The University of Tokyo · Engineering
Professor Samir Khan's research lab focuses on the challenges of fault diagnosis and maintenance in complex engineered systems, particularly in aerospace and electromechanical applications. The lab investigates persistent issues such as No-Fault Found (NFF) events, diagnostic granularity, and the impact of system complexity on troubleshooting reliability. It also explores advanced control methodologies, including non-uniform sampling and inverse probability weighting techniques, to improve system diagnostics and decision-making under uncertainty. The lab emphasizes industry-university collaboration to standardize terminology, optimize maintenance practices, and enhance diagnostic capabilities through sensor integration and data-driven approaches.
Figures are computed from collected data and may differ slightly.
This paper reviews the literature dealing with the nature and characteristics of no-fault found events within maintenance lines. Increasing systems complexities have seen a rise in the number of unknown faults that are being reported during operational service. Units tagged as 'No-Fault Found' are evidence that a serviceable component was removed, and attempts to troubleshoot the root cause have been unsuccessful. This scenario worsens when faults occurring at the component level are intermitten
Most conventional control algorithms cause numerical problems where data is collected at sampling rates that are substantially higher than the dynamics of the equivalent continuous-time operation that is being implemented. This is of relevant interest in applications of digital control, in which high sample rates are routinely dictated by the system stability requirements rather than the signal processing needs. Digital control systems exhibit bandwidth limitations enforced by their closed-loop
Purpose – The purpose of this paper is to present the successes and barriers from an industry-university partnership on studying the impact of No Fault Found (NFF) events. As a consequence, various opportunities are explored to engage with industry to investigate the problem. A comprehensive training is also outlined to ensure that experience and troubleshooting techniques can be disseminated as guidelines across businesses. Design/methodology/approach – The study was performed by Cranfield Univ
Abstract Inverse probability weighting (IPW) is a general tool in survey sampling and causal inference, used in both Horvitz–Thompson estimators, which normalize by the sample size, and Hájek/self-normalized estimators, which normalize by the sum of the inverse probability weights. In this work, we study a family of IPW estimators, first proposed by Trotter and Tukey in the context of Monte Carlo problems, that are normalized by an affine combination of the sample size and a sum of inverse weigh
The paper discusses the importance of granularity in maintenance requirements. This becomes significantly important when investigating false alarms that cannot be verified, nor duplicated under typical inspections. Continuing advances in electromechanical systems, such as an aircraft's fuel system, can frequently face a high number of No Fault Found (NFF) events due to design limitations associated with fault diagnosability. This work discusses such maintenance requirements whilst covering the h
Various applications in digital systems require the involvement of concepts from\nsignal processing and filtering. These specific problems often need the linear dynamic systems\nto have a transfer function that can specify the behavioural characteristics of the system. When\noperating in the digital domain, such functions can effectively be used to approximate the same\ncharacteristics over the frequency range of importance as any given continuous-time transfer\nfunction. In the case with unifor
There is a phenomenon which exists in complex engineered systems, most notably those which are electrical or electronic which is the inability to diagnose faults reported during operation. This includes difficulties in detecting the same reported symptoms with standard testing, the inability to correctly localise the suspected fault and the failure to diagnose the problem which has resulted in maintenance work. However an inconsistent terminology is used in connection with this phenomenon within
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