Reliability & Maintainability

Reliability is often thought of as a Figure of Merit (FOM) or a Technical Performance Measure (TPM) defined as, “The probability that an item will perform its intended function for a specified mission profile.” In reality, reliability is an engineering discipline that provides a critical design function which involves the application of engineering principles to the design and processing of products, both hardware and software, for the purpose of meeting product reliability requirements or goals.

Reliability as an engineering discipline is the application of engineering principles to the design and processing of products, both hardware and software, for the purpose of meeting product reliability requirements or goals. Reliability as a figure of merit is the probability that a part or an item will perform its intended function for a specified mission profile (i.e., specified mission duration and under specified condition). The Reliability Function is defined as the probability that the system will operate successfully for a specified amount of time.

• Operational Reliability Prediction is the process of quantitatively estimating the mission reliability for a system, subsystem, or component using both objective and subjective data.
• Design Reliability Prediction is the process of predicting the reliability of a given design based on failure physics using statistical techniques and probabilistic engineering models.
• Process Reliability is the process of mapping the design drivers in the manufacturing process to identify the process parameters critical to generate the material properties that meet the specs. A high process reliability is achieved by maintaining a uniform, capable, and controlled processes.
• Reliability Demonstration is the process of quantitatively demonstrating certain reliability level (i.e., comfort level) using objective data at the level intended for demonstration.

Reliability Metrics

There are many ways to measure and evaluate reliability. The following are the most commonly used across government and industry:

• Mean Time Between Failures (MTBF)
  • A basic measure of reliability for repairable items.
  • Is the expected value of time between two consecutive failures, for repairable systems.
• Mean Time to Failure (MTTF)
  • A basic measure of reliability for non-repairable systems. It is the mean time expected until the first failure.
• Predicted reliability numbers
  • Reliability prediction is the process of quantitatively estimating the reliability using both objective and subjective data.
• Demonstrated reliability numbers
  • Unlike reliability prediction, reliability demonstration is the process of quantitatively estimating the reliability of a system using objective data at the level intended for demonstration. In general, demonstrated reliability requirement is set at a lower level than predicted reliability. It is intended to demonstrate a comfort level with a lower reliability than the predicted reliability because of the cost involved
• Safety factors
  • A term describing the capability of a system beyond the expected loads or actual loads.
• Fault tolerances
  • Fault tolerance is the property that enables a system to continue operating properly in the event of the failure of some of its components.

“How Reliable is Reliable Enough?”

In reliability engineering, no one likes things to fail. We don’t like bridges to collapse and we don’t like nuclear plants to leak radioactive material. Engineers still have to address the question “How reliable is reliable enough?” Is it one in a thousand? One in ten thousands? One in a million? The answer is: It depends. For example, “reliable enough” for a critical situation might mean a high safety factor (e.g., 2.0 or better), or high reliability (e.g., 0.999999 or better). For degraded performance, a lower safety factor or lower reliability might be acceptable. For these reasons, engineers must design things to certain reliability specifications depending on the safety and economics of the situation, technology availability, and design constraints.

Reliability Training at the APT SEAC

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APT Point of Contact

Melissa Emery, 256.327.3373
aptinfo@apt-research.com