Introduction to the field of reliability engineering¶
Reliability engineering is a field of study that deals with the estimation, prevention, and management of failures by combining statistics, risk analysis, and physics. By understanding how failures may occur or have occurred, we are able to better predict the lifespan of a product or system, allowing us to manage its lifecycle and the risks associated with its failure. All engineering systems, components, and structures will eventually fail, and knowing how and when that failure will occur is of great interest to the owners and operators of those systems. Due to the similarities between the lifecycle of engineering systems and the lifecycle of humans, the field of study known as survival analysis has many concepts that are used in reliability engineering.
Everyone is acutely aware of the importance of reliability, particularly when something doesn’t work at a time we expect it to. Whether it be your car not starting, your television failing, or the chance of being delayed on the runway because your aircraft’s airconditioning unit just stopped working, we know that system failure is something we all want to avoid. When it can’t be avoided, we at least want to know when it is likely to occur so we can conduct preventative maintenance before the need for corrective maintenance arises. Reliability engineering is most frequently used for systems which are of critical safety importance (such as in the nuclear industry), or in systems which are numerous (such as vehicles or electronics) where the cost of fleetwide reliability problems can quickly become very expensive.
Much of reliability engineering involves the analysis of data (such as time to failure data), to uncover the patterns in how failures occur. Once we understand how things are failing, we can use those patterns to forecast how the failures will occur throughout the lifetime of a population of items, or the lifetime of one or more repairable items. It is the data analysis part of reliability engineering that this Python library is designed to help with.
Further reading is available on Wikipedia and in many other reliability resources.