Oil analysis (OA) is the sampling and laboratory analysis of a lubricant's properties, suspended contaminants, and anti-wear additives. OA is performed during routine preventive maintenance to provide meaningful and accurate information on lubricant and machine condition. By monitoring oil analysis sample results over the life of a particular machine, trends can be established which can help eliminate costly repairs. The study of wear in an engine is called tribology. Tribologists often perform or interpret oil analysis.

OA can be divided into four categories:

1. analysis of oil properties,
2. analysis of contaminants,
3. analysis of wear elements from machinery, and
4. analysis of the additive package used in most motor oils

Predictive maintenance ( PdM) techniques help determine the condition of in-service equipment in order to predict when maintenance should be performed. This approach offers cost savings over routine or time-based preventive maintenancebecause tasks are performed only when warranted.

Preventive maintenance (PM) has the following meanings:

1. The care and servicing by personnel for the purpose of maintaining equipment and facilities in satisfactory operating condition by providing for systematic inspection, detection , and correction of incipient failures either before they occur or before they develop into major defects.
2. Maintenance , including tests, measurements, adjustments, and parts replacement, performed specifically to prevent faults from occurring.

Source: from Federal Standard 1037C and from MIL-STD-188 and from the Department of Defense Dictionary of Military and Associated Terms

Reliability-Centered Maintenance, often known as RCM, is an industrial improvement approach focused on identifying and establishing the operational, maintenance, and capital improvement policies that will manage the risks of equipment failure most effectively. It is defined by the technical standard SAE JA1011, Evaluation Criteria for RCM Processes.

Reliability centered maintenance is an engineering frameworkthat enables the definition of a complete maintenanceregime. It regards maintenance as the means to maintain the functions a user may require of machinery in a defined operating context. As a discipline it enables machinery stakeholders to monitor, assess, predict and generally understand the working of their physical assets.

Reliability engineering is an engineering field, that deals with the study reliability: the ability of a system or component to perform its required functions under stated conditions for a specified period of time. It is often reported in terms of a probability.

In probability theory and statistics , the Weibull distribution ^[1] (named after Waloddi Weibull ) is a continuous probability distribution with the probability density function

for and f( x; k, λ) = 0 for x < 0, where k > 0 is the shape parameter and λ > 0 is the scale parameter of the distribution. Its complementary cumulative distribution function is a stretched exponential .

The Weibull distribution is often used in the field of life data analysis due to its flexibility—it can mimic the behavior of other statistical distributions such as the normal and the exponential. If the failure rate decreases over time, then k < 1. If the failure rate is constant over time, then k = 1. If the failure rate increases over time, then k > 1.

An understanding of the failure rate may provide insight as to what is causing the failures:

• A decreasing failure rate would suggest "infant mortality". That is, defective items fail early and the failure rate decreases over time as they fall out of the population.

• A constant failure rate suggests that items are failing from random events.

• An increasing failure rate suggests "wear out" - parts are more likely to fail as time goes on.

When k = 3.4, then the Weibull distribution appears similar to the normal distribution . When k = 1, then the Weibull distribution reduces to the exponential distribution .