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Failures over useful life are random but have an average rate: Poisson Process

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Result #3:. # Failures/yr = #Units * S l i = 7.20. Reliability Analysis of a Low Voltage Power Supply Design for the Front-End Electronics of the ATLAS Tile Calorimeter. Gary Drake, Member IEEE , James Proudfoot Argonne National Laboratory, Lemont, IL USA. - PowerPoint PPT Presentation
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Argonne National Laboratory is a U.S. Department of Energy laboratory managed by U Chicago Argonne, LLC. – Failures over useful life are random but have an average rate: Poisson Process – Probability of k failures between time t and t+t: Poisson Distribution The TileCAL Low Voltage System Reliability Analysis Methodology Calculations Power for TileCAL Front-End Electronics Novel Switching DC-DC Power Supply Custom, Compact, High-Efficiency, 250 Watt 8 Different Voltages Customized Bricks Water Cooled; System Interface & Monitoring Environment: Magnetic Field, Radiation Tolerant 256 boxes on detector, 2048 bricks, + spares Reliability is Important Infrequent Access End of Long Barrel Detector Section LVPS Access on Detector Drawer Electronics LVPS Box 8 bricks per Box LVPS Brick Reliability Analysis of a Low Voltage Power Supply Design for the Front-End Electronics of the ATLAS Tile Calorimeter Abhirami Senthilkumaran , Bruce Mellado, Anusha Gopalakrishnan, Sanish Mahadik University of Wisconsin-Madison, Madison, WI USA On Behalf of the ATLAS Tile Calorimeter System Gary Drake, Member IEEE, James Proudfoot Argonne National Laboratory, Lemont, IL USA 2. Series-Parallel Model and Voltage De-rating for Capacitor Tantalum capacitors most critical Rated for 35V, used at <= 15V Higher voltage rating reduces failure When a capacitor fails Probability of short = 0.75; Probability of open = 0.25 Also include 4 caps in parallel + diodes + LC filter Failures in Electronics Failures generally described by the Bathtub Curve Interested in region of Constant Failure Rate 1. Series Reliability Model Any single failure can cause brick to fail Use only critical parts in model Assume Part failures are independent & random Start with single tantalum cap Parts Count Method Use FITS values for each part Mean Time Between Failures MTBF Expected time between failures MTBF = 1 / l This is not “useful lifetime” Probability of Failure-Free Operation Probability of no failures at time t R(t) = e -lt Must calculate l for the entire unit 3. Comparison with Previous Design Rated voltage of capacitor is 20V Calculated failure rate: 12.4 bricks/year Observed failure rate: 5.2 bricks/year From 3 years of operation # Failures/yr = #Units * = 7.20 Dominated by Tantalum Reliability Result #1: # Failures/yr = #Units * S [l i * w i ] = 5.03 Still Dominated by Tantalum Reliability Result #2: Result #3: We have performed a reliability analysis on the new upgraded supplies 2048 Bricks in the detector system Expect 2.11 failures per year in the system l = Average number of units failing per unit time Measured in Failures In Time FITS (# / 10 9 hrs) Part Failures/10 9 hr IR2110S FET Driver 43.6 IRFS9N60 MOSFET 0.544 Inductor 470 uH 10 Capacitor 47 uF 288 HCPL7800 Opto- Isolator 52 LM6142 Op-Amp 2 LT1681 Controller Chip 6.04 # Failures/yr = # Units * S [l i * w i ] X x Statistical Analysis Poisson distribution; Neyman procedure Use observations as a correction R(t = 2 yrs) R(t = 5 yrs) R(t = 10 yrs) R(t = 20 yrs) 0.992992 0.982573 0.965450 0.932094 R(t = 2 yrs) R(t = 5 yrs) R(t = 10 yrs) R(t = 20 yrs) 0.995097 0.987788 0.975727 0.952049 R(t = 2 yrs) R(t = 5 yrs) R(t = 10 yrs) R(t = 20 yrs) 0.997938 0.994853 0.989732 0.979569
Transcript
Page 1: Failures over useful life are random but have an       average rate:  Poisson Process

Argonne National Laboratory is a U.S. Department of Energy laboratory managed by U Chicago Argonne, LLC.

– Failures over useful life are random but have an average rate: Poisson Process

– Probability of k failures between time t and t+t: Poisson Distribution

The TileCAL Low Voltage System

Reliability Analysis Methodology

Calculations

• Power for TileCAL Front-End Electronics• Novel Switching DC-DC Power Supply– Custom, Compact, High-Efficiency, 250 Watt– 8 Different Voltages Customized Bricks– Water Cooled; System Interface & Monitoring– Environment: Magnetic Field, Radiation Tolerant• 256 boxes on detector, 2048 bricks, + spares Reliability is Important Infrequent Access

End of Long Barrel Detector Section

LVPS Access

on Detector Drawer Electronics

LVPS Box8 bricks per Box

LVPS Brick

Reliability Analysis of a Low Voltage Power Supply Design

for the Front-End Electronics of the ATLAS Tile Calorimeter

Abhirami Senthilkumaran, Bruce Mellado, Anusha Gopalakrishnan, Sanish MahadikUniversity of Wisconsin-Madison, Madison, WI

USAOn Behalf of the ATLAS Tile Calorimeter System

Gary Drake, Member IEEE, James Proudfoot

Argonne National Laboratory, Lemont, IL USA

2. Series-Parallel Model and Voltage De-rating for Capacitor– Tantalum capacitors most critical– Rated for 35V, used at <= 15V– Higher voltage rating reduces failure

When a capacitor fails– Probability of short = 0.75; Probability of open = 0.25 Also include 4 caps in parallel + diodes + LC filter

• Failures in Electronics– Failures generally described by the Bathtub Curve

– Interested in region of Constant Failure Rate

1. Series Reliability Model– Any single failure can cause brick to fail– Use only critical parts in model

Assume – Part failures are independent & random Start with single tantalum cap Parts Count Method– Use FITS values for each part

• Mean Time Between Failures MTBF– Expected time between failures– MTBF = 1 / l – This is not “useful lifetime”

• Probability of Failure-Free Operation– Probability of no failures at time t– R(t) = e-lt

Must calculate l for the entire unit

3. Comparison with Previous Design– Rated voltage of capacitor is 20V– Calculated failure rate: 12.4 bricks/year

– Observed failure rate: 5.2 bricks/year– From 3 years of operation

# Failures/yr = #Units * S li = 7.20

Dominated by Tantalum Reliability

Result #1: # Failures/yr = #Units * S [li * wi] = 5.03

Still Dominated by Tantalum Reliability

Result #2: Result #3:

We have performed a reliability analysis on the new upgraded supplies 2048 Bricks in the detector system

Expect 2.11 failures per year in the system

– l = Average number of units failing per unit time– Measured in Failures In Time FITS (# / 109 hrs)

Part Failures/109 hrIR2110S FET Driver 43.6IRFS9N60 MOSFET 0.544Inductor 470 uH 10Capacitor 47 uF 288HCPL7800 Opto-Isolator 52LM6142 Op-Amp 2LT1681 Controller Chip 6.04

# Failures/yr = # Units * S [li * wi] X x

Statistical Analysis– Poisson distribution; Neyman procedure

Use observations as a correction

R(t = 2 yrs) R(t = 5 yrs) R(t = 10 yrs) R(t = 20 yrs)

0.992992 0.982573 0.965450 0.932094

R(t = 2 yrs) R(t = 5 yrs) R(t = 10 yrs) R(t = 20 yrs)

0.995097 0.987788 0.975727 0.952049

R(t = 2 yrs) R(t = 5 yrs) R(t = 10 yrs) R(t = 20 yrs)

0.997938 0.994853 0.989732 0.979569

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