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where C is the network capacitance, i is the charge or discharge current, and v is the change in voltage that occurs during the measurement time t. Related, though more complex, behaviors occur for RC time constant and AC coupling measurements. Using the preceding example, note that if two networks are shorted, the resulting capacitance is the sum of their individual capacitances. The larger capacitance causes a slower charge rate than is expected for either net individually. The system may note that these two networks are adjacent and displaying suspiciously similar charge time behavior. The system tags the networks as suspicious, and either fails them or verifies the presence of a short with a DC measurement. Networks containing an open will have reduced capacitance and will charge or discharge too quickly. These conditions are illustrated in Fig. 37.8. To use these indirect methods, most systems require testing of a first article board using standard direct measurement methods for both continuity and isolation. Once the board is known to be good, the signal-coupling behavior is learned for each network on this board.The learned values are saved and compared to measured results from subsequent boards as described previously. Tremendous speed increases are obtained by eliminating repetitive probing of each network at multiple locations, particularly in the case of isolation testing. Some users combine a traditional DC continuity measurement with the indirect method as a substitute for isolation.

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37.4.4.2 Adjacency Analysis: Isolation Testing on Flying Probe Systems. Adjacency analysis simplifies isolation testing on flying probers by reducing the number of measurements, even for direct measurement methods. In adjacency analysis, a database is prepared listing each network and all traces found to be immediately adjacent to that network according to a set of geometric criteria. Such locations are assumed to represent the sole opportunities for shorts and leaks. Isolation testing is then performed only between adjacent pairs, this measurement being well suited to the nature of the flying prober. It is important that attention be paid to whether such analysis is three-dimensional. Networks may cross over a network horizontally, but on a different layer of the board. A hole or defect in the intervening insulating layer may allow a short or leakage to FIGURE 37.9 Network adjacency. occur. In the example illustrated in Fig. 37.9, network A would probably be judged adjacent to B, but not to C. B would be considered adjacent to A and D. Assuming that the qualifying dimension was a bit smaller than the distance from E to either B or D, E might not be judged adjacent to either.

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An essential element in any test operation is the means of generating test programs, and, in the case of fixtured tests, the design of an appropriate test fixture. There are several methods for deriving this program and fixture information. These methods vary from simple to complex and from escape-prone to very sound.The most common terms used in the language of bare board testing for the test program development are self-learning and netlist testing. Netlist testing is a misnomer that confuses computer-aided design (CAD) output with test inputs and implies that there is not much in between. In this discussion, we will use the term data-driven test program to indicate the program to be loaded into the test system is derived from the board s design data (which may be provided in any of several different forms). On the other hand, a self-learned program is derived by placing an assumed good board on the test system and causing the test system s internal computer to create a

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program automatically that can be used to compare other boards to the detected pattern. It is worth noting that the description known good is often used to describe this first board, when in fact our knowledge of its quality is often imperfect. Flying probe test systems generally require no fixturing, except sometimes a frame to hold thin boards or to load multiple small boards simultaneously. Flying probers still require test program generation and optimization. Instead of a fixture, the product program contains probe position information for planned test. Data preparation processes are therefore similar to those of fixtured tests, but only test program data are output. Note that the extractions of program and fixture information are quite naturally linked. In fact, the final test program cannot be created until the fixture is defined. The fixture determines how the individual test points of the test system are connected to specific product locations. Knowledge of how the fixture has taken hold of the product is essential to determining which system test points to employ in performing specific measurements. Thus, the same software system generally outputs both the final test program and the fixture drilling/loading information.

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