Definition and Importance of Reliability Engineering
- Reliability engineering is a sub-discipline of systems engineering that focuses on the ability of equipment to function without failure.
- Reliability is 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 refers to the ability of a component or system to function at a specified moment or interval of time.
- The reliability function, denoted as R(t), represents the probability of success at time t.
- Reliability engineering is essential for cost-effectiveness of systems and plays a key role in minimizing system downtime and warranty claims.
Prediction and Management in Reliability Engineering
- Reliability engineering deals with the prediction, prevention, and management of engineering uncertainty and risks of failure.
- Reliability is not solely achieved through mathematics and statistics, but also requires consideration of other factors.
- Detailed analysis, previous data sets, reliability testing, and reliability modeling are used to estimate reliability.
- Availability, testability, maintainability, and maintenance are important aspects of reliability engineering.
- Reliability engineering relates closely to Quality Engineering, safety engineering, and system safety.
History and Evolution of Reliability Engineering
- The term 'reliability' can be traced back to 1816, first used by poet Samuel Taylor Coleridge.
- Before World War II, reliability was associated with repeatability and obtaining consistent results.
- Dr. Walter A. Shewhart promoted product improvement through statistical process control in the 1920s.
- The U.S. military defined the modern use of 'reliability' in the 1940s, characterizing a product that operates as expected for a specified period.
- Reliability engineering gained prominence during World War II due to the unreliability of electronic equipment and fatigue issues.
- In the 1960s, reliability testing on component and system level became more emphasised.
- Pragmatic approaches, as used in consumer industries, were adopted in the 1980s.
- The reliability of integrated circuits (ICs) improved significantly, but system-level issues became more prominent.
- Software became crucial for system reliability, leading to the development of the Capability Maturity Model (CMM).
- New technologies such as micro-electromechanical systems (MEMS) and handheld devices posed challenges in maintaining reliability.
Objectives and Importance of Reliability Engineering
- The objectives of reliability engineering, in decreasing order of priority, are: prevent or reduce the likelihood of failures, identify and correct the causes of failures, determine ways to cope with failures, estimate the likely reliability of new designs and analyze reliability data.
- Reliability engineering aims to improve product performance and meet or exceed customer expectations.
- Reliability engineering minimizes costs and ensures reliable products.
- Key skills include understanding and anticipating causes of failures and knowledge of prevention methods.
- Various reliability techniques include fault tree analysis (FTA), Reliability Centered Maintenance (RCM), and reliability testing.
- Proper analysis and attention to detail are crucial for effective reliability engineering.
- Reliability program plans specify tasks and requirements for different systems.
Reliability Requirements and Design
- Reliability engineering specifies reliability and maintainability requirements derived from design failure analysis or prototype test results.
- Clear requirements constrain designers from creating unreliable items, constructions, interfaces, or systems.
- Reliability requirements address the system itself, including test and assessment requirements.
- Reliability design requirements aim to prevent failures or limit their consequences.
- Design requirements should be precise and provable through analysis or testing.
- Maintainability requirements address repair costs and repair time.
- Testability requirements link reliability and maintainability and focus on failure detectability and isolation.
- Humans can detect failures, correct them, and improvise in abnormal situations.
- Policies that exclude human actions may not effectively improve reliability.
- Human errors in management, data organization, and item misuse can contribute to unreliability.
- Achieving high reliability requires a robust systems engineering process, proper planning, and execution of validation and verification tasks.
- Design for Reliability (DfR) is a process to ensure that a product meets its reliability requirements.
- DfR is implemented in the design stage of a product to proactively improve product reliability.
- Reliability design begins with the development of a system model.
- Block diagrams and Fault Tree Analysis are used to evaluate the relationships between different parts of the system.
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.
