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Optimizing "Bed-Of-Nails" Tester Configuration And Signal-To-Ground Assignment of In-Circuit Testers

IP.com Disclosure Number: IPCOM000119906D
Original Publication Date: 1991-Mar-01
Included in the Prior Art Database: 2005-Apr-02
Document File: 1 page(s) / 54K

Publishing Venue

IBM

Related People

Ahmadi, J: AUTHOR

Abstract

There is disclosed a technique for implementation in software which optimizes the configuration of a bed-of-nails tester used for in-circuit test of an electronic circuit board. The objective of the optimization method is assignment of the most desirable probe type (e.g., offering the highest contact reliability) to test sites from a set of sites requiring a given number of probes. (There are many such sets on a given board.)

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Optimizing "Bed-Of-Nails" Tester Configuration And Signal-To-Ground
Assignment of In-Circuit Testers

      There is disclosed a technique for implementation in
software which optimizes the configuration of a bed-of-nails tester
used for in-circuit test of an electronic circuit board.  The
objective of the optimization method is assignment of the most
desirable probe type (e.g., offering the highest contact reliability)
to test sites from a set of sites requiring a given number of probes.
(There are many such sets on a given board.)

      However, dimensional characteristics of the probe types with
respect to the geometry and location of the test sites constrains the
assignment decisions for electrical considerations.  The decision
problem is modeled as an integer mathematical program.  Three
constraint classes are required in the model:  (i) To each test site,
at most one probe of any kind may be assigned, (ii) the number of
probes required for any subset of test sites is strictly observed,
and (iii) proximity relationships between neighboring probes must be
observed.  The current implementation of the model uses IBM's
mathematical programming system MPSX/MIP 370.  To insure efficient
convergence of the solution, the automatic model generator developed
judiciously converts the constraints (iii) to all unitary coefficient
constraints. The inputs to the system are location of the test sites,
number of the probes required per subsets of test sites, applicable
pr...