![]() Numerous prediction methods have been developed to determine reliability. That will help you choose wisely, and to select the appropriate product for your application. Always ask for an MTBF value, always find out how current that information is and always find out what standards it is based upon. But, it is still a very useful tool when evaluating a product purchase. The true value of MTBF calculations is often debated, sometimes called irrelevant and often misunderstood. However, MTBF remains the basic measure of a system’s reliability for most products. Reliability methods such as MTTR, MTTF and FIT apply to products or to specific components. The product is far more likely to be as flawless and as functional as advertised. That means that a product will be rigorously tested in numerous ways, including submissions to outside labs for the appropriate certifications. ISO certified companies have committed themselves to meet the goals of “continual improvement” and “zero defects”. ISO-9001 Certification is an indication that the manufacturer has calculated the MTBF accurately. New, RoHS-compliant components may have a different life cycle than the parts that they replace. If a released product is re-developed in order to meet RoHS compliance, the entire calculation has to be performed again. For example, RoHS “(Restriction of Hazardous Substances”) was mandated by the European Community in 2006. Since this process takes time, calculating the MTBF and other predictions of reliability is an ongoing process. Combining all of this data should produce a more accurate prediction of a product’s service life. In addition to the MTBF calculation, quality assurance managers should track all reported field failures as well as the root causes. A person certified and educated in calculating MTBF must review the MTBF for every component, as well as other factors like operating temperature range and storage temperature range. A product with an extremely high MTBF may not necessarily have an equally impressive service life, depending upon how it is being treated. This calculation assumes that the product was properly packaged when delivered, that it was installed correctly, and that the customer is not doing anything to damage the product after it has been deployed. The MTBF is often calculated based on an algorithm that factors in all of a product’s components to reach the sum life cycle in hours. The CL will be based on the number of failures that occurred. For example, component manufacturers will take a small sampling of a component, test for x number of hours, and then determine if there were any failures in the test bed. In statistics, a claim to 95% confidence simply means that the researcher has seen something occur that only happens one time in twenty, or less. In common usage, a claim to 95% confidence in something is normally taken as indicating virtual certainty. FIT and Confidence Limits (CL) are often provided together. Examples include: 1000 devices for 1 million hours, 1 million devices for 1000 hours each, and other similar combinations. FIT can be quantified in a number of ways. This term is very important in the semiconductor industry, but is also used by component manufacturers. FIT reports the number of expected failures per one billion hours of operation for a device. However, MTBF is commonly used for both repairable and non-repairable items.įailure In Time (FIT) is another way of reporting MTBF. MTBF should be used in reference to repairable items, while MTTF should be used for non-repairable items. MTTF is a statistical value and is calculated as the mean over a long period of time and a large number of units. It is the mean time expected until the piece of equipment fails and needs to be replaced. Mean Time To Failure (MTTF) is a measure of reliability for nonrepairable systems. The time required to acquire the new part is also a factor. The actual installation time is only part of the story. Mean Time To Repair (MTTR) is the mean time needed to repair a failed hardware module. If this data is not provided, a manufacturer’s piece of equipment should be immediately disqualified. MTBF data should be a required line item in a request-for-quote (RFQ). MTBF data is not always readily available but, it is worth asking for the information. They may not realize that a product with a short lifespan really is not much of a bargain. Industries and integrators tend to pay close attention to MTBF, but consumers are often price driven. This is the most common parameter used to predict a product’s life span. Mean Time Between Failure (MTBF) is the number of failures per million hours for a product. Understanding the methods used to predict a product life cycle will help you make informed decisions. You should also consider the product’s life expectancy. Product purchasing decisions should not be based on feature sets alone.
0 Comments
Leave a Reply. |