Reliability Knowledge

After successful DV testing, the product moves into the PV phase. PV testing is conducted on units that are manufactured using the final production process, materials, and equipment. The purpose of PV is to validate that the production process can consistently produce units that meet the design specifications.

The sample size for PV is typically smaller than for DV, as indicated by the user input of around 10 samples. This is because the focus of PV is on the consistency and capability of the production process rather than the design itself.

These tests are crucial for products that incorporate complex mechanical, electrical, and chemical components, as they must perform reliably under a wide range of operating conditions and comply with stringent safety and environmental regulations.

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Yes, reliability testing can be done in parallel with design validation (DV). This approach has both advantages and disadvantages, which are important to consider in the context of product development and testing. Pros of conducting reliability testing in parallel with design validation include time efficiency. Conducting reliability testing in parallel with (DV) can significantly reduce the overall time required for product development. By overlapping these processes, you can identify and address potential issues earlier, which can accelerate the time to market. Early detection of issues running reliability tests alongside (DV) allows for the early detection of design flaws or weaknesses. This can lead to quicker iterations and improvements, enhancing the overall quality and robustness.

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The allocation of samples for different tests during the design validation stage in the automotive industry can vary depending on the specific requirements of the product and the risks associated with its failure. However, based on the general practice of using a total of 30 samples for design validation, we can provide a hypothetical allocation for the different tests. It’s important to note that these numbers are illustrative and should be adjusted based on the actual testing needs, regulatory requirements, and industry standards.

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In the world of engineering reliability, there is a crucial aspect that spans various domains, the two fields that often get confused due to their similar names. While site reliability engineering (SRE) and hardware reliability engineering are both aimed at ensuring the dependability of systems, they focus on vastly different areas and employ distinct methodologies.

Let’s explore the key differences between these two disciplines and delve into the history behind the SR naming convention.

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During the first prototype stage of product development, there is no one-size-fits-all answer for the right sample size. The appropriate sample size depends on various factors, including the objectives of your research, the nature of the prototype, the variability of the measurements, and the constraints of your project such as budget and timeline.

At the prototype stages of product development, especially for electromechanical devices, understanding the safety factor in your design is crucial. The safety factor, often referred to as the Factor of Safety (FoS), is a measure of the load-carrying capacity of a system beyond the expected or actual loads. Essentially, it indicates how much stronger the system is than it usually needs to be under normal conditions. A common approach to validate the safety factor in design, particularly for new and untested devices, is through step-stress accelerated life testing (SSALT). This method involves subjecting the prototype to increasing stress levels until failure occurs, providing insights into the product’s durability and reliability under various conditions. [Read more…]

In the realm of mechanical engineering the reliability and longevity of pumps are critical for numerous industrial applications. Predicting wear out of pumps can significantly enhance maintenance strategies, reduce downtime, and optimize operational efficiency. One effective approach to predicting wear out is by monitoring the revolutions per minute RPM of pumps over a large population in extended time periods.

This video delves into the methodology of creating a wear out prediction model.

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The Weibull distribution’s popularity across various industries stems from its remarkable flexibility and adaptability in modeling a wide range of data types, especially in reliability engineering and failure time analysis. This versatility is primarily due to the Weibull distribution’s shape parameter, which allows it to model different failure rates over time, aligning closely with the real-world behavior of many systems and components.

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Continuous Improvement in product development is a systematic and ongoing approach to enhancing products processes and services. This concept is crucial for organizations to stay competitive, meet evolving customer needs, and maintain product quality.

Let’s explore the key concepts of continuous Improvement in product development. Continuous Improvement is an iterative process tha 2involves constantly evaluating and refining products and processes. It’s not a one-time effort but a cyclical approach that allows for ongoing enhancements based on feedback.

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Quality: A Snapshot at Time Zero

Quality is a measure of how well a product meets specified requirements and standards at the beginning of its life. It’s a static measure that can be controlled and measured with accuracy. Quality engineers focus on designing and implementing quality control processes, conducting inspections and testing, and identifying and addressing defects or issues.

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Given the reliability goal for a system, we often need to understand the reliaility goals for elements within the system. It is a balance between safety, cost, and performance. This short video discussed how to approach allocating reliability goals within a complex system.

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Software reliability and hardware reliability are two distinct concepts within the field of engineering, each with its own unique characteristics and measurement challenges.

Software reliability is defined as the probability that software will operate without failure for a specified period of time in a specified environment. It is a reflection of the design perfection rather than manufacturing perfection, which is more associated with hardware reliability. The complexity of software is a major contributing factor to software reliability issues. Unlike hardware, software does not degrade over time or wear out, but it may have faults due to design defects that can cause failures.

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Once a problem is clearly identified, the team must gather information concerning the problem, and identify potential solutons. After evaluating the potential solutions, the team can select the solution that will solve the problem effectively. It is then time to plan the details on the design change implementation.

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Accelerated Life Testing (ALT) is a method used in reliability engineering to assess the lifespan and performance of a product under accelerated stress conditions. The goal is to uncover potential faults and failures in a shorter time frame than would be possible under normal operating conditions. ALT is particularly useful when the product’s expected lifespan is long, and waiting for failures to occur naturally is not feasible.

In the context of Design Verification (DV), ALT can help shorten the testing time by inducing failures more quickly than under normal conditions. This allows engineers to identify and address potential issues earlier in the product development process, thereby improving the product’s reliability and reducing the time to market. [Read more…]

The importance of failure repeatability lies in its role in understanding and improving systems, processes, and products. Failure repeatability refers to the consistency with which a system or device can reproduce an outcome under unchanged conditions. In the context of product design engineering and testing, being able to consistently replicate a failure means that the underlying cause can be more accurately identified and addressed.

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Degradation testing for electromechanical components such as pumps, valves, and sensors involves a series of steps to identify wear and tear that could lead to system failure. The goal is to detect these signs of degradation early enough to replace the part and prevent system failure.

For pumps, degradation can be monitored by sensors. A study on gear pumps used an accelerated life test (ALT) to monitor the degradation state. The volumetric efficiency of the pumps was measured over time, and the wear clearances were recorded. As the wear gap increased, the flow rate gradually decreased, indicating wear degradation.

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