DSI International routinely contributes new concepts to the diagnostics and testability industry. Among our contributions are papers presented at industry conferences. Each of the following papers identify true breakthroughs in technology.
Prognostics and Health Management (PHM), 2011 IEEE Conference
Eric Gould, DSI International
Although substantial effort has been spent developing new metrics for the evaluation of prognostic performance, relatively little attention has been directed toward ways in which existing systems analysis practices should be modified to incorporate knowledge from Prognostic Health Management. This paper discusses an approach to modifying system design assessments (such as Reliability, Testability and Maintainability) based on parameters provided within System Prognostic Requirements.
Eric Gould, DSI International
Hybrid Diagnostic Modeling (HDM) is an extension of diagnostic dependency modeling that allows the inter-relationships between a system or device’s tests, functions and failure modes to be captured in a single representation (earlier dependency modeling approaches could represent the relationships between tests and either functions or failure modes). With Hybrid Diagnostic Modeling, the same model can be used for early evaluations of a design’s diagnostic capability, creation of hierarchical FMECAs, prediction of diagnostic performance, and generation of actual runtime diagnostics. This paper examines issues associated with the application of HDM to hierarchical systems, including: the types of diagnostic inference used to interpret the relationships between functions and failure modes, the correlation of functional and failure-based reliability data, and diagnostic assessment using Hybrid Diagnostic Models.
Ion A Neag TYX Corp., Stefan Gal TYX Corp., Danver Hartop DSI International
This paper highlights the importance of data type extensibility for preventing software obsolescence in Automatic Test Systems. It describes solutions proposed by the authors for supporting such extensibility in several interfaces of Automatic Test Systems. Some of these solutions are proposed for interface standards currently under development, while others are implemented in existing commercial products.
Published: AutoTestCon 2000
Authors: Eric Gould DSI International, Danver Hartop DSI International
This paper will discuss the use of diagnostic simulations to generate the Fault Resolution metric for a system or equipment. Simulation-based calculations are free of some of the biases that inhere within traditional, math-based approaches. Moreover, a simulation-based evaluation of the replacement of failed items also provides a basis for the calculation of the effect of diagnostic ambiguity upon false removals — including the estimated costs that can be attributed to removals beyond those that would be expected during a product’s intended lifetime.
Eric Gould DSI International, Danver Hartop DSI International
This paper exposes some major deficiencies inherent within current methods for assessing design Testability—critical shortcomings that not only might cause adherence to contracted Testability requirements to be in conflict with long-term maintenance goals (such as Life Cycle Cost and Operational Availability), but could also result in evaluations that fail to predict the actual diagnostic behavior of the system or device. In recent years, the need to accurately forecast diagnostic performance has become more essential as more development projects are contractually linked to the maintenance of the fielded product (as witnessed by the recent emergence of maintenance warranties and the combined contracting of development and maintenance efforts). What is needed are Testability procedures that can better serve long-term maintenance and support objectives, yet remain true to the discipline’s original intent of providing diagnostics-based feedback in early phases of the development cycle. Hoping to foster a less conflicted Testability practice, this paper proposes some alternatives to current quantitative methods of Testability assessment that can more accurately predict diagnostic behavior and more consistently reflect the relationships between a system or device’s diagnostic capability and its Life Cycle Cost and Operational Availability.