Profust reliability of a gracefully degradable system
Research in traditional reliability theory is based mainly on probist reliability, which uses a binary state assumption and classical reliability distributions. In the present paper the binary state assumption has been replaced by a fuzzy state assumption, thereby leading to profust reliability estimates of a powerloom plant, which is modelled as a two unit gracefully degradable system. Results of Bowles and Palaez [Application of fuzzy logic to reliability engineering, Proc. IEEE 83(3) (1995) 435-449] have been deduced as a particular case of results presented here. It is also recognized that estimation of system parameters such as failure rates, is vital in reliability estimation. Available methods for such estimation do not cover the underlying uncertainty in the failure data collection involving human judgment, evaluation and decision. In this paper we introduce a new approach based on fuzzy set theory to estimate such system parameters. (C) 2006 Elsevier B.V. All rights reserved.
profust reliability human judgment failure rate estimation defuzzification