Electrical Testing at UCSB: Hybrids, Modules, & Rods Anthony Affolder On behalf of the UCSB testing group

Testing personnel at UCSB Professors Joe Incandela Claudio Campagnari Post-docs Anthony Affolder Patrick Gartung (UC-Riverside) Russell Taylor Graduate Students Steve Levy ( now post-doc @ University of Chicago) Jim Lamb Brad Patterson (returning this summer) Electrical Engineering Support Sam Burke Mechanical Engineering Support David Hale Dean White Undergraduates Derek Barge (B.S. Physics) Chris McGuinness Lance Simms (B.S. Physics) Joined group since February, 2003

Faulty Channel Sources Fault Sources (excluding cable breaks and CMN) Hybrid-0.012% Sensor (in DB)-0.33% Sensor (not in DB)-0.19% Either high noise and/or visible sensor damage Bonding-0.034% Mostly due to early pitch-adaptors (RMT). No problems seen with production pitch-adaptors (PLANAR). Testing-0.049% Mostly due to an early problem which has been alleviated Total faults – 0.63% We introduce only 0.095% bad channels per modules on average Grade A Grade B Grade C

Fault Finding Using ARCS (3) Test failures are correlated in order to diagnose fault type Open (1 or 2 sensor) Short Pinhole/Saturated Channel Noisy Channels Mid-sensor opens Faults are found >99% with correct fault type identified ~90% of the time Misidentification is almost always between 1 or 2 sensor opens Less than .1% of good channel flagged as faulty As more modules are built, fault finding criteria will be re-tuned to improve performance Integrated into ARCS software by Aachen Database output of module testing is being finalized Similar tuning of fault finding underway for DAQ-based systems Led by Patrick Gartung (UC-Riverside)