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Using Monte Carlo Simulation with BAT and OCBA for the Binary-state Network Reliability Problem
會議論文集

Using Monte Carlo Simulation with BAT and OCBA for the Binary-state Network Reliability Problem

W.-C. Yeh, F.-C. LuoC.-S. Lin
2025 IEEE International Conference on Prognostics and Health Management, ICPHM 2025
2025
Web of Science ID: WOS:001541522800042

摘要

Binary-Addition-Tree Algorithm Monte Carlo Simulation Network Reliability Optimal Computing Budget Allocatin Probe Card Circuit Binary trees Budget control Circuit simulation NP-hard Probes Reliability analysis Binary additions Binary-addition-tree algorithm Computing budget Monte Carlo's simulation Network reliability Optimal computing Optimal computing budget allocatin Probe card circuit Probe cards Tree algorithms Monte Carlo methods
The probe card is an essential tool for measuring the yield of semiconductor wafers and is indispensable in semiconductor testing. To ensure that the probe card functions properly after multiple uses, it is crucial to maintain and verify the performance and accuracy of each probe to avoid impacting product quality and delivery time. This study employs network reliability characteristics to convert the probe card's circuit diagram into a general network for analysis, resulting in the reliability values for the normal operation of each probe within the probe card, thus facilitating the monitoring of its operational reliability. As the scale of the network diagram increases, the complexity of solving it also grows. Determining precise reliability values using traditional mathematical methods is an NP-hard problem. Therefore, this study proposes an Optimal Computing Budget Allocation and Monte Carlo Simulation based on the Binary-Addition-Tree algorithm (BAT-MCS-OCBA) to quickly obtain approximate reliability values. BAT-MCS-OCBA combines the accuracy of the Binary-Addition-Tree algorithm (BAT) with the concept of super vectors, which simplifies the extensive time spent on enumerating variable combinations in BAT. It also utilizes Monte Carlo Simulation (MCS) to simulate subsequent scenarios not considered by the super vector, enhancing accuracy. Finally, Optimal Computing Budget Allocation (OCBA) is applied to allocate resources effectively during simulations, enabling the algorithm to achieve faster approximate reliability values with improved solution quality. © 2025 IEEE.

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https://www.scopus.com/inward/record.uri?eid=2-s2.0-105011029921&doi=10.1109%2fICPHM65385.2025.11062062&partnerID=40&md5=3714bf1fa515e5a8e05177666ccfd090檢視

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