Diagnostics and ReliabilityDiagnostics and Reliability

The course cannot be taken simultaneously with:

Diagnostics and Reliability (E36DSP)

Lecturer:

Tutor:

Supervisor:

Department of Computer Science and Engineering

Synopsis:

Fault models for digital systems, test generation for combinational and sequential circuits, test set minimization, fault simulation, signature analysis, built-in self-test, testing LSI and VLSI circuits, hardware for diagnostics. Introduction to reliability, models and characteristics, their evaluation, system redundancy, fault-tolerant systems.

Requirements:

Syllabus of lectures:

1. Introduction to diagnostics, basic terms, fault models.

2. Test generation for combinational circuits.

3. Test generation for sequential circuits.

4. Test set minimization, random and pseudorandom test vectors.

5. Automated test generation systems, fault simulation.

6. Diagnostic data compression, signature analysis, fault dictionaries.

7. Design for testability, built-in self-test equipment.

8. Fail-safe circuits, totally self-checking circuits. Watchdog.

9. Testing LSI and VLSI: microprocessors, memories and PLDs.

10. Testers. Boundary scan.

11. Introduction to reliability theory, reliability models.

12. Evaluation and prediction of reliability characteristics

13. System redundancy (static and dynamic).

14. Fault-tolerant systems, their design and application.

Syllabus of tutorials:

1. Faults in digital systems, fault models.

2. Intuitive path sensitizing

3. Path sensitizing in circuits with redundancy, D-algorithm

4. Boolean difference, modular approach to test generation

5. Test generation for sequential circuits.

6. Test set minimization

7. Diagnostic data compression, fault dictionaries.

8. Fail-safe circuits. Preparing laboratory measurements

9.-12. Laboratory measurements (rotating)

-Fault detection and location in combinational circuits.

-Boundary scan

-Built-in self-test equipment

-Signature analysis

13. Computing of reliability characteristics, redundant systems

14. Markov models of repaired and non-repaired systems

Study Objective:

Study materials:

Note:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans: