Machinery Lubrication magazine published by Noria Corporation
Issue link: https://www.e-digitaleditions.com/i/359954
22 July - August 2014 | www.machinerylubrication.com oIl ANAlYsIs By SteFFen BotS, oelcheck T The evaluation of oil or grease analysis results is often a tough job for a diagnostician, demanding experience in mechanical engineering and chemistry. However, modern tools and statis- tical methodologies can support and improve the process. The first step is to define a proper set of test methods that delivers sufficient parameters for answering important questions about the sample while still being as economical as possible. After determining the test parameters, the next challenge is to set up limit values and guidelines for the evaluation. In some cases, general limit values are available. However, in many cases, oil, component or equipment manufacturers cannot or will not supply complete limit sets. So how can a meaningful diagnosis be created? One way is with the help of an experienced engineer who knows the application and when critical values are exceeded. It is also easier if previous samples exist. Developing parameters over a period of time can identify layers or single parameters that move away from the regular trend line. Absolute limit values must also be applied in order to have a fixed reference point for the critical region. An adequate set of oil analysis results from the same or comparable equipment/application is the baseline for statistical methods. ASTM D-7720 describes an approach for identifying alarm limits by statistical methods, but a large set of data and statistical guidelines do not automatically provide proper limit values. The quality of the data set can have a significant impact on the statistical results. It may make the difference between having reasonable statistically based limits or nonsense. This article will show how carefully filtered data sets within a sophisticated structure can deliver valuable limit values. The system, which is based on an application matrix, enables oil samples to be categorized with as much detail as the sample information allows. Combined with an advanced evaluation program, this is the basis for defining limit values, applying them with evaluation guidelines and proving them on a regular basis. Analyzing an Oil Sample The analysis of a used oil sample produces a lot of data. A typical lab report contains in the range of 20 to 40 single measurement results. In order to provide a proper diagnosis or trigger the necessary actions based on the analysis, typical or normal ranges for each element must be known. The oil type, construction, maintenance and operating conditions are the four main influencing factors for evaluating an oil sample. A single rating for each oil analysis parameter does not cover the complexity and interdisciplinary knowledge in the fields of mechanical engineering, chemistry, tribology and lubrication that must be applied. If an evaluation is based on one element that has exceeded a limit, incorrect interpretations are possible. Some labs offer a comment for every oil sample, pointing out critical areas of the analysis along with recommendations for the next mainte- nance action. However, lab reports generally do not contain limit information in order to avoid misinterpretation by the end user. Limit Values Most oil analysis reports from commercial laboratories contain a rating based on the traffic-light principle. This utilizes a three-stage color code (green, yellow and red) to quickly indi- cate the severity of a sample result. If a large number of samples must be handled, it may make sense to filter the yellow- and red-flagged samples in order to decide what kind of maintenance action is necessary. Green-flagged samples can be stored for trending and documentation. The coding system should not be too complicated. Other- wise, it loses its advantage of providing quick and simple decision guidance. At the same time, it must be reasonable and consistent for comparable oil analysis patterns. Proper limit parameter sets that can be both absolute or trend-based are the basis of this consistency. Standardized processes for the creation and revision of limit values combined with well-founded guidelines for the recogni- tion of failure modes and the identification of normal conditions are fundamental for a high-quality oil analysis program. The opposite of such a methodology is an empirical approach based on the knowledge of an experienced diagnostician. This expert knowledge is very valuable and should be used to prove whether limits are reasonable. However, empirical knowledge is not the right methodology for managing a standardized oil analysis program with a proactive maintenance approach. A Practical Approach for Evaluating Oil Analysis Results with limit Values