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Approximately 500 million oil filters are sold in the United States of America each year, and are not required by law to meet any Government or industry testing procedures prior to being sold in the US market. The lack of required testing has resulted in no uniform testing procedure which in many cases leads to misleading claims by the manufacturer and/or inferior filtration designs and construction materials. Due to the lack of mandatory testing, the majority of oil filter manufacturers use in-house labs with different filtering methods to highlight the filter's unique strengths while not disclosing all relevant filtering data and in turn the filters inherent weaknesses. Instead of manufacturers offering full disclosure of the relevant performance specifications and internal design characteristics of the oil filter, they state that the specifications are proprietary information.

A current trend by automotive manufacturers involves the use of Oil Life Monitoring Systems (OLMS) to determine the drain interval of the engine oil. The premise of the OLMS system is to extend the oil drain interval by monitoring engine parameters and reduce the number of oil changes during the vehicle's lifecycle. The OLMS uses an engine oil sensor or various engine sensors and an advanced algorithm to predict when the engine oil has reached the end of its lifecycle. The OLMS effectively supports customer demands for lower operating costs and government fleet requirements to reduce the consumption of petroleum derived products and hazardous waste. This research analyzed the correlation between various external influences that alter the output of the OLMS. The external influences include monitoring of the vehicle operating conditions in densely populated metropolitan statistical areas versus more rural areas.