System Reliability Engineering Practice

A System Reliability Engineering Practice is a systems engineering practice that emphasizes dependability and aims at estimating, preventing, and managing the uncertainties and risks of system failure over its lifecycle.

• Context:
  • It can involve System Availability Testing to ensure that a system is available for use when required.
  • It can involve System Testability Testing to determine if the system can be effectively tested for performance and functionality.
  • It can involve System Maintainability Testing to determine how easily the system can be maintained and updated.
  • It can aim to reduce Costs of Failure caused by system downtime, cost of spares, repair equipment, personnel, and cost of warranty claims.
  • It can relate closely to Safety Engineering and System Safety, sharing common methods for analysis.
  • It can also involve analyzing the probabilities of system failure and success to improve reliability.
  • It can generally require attention to detail and good engineering practices.
  • It can be a sub-discipline of Systems Engineering focusing on the dependability in the Product Lifecycle Management of a product.
  • ...
• Example(s):
  • Manufacturing Reliability Engineering Practice: Developing maintenance protocols and employing Predictive Maintenance techniques to minimize system downtime and maximize efficiency in a Manufacturing Plant.
  • Data Center Reliability Engineering Practice: Implementing redundant systems, such as backup power supplies and failover clusters, in Data Centers to ensure high Availability and minimize service interruptions.
  • Automotive Reliability Engineering Practice: Analyzing failure patterns and conducting Stress Testing of an automotive braking system to improve its reliability and ensure the safety of passengers.
  • Telecommunication Reliability Engineering Practice: Utilizing Fault Tolerance techniques and monitoring network performance to guarantee reliable and uninterrupted communication services in a Telecommunication Network.
  • Software Reliability Engineering Practice: Implementing rigorous testing methodologies, such as Unit Testing, Integration Testing, and Stress Testing, and utilizing Version Control systems in software development to ensure the reliability and stability of software applications across different platforms and environments.
  • ...
• Counter-Example(s):
  • a System Functionality Improving Practice, with ancillary consideration reliability.
  • A Reactive System Failure Management Process, without preventive measures.
  • ...
• See: Safety Factor, Dependability, Product (Business), Cost-Effectiveness, Service Life, Maintenance, Repair and Operations, Stochastic.

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References

2023

• (Wikipedia, 2023) ⇒ https://en.wikipedia.org/wiki/reliability_engineering Retrieved:2023-6-15.
  • Reliability engineering is a sub-discipline of systems engineering that emphasizes the ability of equipment to function without failure. Reliability describes the ability of a system or component to function under stated conditions for a specified period of time. Reliability is closely related to availability, which is typically described as the ability of a component or system to function at a specified moment or interval of time. The reliability function is theoretically defined as the probability of success at time t, which is denoted R(t). In practice, it is calculated using different techniques and its value ranges between 0 and 1, where 0 indicates no probability of success while 1 indicates definite success. This probability is estimated from detailed (physics of failure) analysis, previous data sets or through reliability testing and reliability modeling. Availability, testability, maintainability and maintenance are often defined as a part of "reliability engineering" in reliability programs. Reliability often plays the key role in the cost-effectiveness of systems. Reliability engineering deals with the prediction, prevention and management of high levels of “lifetime” engineering uncertainty and risks of failure. Although stochastic parameters define and affect reliability, reliability is not only achieved by mathematics and statistics. "Nearly all teaching and literature on the subject emphasize these aspects, and ignore the reality that the ranges of uncertainty involved largely invalidate quantitative methods for prediction and measurement." For example, it is easy to represent "probability of failure" as a symbol or value in an equation, but it is almost impossible to predict its true magnitude in practice, which is massively multivariate, so having the equation for reliability does not begin to equal having an accurate predictive measurement of reliability. Reliability engineering relates closely to Quality Engineering, safety engineering and system safety, in that they use common methods for their analysis and may require input from each other. It can be said that a system must be reliably safe. Reliability engineering focuses on costs of failure caused by system downtime, cost of spares, repair equipment, personnel, and cost of warranty claims.

1996

• (Lyu, 1996) ⇒ Michael R. Lyu. (1996). “Handbook of Software Reliability Engineering. Vol. 222.” CA: IEEE computer society press, 1996.

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2023

• (Wikipedia, 2023) ⇒ https://en.wikipedia.org/wiki/Reliability_engineering Retrieved:2023-7-10.
  • Reliability engineering is a sub-discipline of systems engineering that emphasizes the ability of equipment to function without failure. Reliability describes the ability of a system or component to function under stated conditions for a specified period of time. Reliability is closely related to availability, which is typically described as the ability of a component or system to function at a specified moment or interval of time. The reliability function is theoretically defined as the probability of success at time t, which is denoted R(t). In practice, it is calculated using different techniques and its value ranges between 0 and 1, where 0 indicates no probability of success while 1 indicates definite success. This probability is estimated from detailed (physics of failure) analysis, previous data sets or through reliability testing and reliability modeling. Availability, testability, maintainability and maintenance are often defined as a part of "reliability engineering" in reliability programs. Reliability often plays the key role in the cost-effectiveness of systems. Reliability engineering deals with the prediction, prevention and management of high levels of "lifetime" engineering uncertainty and risks of failure. Although stochastic parameters define and affect reliability, reliability is not only achieved by mathematics and statistics. "Nearly all teaching and literature on the subject emphasize these aspects, and ignore the reality that the ranges of uncertainty involved largely invalidate quantitative methods for prediction and measurement." For example, it is easy to represent "probability of failure" as a symbol or value in an equation, but it is almost impossible to predict its true magnitude in practice, which is massively multivariate, so having the equation for reliability does not begin to equal having an accurate predictive measurement of reliability. Reliability engineering relates closely to Quality Engineering, safety engineering and system safety, in that they use common methods for their analysis and may require input from each other. It can be said that a system must be reliably safe. Reliability engineering focuses on costs of failure caused by system downtime, cost of spares, repair equipment, personnel, and cost of warranty claims.