A Novel Feasibility Based Approach for Redundancy Allocation and Reliability Based Cost Optimization

In the field of reliability and cost optimization, the cost function plays a crucial role in all real-life applications. Conevtionally, cost of a component is assumed directly proportional to the component reliability only. However, this assumption ignores the crucial impact of the component feasibility which determines manufacturability, design adaptability, resource availability, and operational suitability on system performance and cost. This indicates the need of a cost function that considers the component reliability along with the component feasibility. To address this issue this work proposes a modified cost function for the component which integrates the feasibility parameter along with component reliability. The proposed work aims to strike a balance between system’s reliability and cost by introducing the modified cost optimization problem while the system’s reliability with multiple redundancy arrangements taken as a constraint. By leveraging the general model of Abrasive Jet Machining (AJM), this study explores the trade-off between reliability and cost across different levels of feasibility. To tackle this complex non-linear mixed-integer mathematical optimization problem and system designing, a well-established metaheuristic Particle Swarm Optimization (PSO) algorithm is developed. Additionally, a comparative study with a widely used benchmark series system, is presented for method validation. This research offers a practical framework for industries to enhance the reliability of systems while optimizing costs with a sincere consideration of component’s feasibility.