- •14 4.5 Reliability test requirements
- •2 Reliability engineering for complex systems requires a different, more elaborated systems approach than reliability for non-complex systems
- •9 4 Reliability program plan
- •11 4.2 Reliability prediction
- •9 4 Reliability program plan
- •52 Main articles: reliability theory, failure rate.
- •106 The parts stress modelling approach is an empirical method for prediction based on counting the number and type of components of the system, and the stress they undergo during operation.
- •18 7 Accelerated testing
- •39 The probability that a functional unit will perform its required function for a specified interval under stated conditions.
- •12 4.3 System reliability parameters
- •2 Reliability engineering for complex systems requires a different, more elaborated systems approach than reliability for non-complex systems
- •82 Reliability predictions:
- •20 9 Reliability operational assessment
- •21 10 Reliability organizations
- •7 2 Reliability theory
- •36 The capacity of a device or system to perform as designed;
- •20 9 Reliability operational assessment
- •34 Reliability may be defined in several ways:
- •57 Where is the failure probability density function and t is the length of the period of time (which is assumed to start from time zero).
- •58 Reliability engineering is concerned with four key elements of this definition:
- •2 Reliability engineering for complex systems requires a different, more elaborated systems approach than reliability for non-complex systems
- •48 Automotive engineers have reliability requirements for the automobiles (and components) which they design
- •49 Electronics engineers must design and test their products for reliability requirements.
- •127 Failures from occurring. Rcm (Reliability Centered Maintenance) programs can be used for this.
- •96 Serial System: Any assembly of units for which the failure of any single unit will cause a failure of the system or overall mission.
- •45 Many types of engineering employ reliability engineers and use the tools and methodology of reliability engineering. For example:
- •33 A reliability block diagram
- •58 Reliability engineering is concerned with four key elements of this definition:
- •40 The ability of something to "fail well" (fail without catastrophic consequences)
- •23 12 Reliability engineering education
- •148 Human error analysis
- •39 The probability that a functional unit will perform its required function for a specified interval under stated conditions.
2 Reliability engineering for complex systems requires a different, more elaborated systems approach than reliability for non-complex systems
105 The physics of failure approach uses an understanding of physical failure mechanisms involved, such as mechanical crack propagation or chemical corrosion degradation or failure;
106 The parts stress modelling approach is an empirical method for prediction based on counting the number and type of components of the system, and the stress they undergo during operation.
118 Reliability engineering must also address requirements for various reliability tasks and documentation during system development, test, production, and operation. These requirements are generally specified in the contract statement of work and depend on how much leeway the customer wishes to provide to the contractor. Reliability tasks include various analyses, planning, and failure reporting. Task selection depends on the criticality of the system as well as cost. A critical system may require a formal failure reporting and review process throughout development, whereas a non-critical system may rely on final test reports. The most common reliability program tasks are documented in reliability program standards, such as MIL-STD-785 and IEEE 1332. Failure reporting analysis and corrective action systems are a common approach for product
187 One of the most common methods to apply a reliability operational assessment are Failure Reporting, Analysis and Corrective Action Systems (FRACAS). This systematic approach develops a reliability, safety and logistics assessment based on Failure
combination
76 Reliability prediction is the combination of the creation of a proper reliability model together with estimating (and justifying) the input parameters for this model (like failure rates for a particular failure mode or event and the mean time to repair the system for a particular failure) and finally to provide a system (or part) level estimate for the output reliability parameters (system availability or a particular functional failure frequency).
116 The combination of reliability parameter value and confidence level greatly affects the development cost and the risk to both the customer and producer. Care is needed to select the best combination of requirements - e.g. cost-effectiveness. Reliability testing may be performed at various levels, such as component, subsystem, and system. Also, many factors must be addressed during testing and operation, such as extreme temperature and humidity, shock, vibration, or other environmental factors (like loss of signal, cooling or power; or other catastrophes such as fire, floods, excessive heat, physical or security violations or other myriad forms of damage or degradation). Reliability engineering must assess the root cause of failures and devise corrective actions. Reliability engineering determines an effective test strategy so that all parts are exercised in relevant environments in order to assure the best possible reliability under understood conditions. For systems that must last many years, reliability engineering may be used to design accelerated life tests.
179 Software reliability is a special aspect of reliability engineering. System reliability, by definition, includes all parts of the system, including hardware, software, supporting infrastructure (including critical external interfaces), operators and procedures. Traditionally, reliability engineering focuses on critical hardware parts of the system. Since the widespread use of digital integrated circuit technology, software has become an increasingly critical part of most electronics and, hence, nearly all present day systems. There are significant differences, however, in how software and hardware behave. Most hardware unreliability is the result of a component or material failure that results in the system not performing its intended function. Repairing or replacing the hardware component restores the system to its original operating state. However, software does not fail in the same sense that hardware fails. Instead, software unreliability is the result of unanticipated results of software operations. Even relatively small software programs can have astronomically large combinations of inputs and states that are infeasible to exhaustively test. Restoring software to its original state only works until the same combination of inputs and states results in the same unintended result. Software reliability engineering must take this into account.
182 A common reliability metric is the number of software faults, usually expressed as faults per thousand lines of code. This metric, along with software execution time, is key to most software reliability models and estimates. The theory is that the software reliability increases as the number of faults (or fault density) goes down. Establishing a direct connection between fault density and mean-time-between-failure is difficult, however, because of the way software faults are distributed in the code, their severity, and the probability of the combination of inputs necessary to encounter the fault. Nevertheless, fault density serves as a useful indicator for the reliability engineer. Other software metrics, such as complexity, are also used. This metric remains controversial, since changes in software development and verification practices can have dramatic impact on overall defect rates.
components