Towards Refinement and Generalization of Reliability Models Based on Component States

TL;DR

This paper introduces methods for generalizing and refining reliability models using metamodeling techniques, which help in iterative complex system design by automating model adjustments and improving accuracy.

Contribution

It presents a novel approach to metamodeling reliability models through systematic generalization and refinement operations based on system constraints.

Findings

Defined generalization and refinement operations on reliability models

Applied the methods to Markov chain-based reliability formalism

Demonstrated potential for iterative system design improvements

Abstract

Complex system design often proceeds in an iterative fashion, starting from a high-level model and adding detail as the design matures. This process can be assisted by metamodeling techniques that automate some model manipulations and check for or eliminate modeling mistakes. Our work focuses on metamodeling reliability models: we describe generalization and refinement operations for these models. Generalization relaxes constraints that may be infeasible or costly to evaluate; refinement adds further detail to produce a model that more closely describes the desired system. We define these operations in terms of operations on system constraints. To illustrate the proposed method, we relate these constraints to a common Markov chain-based reliability modeling formalism.