10th Advances in Reliability Technology Symposium by A. C. Barrell (auth.), G. P. Libberton (eds.)

By A. C. Barrell (auth.), G. P. Libberton (eds.)

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Which will be significantly non-zero. e. being significantly nonzero -therefore merely shows that the co-variate z is having a significant affect on the reliability. It cannot necessarily be used directly for reliability prediction. An example of this is given below when the "time trend" for North Wales is discussed. Constancy of the Underlying Distribution It is a fundamental hypothesis of the PHM formulation that the reliability distribution parameters are independant of the co-variate z. Let, for example, the underlying reliability distribution with z=O (the baseline hazard) be exponential such that:- If the effect of the co-variate z is simply to alter the scaling parameter A then PHM will perfectly describe the process going on.

In some cases it was possible to make minor modifications to the existing reporting systems to satisfy the minimum requirements. However, major modifications of reporting systems were impractical. This in practice meant that the company co-ordinators had to assess several sources within their organisation before final selection. After the initial equipment selection had been finalised, the working group addressed the practical problems associated with the detailed coding of the data input. The type and manner of data recording, not surprisingly, differs between data sources.

J. Wingerden Reliability Data Collection and Use in Risk and Available Assessment. Springer. Verlag, 1986. T. Manning Central Electricity Generating Board 15 Newgate Street London ECIA 7AX ABSTRACT The failure and repair data on the CEGB's overhead line transmission system in North Wales has been analysed to examine its data structure. The data is considerably inhomogenous, with failure and repair rates varying throughout the year; an overall time trend has also been identified. The inhomogeneities were identified using Proportional Hazard Modelling (PHM).

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