Skip to Main Content
As tester complexity and cost increase, reducing test time is an important manufacturing priority. Test time can be reduced by ordering tests so as to fail defective units early in the test process. Algorithms to order tests that guarantee optimality require execution time that is exponential in the number of tests applied. We develop a simple polynomial-time heuristic to order tests. The heuristic, based on criteria that offer local optimality, offers globally optimal solutions in many cases. An ordering algorithm requires information on the ability of tests to detect defective units. One way to obtain this information is by simulation. We obtain it by applying all possible tests to a small subset of manufactured units and assuming the information obtained from this subset is representative. The ordering heuristic was applied to manufactured digital and analog integrated circuits (ICs) tested with commercial testers. When both approaches work, the orders generated by the heuristic are optimal. More importantly, the heuristic is able to generate an improved order for large problem sizes when the optimal algorithm is not able to do so. The new test orders result in a significant reduction, as high as a factor of four, in the time needed to identify defective units. We also assess the validity of using such sampling techniques to order tests.