K. Malik, Sameer Chillarige, Kanika Kanwal |
| Rok vydání: |
2019 |
| Předmět: |
|
| Zdroj: |
2019 IEEE International Test Conference India (ITC India). |
| Popis: |
Traditional software-based scan chain diagnosis methodology requires failures from scan chain shift pattern(s) and a few logic patterns to identify the location of defective flop(s). The number of failures required for this methodology is massively high and collecting such magnitude of failures may not always be practical in a volume diagnostic environment. This problem is further exacerbated by the increased usage of low cost testers with limited tester fail buffer. Furthermore, the diagnosis of these massive failures is extremely time consuming due to expensive simulation iterations required for identifying the defective flop(s). In this paper, we propose 3 enhancements to an existing hardware-based scan chain diagnosis technique defined for FULLSCAN test mode to make it successful in a volume diagnostic environment. These include: 1) extension for compression modes 2) reduction of failures required for diagnosis by minimizing the expect values in patterns 3) novel Multiple Device Diagnosis (MDD) algorithm and methodology to diagnose 1000s of failing devices in a single run. Experiments conducted on industrial designs on randomly chosen failing devices demonstrated up to 19.68X speed-up using the proposed MDD algorithm. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
|
