Failure Logs Research Articles

Timing-Aware Multiple-Delay-Fault Diagnosis

With feature sizes steadily shrinking, manufacturing defects and parameter variations often cause design timing failures. It is essential that those errors be correctly and quickly diagnosed. In this paper, we analyze the multiple-delay-fault diagnosis problem and propose a novel approach to solve it. We enhance the diagnostic resolution by processing failure logs at various slower-than-nominal clock frequencies. We evaluate the utility of n-detection and timing-aware automatic-test-pattern-generated (ATPG) sets. Experimental results show that using timing-aware ATPG sets yields better diagnostic resolution and results in better delay-defect-size estimations compared to n -detection ATPG sets. We experimentally determined our diagnosis algorithm's sensitivity to delay variations.

Improving the Resolution of Single-Delay-Fault Diagnosis

With feature sizes steadily shrinking, manufacturing defects and parameter variations often cause design-timing failures. It is essential that those errors be correctly and quickly diagnosed. The existing delay-fault diagnosis algorithms cannot identify delay faults that require nonrobust test patterns due to incorrect emulation of the failure analyzer's behavior. We propose a novel approach to performing delay-fault diagnosis for robust and nonrobust tests. We enhance the diagnostic resolution by utilizing passing patterns, processing failure logs at various slower frequencies, and applying n-detection and timing-aware automatic test pattern generation sets. Experimental results show that our approach can diagnose delay faults with good resolution. The algorithm is stable with respect to delay variations that manufactured chips might experience.

Maintenance Manager to control operation and maintenance of offshore wind farms

Maintenance of wind farms is of increasing importance. Especially in remote areas, where logistics and accessibility are restricted, costs of preventive as well as corrective maintenance form a substantial part of the costs of electricity. The importance of a tool that assists in feedback to the design, failure logging, configuration control and maintenance planning is evident. This paper describes the importance of such a tool, the functional specifications that should be met and the experience with implementation of such a system at a wind turbine manufacturer.

Dynamic fatigue of feldspathic porcelain

Several studies (Sherrill and O'Brien, 1974; Southan and Jørgensen, 1974; Jones, 1983) have shown that stress corrosion fatigue occurs in dental porcelains. Morena et al. (1986) reported on an assessment of slow crack growth parameters for dental ceramics. The purpose of the study reported here was to evaluate the fatigue parameters of a model experimental porcelain using dynamic fatigue testing. This test procedure makes use of several constant stressing rates to perform strength tests. Dynamic stress testing was first described by Evans (1974) and later defined as a distinct test modality by Ritter (1978). From such data, the fatigue parameters can be calculated. These fatigue parameters, n and σ ƒ0 , are, respectively, the crack growth exponent from the crack velocity expression and a materials constant which is dependent on the test environment and the inert (moisture-free) strength. The model porcelain was made from 60% component 1 and 40% component 3 according to the Weinstein patent (Weinstein, et al., 1962). The biaxial flexure strength of 300 specimens 1 mm thick was tested in 37°C water by testing 50 samples at each of 6 constant stressing rates: 100, 10, 1 0.1, 0.01, and 0.001 MPa/s. One hundred specimens were tested in a moisture-free environment at 100 MPa/s using a servo-mechanical testing machine. A commercial porcelain (Jelenko Gingival-Lot# 2012, Jelenko Dental Health Products, Armonk, NY, USA) was chosen as a reference material. One hundred twenty specimens were tested using the same procedures as those used for the model porcelain; however, only 20 samples were tested for 5 stressing rate groups and an inert group. Fatigue parameters with their respective standard errors for the model porcelain were n = 28 ± 1.00, and σ ƒ0 = 58.7 ± 0.31 MPa . Values for the commercial porcelain were n=27.6 ± 2.00 and σ ƒ0 = 49.1 ± 0.51 MPa . These parametric values were obtained from the constants of a linear regression of LOG failure stress vs LOG time to failure obtained from constant stressing rate data for all of the stressing rate groups tested in water for each porcelain. Readers are cautioned that direct extrapolation of the results of this research to clinical applications could be misleading. The additional effects of porcelain to metal bonding on fatigue are poorly understood at this time. A report on preliminary results of porcelain-fused-to-metal disk strength has been presented (Fairhurst et al., 1992), and fatigue parameter evaluations at this laboratory are in progress.

A Statistical Failure/Load Relationship: Results of a Multicomputer Study

In this correspondence we present a statistical model which relates mean computer failure rates to level of system activity. Our analysis reveals a strong statistical dependency of both hardware and software component failure rates on several common measures of utilization (specifically CPU utilization, I/O initiation, paging, and job-step initiation rates). We establish that this effect is not dominated by a specific component type, but exists across the board in the two systems studied. Our data covers three years of normal operation (including significant upgrades and reconfigurations) for two large Stanford University computer complexes. The complexes, which are composed of IBM mainframe equipment of differing models and vintage, run similar operating systems and provide the same interface and capability to their users. The empirical data comes from identically structured and maintained failure logs at the two sites along with IBM OS/VS2 operating system performance/load records.