Journal of Quality Engineering and Management

Abstract Purpose: This paper presents an innovative model for the simultaneous optimization of redundancy allocation and condition-based maintenance in series-parallel load-sharing systems. The primary objective of the model is to determine the optimal level of redundancy so that costs are minimized while system reliability constraints are met.
Methodology: In this research, stochastic dependencies between system components are considered using the proportional hazards model and tempered failure rates to assess reliability accurately. Additionally, transition probability matrices are used to determine the optimal maintenance limits for each subsystem, and periodic inspections are performed. The proposed model is solved using MATLAB, and its performance is evaluated under four different scenarios: 1) a baseline model without redundancy or stochastic dependencies, 2) redundancy allocation without stochastic dependencies, 3) stochastic dependencies without redundancy, and 4) the proposed model.
Findings: The results show that the proposed model achieves an optimal balance between cost and reliability, reducing both failure and maintenance costs. Compared to the various scenarios, the proposed model demonstrates superior performance in optimizing costs and enhancing reliability. The findings also emphasize the importance of simultaneously considering stochastic dependencies and redundancy allocation to improve system performance.
Originality/Value: This research introduces a novel approach by simultaneously considering stochastic dependencies and redundancy allocation in series-parallel load-sharing systems. The proposed model significantly improves system performance and reduces failure and maintenance costs. It underscores the importance of integrating these two factors in optimizing complex engineering systems.

Abstract Purpose: The goal of this research is to establish a design framework based on reliability for submarine pressure hulls, with the aim of attaining an ideal equilibrium between structural integrity and reliability.
Methodology: Initially, a mechanical Finite Element Model (FEM) was created and verified by comparing it to experimental data. Following that, various alternative models created through weight optimization algorithms were formulated. Uncertainties were represented using random variables, and reliability assessments were performed for each design.
Findings: The findings suggest that optimized models, even with reduced weights, can provide satisfactory failure probabilities. The prioritization derived from the reliability analysis offers a clear view of the final design.
Originality/Value: This study's uniqueness stems from its combined application of finite element analysis, uncertainty modeling, and optimization methods in reliability-based pressure hull design, a strategy seldom utilized in marine structural design.