Abstract
This paper presents general renewal processes (GRP) to model and analyze complex repairable systems with various degrees of repair. A general likelihood function formulation for single and multiple repairable systems is presented for estimation of the GRP parameters. Confidence bounds based on the Fisher information matrix are also developed. The practical use of the proposed statistical inference is demonstrated by two examples, and the results show that our proposed method is a very promising and efficient approach with the potential of becoming very useful in industry and of leading to further generalization of repairable systems analysis.
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