Analyzing Reliability And Cost When Designing System Compone

Analyzing Reliability and Cost When Designing System Components

The assignment focuses on evaluating system reliability based on component reliability, backup systems, and cost analysis for outsourcing versus in-house production. Specifically, it involves calculating the required reliability for individual components in a series system, assessing the impact of backup components on overall system reliability, determining the necessary reliability of components within a server system to meet a targeted overall reliability, and performing cost-benefit analyses for outsourcing and insourcing decisions. Each problem emphasizes understanding the interplay between reliability, redundancy, and economic considerations in system design and operation.

Paper For Above instruction

Introduction

The design of reliable and cost-effective systems is central to engineering and management practices across various industries. System reliability, the probability that a system performs its intended function without failure, significantly influences operational efficiency, safety, and customer satisfaction. This paper explores several key aspects of system reliability and cost analysis, including calculating the required reliability of individual components in a series system, analyzing the effect of backup components on overall reliability, determining the reliability requirement for a server system with multiple components, and evaluating the economic implications of outsourcing versus in-house production. These concepts are integral to making informed decisions that balance performance, redundancy, and cost.

Reliability in Series Components

In many systems, components are arranged in series, where the failure of any single component results in system failure. The system reliability (R_sys) for such arrangements is the product of the reliabilities of all components, assuming they are independent and identical. When a system consists of three main components in series, each with the same reliability (R), the overall system reliability is expressed as R_sys = R^3.

Given a target system reliability of 0.998, we solve for R: R = (R_sys)^(1/3). Substituting, R = (0.998)^(1/3). Calculating this value yields approximately 0.99933. This means each component must have a reliability of about 99.933% to ensure the overall system meets the desired reliability. Such high reliability often requires quality assurance and redundancy strategies at the component level to mitigate potential failures effectively.

Impact of Backup Components on Reliability

Adding backup components can enhance system reliability by providing redundancy. Consider a bank system with three primary components, each with a backup that has a reliability of 0.80. The system's overall reliability depends on whether the backup is active or passive. Generally, if the backup activates upon primary failure, the combined reliability of a primary and backup component can be calculated using the formula:

R_combined = R_primary + (1 - R_primary) * R_backup.

Assuming each primary component has a reliability of R, and the backup reliability is 0.80, the effective reliability per component increases. For example, if R is 0.90, then R_combined = 0.90 + (1 - 0.90) 0.80 = 0.90 + 0.10 0.80 = 0.98. Consequently, the overall system reliability significantly improves, illustrating the benefit of redundancy. The total system reliability in this case would depend on how many components are in series and whether multiple redundancies are implemented.

Reliability Requirements for a Server System

In a university web server with five main components each with the same reliability (R), and all must work simultaneously for the server to function, the overall system reliability (R_sys) is again the product of individual reliabilities: R_sys = R^5. If the university aims for a 95% overall reliability, we solve for R: R = (0.95)^(1/5).

Calculating this, R ≈ 0.9895, indicating each component must have approximately 98.95% reliability for the server to meet the desired operational threshold. Achieving such high reliability may involve using durable hardware, regular maintenance, and effective fault tolerance practices to minimize potential failures and maintain service availability.

Reliability Analysis for a New Product System

System reliability analysis includes assessing the reliability of a proposed system configuration comprising various components such as RC, RB, and RS. Suppose the reliabilities of these components are unknown; calculating the overall system reliability depends on how these components are arranged—serial, parallel, or a combination. For example, if the system components are in series, the total reliability R_total = R_C R_B R_S; if in parallel or with redundancy, the calculation involves considering alternative pathways and redundancy strategies.

Understanding the system configuration allows engineering teams to determine the reliability threshold for each component to meet the system-level requirements. Typically, detailed reliability block diagrams and failure mode analyses help in designing systems that meet functional and safety standards efficiently.

Cost Analysis: Outsourcing vs. In-House Production

Cost management decisions often involve comparing the total costs of outsourcing versus making components internally. The total costs include fixed costs (FC) and variable costs (VC), which vary with quantity. Calculating the indifference point—the quantity where total costs are equal—enables managerial decisions based on expected demand.

For example, if approximated costs are known for in-house production and outsourcing, the total costs for each option can be modeled as functions of quantity: Total_Cost_Make = FC_make + VC_make Q, and Total_Cost_Buy = FC_buy + VC_buy Q. Setting these equal allows determination of the quantity at which both options cost the same. If the expected demand exceeds this point, outsourcing might be more economical; otherwise, in-house production is preferable.

An in-depth analysis also considers factors like quality control, supply chain reliability, and strategic control over manufacturing processes, which influence the ultimate decision. Making data-driven supply chain choices optimizes resource utilization and reduces total costs while maintaining system reliability and quality standards.

Conclusion

Reliability engineering integrates technical calculations and strategic considerations to optimize system performance and cost-efficiency. Ensuring high component reliability in series systems requires careful selection and testing, while redundancy can provide critical reliability improvements. Additionally, cost analyses like outsourcing and insourcing are essential for resource allocation and operational planning. A comprehensive understanding of these principles supports effective system design, maintenance, and management, ultimately enhancing organizational resilience and competitiveness.

References

• Bobbio, A., & Meloni, C. (2015). Reliability and Maintainability in Practice. John Wiley & Sons.