Publisher’s Note

A good oil analysis program is an integral part of successful lubricant reliability program. With consistent and accurate monitoring of oil, the oil analysis program can help improving bottom line with many benefits like fewer disposals of used lubricants, less labour and less downtime. Developing an effective oil analysis program requires careful planning.

When plant personnel decide to invest in oil analysis, they choose a lab and start sending samples without thinking about what they are trying to achieve. Instead, the program should be developed with a careful plan in place based on a stated series of reliability goals. The overall structure and foundation of an oil analysis program should be based on sound reliability engineering goals. These goals should guide the end user through the process of designing and implementing the program. Of all the factors involved in developing an effective program, sampling strategy has perhaps the single largest impact on success or failure.

With oil analysis, the proverb “garbage in, garbage out” definitely applies. While most oil analysis labs can provide advice on where and how to sample different components, the ultimate responsibility for sampling strategy must rest on the end user’s shoulders. Assuming the sampling strategy is correct and the program has been designed based on sound reliability engineering goals; it is up to the lab to ensure the sample provides the necessary information.

The first stage is to make sure the sample and subsequent data is logged in the correct location so that trend analysis and rate-of-change limits can be applied. Diagnostic and prognostic interpretation of the data is perhaps the step where the most antagonistic relationship can develop between the lab and its customers.

Evaluating data and making meaningful condition-based monitoring (CBM) decisions is a symbiotic process. The end user needs the lab diagnosticians’ expertise to make sense of the data, while the lab needs the in-plant expertise of the end user who is intimately familiar with each component, its functionality, and what maintenance or process changes may have occurred recently that could impact the oil analysis data. Oil analysis is most effective when it is used to track metrics or benchmarks set forth in the planning stage.

A laboratory likely will not excel in every aspect of oil analysis as one might hope. In order to be competitive, the lab may concentrate its efforts on those areas which are most valued in the market. The problem is many people are often too focused on price and may unknowingly fall short of their end goal by overlooking some of the most important oil analysis principles.

Choosing a lab that is located close enough to where samples can be delivered within 24 hours is a must. Most oil analysis test methods are not straightforward but will necessitate having regulations to carefully follow. The regulations may come from standards provided by ASTM, ISO or other comparable standardization organizations. To achieve the end goal of oil analysis, there must be a comprehensive interpretation of the data. The interpretation stage can be challenging to summarize. After the interpretation has been performed, one should expect from the lab to communicate the results in a quality and user-friendly report. The necessary levels of service and quality should not be sacrificed for price. The attainment of the end goal depends on it.

We would like to thank our readers for the great response to our previous edition’s cover story – “Base OilBuilding block for Lubricants” and other articles. Our current issue’s cover story is “Supercharging Oil Analysis with AI” which will help our readers to understand the rise of artificial intelligence and machine learning. We welcome your feedback & suggestions.

Warm regards,

Udey Dhir