D02.96.04 - Guidelines for In-Services Lubricants Analysis

SIGNIFICANCE AND USE
5.1 This guide is intended as a guideline for fluid analysis programs and serves as an initial justification for selecting fluid tests and sampling frequencies. Plant operating experience along with the review and benchmarking of similar applications is required to ensure that lessons learned are implemented.  
5.2 Selection of proper fluid tests for assessing in-service component condition may have both safety and economic implications. Some failure modes may cause component disintegration, increasing the safety hazard. Thus, any fluid test that can predict such conditions should be included in the condition-monitoring program. Conversely, to maintain a sustainable and successful fluid-monitoring program, the scope of the fluid tests and their frequency should be carefully balanced between the associated risks versus expected program cost savings and benefits.  
5.3 The failure modes monitored may be similar from one application to the next, but the risk and consequences of failure may differ.  
5.4 This analysis can be used to determine which in-service lubricant analysis tests would be of highest value and which would be ineffective for the failure modes of interest. This information can also be used to determine the best monitoring strategy for a suite of failure modes and how often assessment is needed to manage the risk of failure.
SCOPE
1.1 This guide describes a methodology to select tests to be used for in-service lubricant analysis. The selection of fluid tests for monitoring failure mode progression in industrial applications applies the principles of failure mode and effect analysis (FMEA).  
1.2 Although typical FMEA addresses all possible product failure modes, the focus of this guide is not intended to address failures that have a very high probability of unsafe operation as these should immediately be addressed by other means.  
1.3 This guide is limited to components selected for condition-monitoring programs by providing a methodology to choose fluid tests associated with specific failure modes for the purpose of identifying their earliest developing stage and monitoring fault progression. The scope of this guide is also focused on those failure modes and their consequences that can effectively be detected and monitored by fluid analysis techniques.  
1.4 This guide pertains to a process to be used to ensure an appropriate amount of condition monitoring is performed with the objective of improving equipment reliability, reducing maintenance costs, and enhancing fluid analysis monitoring of industrial machinery. This guide can also be used to select the monitoring frequencies needed to make the failure determinations and provide an assessment of the strengths and weaknesses of a current condition-monitoring program.  
1.5 This guide does not eliminate the programmatic requirements for appropriate assembly, operational, and maintenance practices.  
1.6 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use.  
1.7 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.

SIGNIFICANCE AND USE
5.1 This guide is intended as a guideline for justification of oil test selection for monitoring rolling element ball type bearing conditions in industrial applications. Continuous benchmarking against similar applications is required to ensure lessons learned are continuously implemented.  
5.2 Selection of oil tests for the purpose of detecting rolling element ball type bearing failure modes requires good understanding of equipment design, operating requirements and surrounding conditions. Specifically, detailed knowledge is required on bearing design configuration, dimensional tolerances, load directions, design limitations, lubrication mechanisms, lubricant characteristics, and metallurgy of lubricated surfaces including bearing cages. Equipment criticality and accessibility as well as application of other monitoring techniques (for example, vibration, ultrasound or thermal images) are also critical information in this analysis process. In addition, detailed knowledge on the lubricating oil is paramount.  
5.3 To properly apply the FMEA methodology users must understand the changes the system may encounter during all operating modes, their impact on design functions and available monitoring techniques capable of detecting these changes. To assist this approach, Section 6 will provide extensive descriptions on the rolling element ball type bearing failure modes, their causes and effects.  
5.4 It is recognized that in most industrial applications vibration monitoring is the primary condition monitoring technique applied to detect failure modes, causes and effects in rolling element ball type bearings—while oil analysis is primarily used to monitor the lubricating oil properties. In the recent years, however, there is a trend toward using oil analysis in order to provide earlier detection of some failures of rolling element ball type bearings. This is particularly applicable to complex dynamic systems such as compressors, gearboxes and some gas turbines where o...
SCOPE
1.1 This guide approaches oil analysis from a failure standpoint and includes both the rolling element ball type bearing wear and fluid deterioration in industrial application.  
1.2 This guide pertains to improving equipment reliability, reducing maintenance costs and enhancing the condition-based maintenance program primarily for industrial machinery by applying analytical methodology to oil analysis program for the purpose of detecting specific failure modes.  
1.3 This guide reinforces requirements for appropriate assembly, operation within the original design envelope as well as the need for condition-based and time-based maintenance.  
1.4 This guide covers the principles of Failure Mode and Effect Analysis (FMEA) as described in Guide D7874 and its relationship to rolling element ball type bearing wear in industrial application and its fluid deterioration.  
1.5 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use.  
1.6 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.

SIGNIFICANCE AND USE
5.1 Alarm limits are used extensively for condition monitoring using data from in-service lubricant sample test results. There are many bases for initially choosing values for these alarm limits. There are many questions that should be addressed. These include:  
Are those limits right or wrong?
Are there too many false positive or false negative results?
Are they practical?  
5.2 This guide teaches statistical techniques for evaluating whether alarm limits are meaningful and if they are reasonable for flagging problems requiring immediate or future action.  
5.3 This guide is intended to increase the consistency, usefulness, and dependability of condition based action recommendations by providing machinery maintenance and monitoring personnel with a meaningful and practical way to evaluate alarm limits to aid the interpretation of monitoring machinery and oil condition as well as lubricant system contamination data.
SCOPE
1.1 This guide provides specific requirements to statistically evaluate measurand alarm thresholds, which are called alarm limits, as they are applied to data collected from in-service oil analysis. These alarm limits are typically used for condition monitoring to produce severity indications relating to states of machinery wear, oil quality, and system contamination. Alarm limits distinguish or separate various levels of alarm. Four levels are common and will be used in this guide, though three levels or five levels can also be used.  
1.2 A basic statistical process control technique described herein is recommended to evaluate alarm limits when measurand data sets may be characterized as both parametric and in control. A frequency distribution for this kind of parametric data set fits a well-behaved two-tail normal distribution having a “bell” curve appearance. Statistical control limits are calculated using this technique. These control limits distinguish, at a chosen level of confidence, signal-to-noise ratio for an in-control data set from variation that has significant, assignable causes. The operator can use them to objectively create, evaluate, and adjust alarm limits.  
1.3 A statistical cumulative distribution technique described herein is also recommended to create, evaluate, and adjust alarm limits. This particular technique employs a percent cumulative distribution of sorted data set values. The technique is based on an actual data set distribution and therefore is not dependent on a presumed statistical profile. The technique may be used when the data set is either parametric or nonparametric, and it may be used if a frequency distribution appears skewed or has only a single tail. Also, this technique may be used when the data set includes special cause variation in addition to common cause variation, although the technique should be repeated when a special cause changes significantly or is eliminated. Outputs of this technique are specific measurand values corresponding to selected percentage levels in a cumulative distribution plot of the sorted data set. These percent-based measurand values are used to create, evaluate and adjust alarm limits.  
1.4 This guide may be applied to sample data from testing of in-service lubricating oil samples collected from machinery (for example, diesel, pumps, gas turbines, industrial turbines, hydraulics) whether from large fleets or individual industrial applications.  
1.5 This guide may also be applied to sample data from testing in-service oil samples collected from other equipment applications where monitoring for wear, oil condition, or system contamination are important. For example, it may be applied to data sets from oil filled transformer and circuit breaker applications.  
1.6 Alarm limit evaluating techniques, which are not statistically based are not covered by this guide. Also, the techniques of this standard may be inconsistent with the following alarm limit selection techniques: “rate-of-change,...

SIGNIFICANCE AND USE
5.1 This guide is intended to provide machinery maintenance and monitoring personnel with a guideline for performing trend analysis to aid in the interpretation of machinery condition data.
SCOPE
1.1 This guide covers practical techniques for condition data trend analysis.  
1.2 The techniques may be utilized for all instrumentation that provides numerical test results. This guide is written specifically for data obtained from lubricant samples. Other data obtained and associated with the machine may also be used in determining the machine condition.  
1.3 This guide provides a methodology for assessing changes in lubricant during service. For limits on a specific lubricant parameter used in different system types, users should refer to Practice D4378, Practice D6224, or other established industry criteria, such as from the OEM. Guide D7720 may be used to determine limits if unavailable through the other references given.  
1.4 This guide does not address upper or lower control limits. These limits are provided by product manufacturers, defined in ASTM specifications, or both. The range between upper and lower control limits should be greater than the range within each test method’s repeatability coefficient. See Practices D3244, D6299, and D6792 for more information about ensuring that process control limits do not violate statistical fundamentals.  
1.5 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use.  
1.6 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.

SIGNIFICANCE AND USE
5.1 This standard is intended as a guideline for the justification of oil test selection for monitoring plain bearing conditions. One should employ a continuous benchmarking against similar applications to ensure lessons learned are continuously being implemented.  
5.2 Selection of oil tests for the purpose of detecting plain bearing failure modes requires good understanding of equipment design, operating requirements, and surrounding conditions. Specifically, detailed knowledge is required of bearing design configuration, dimensional tolerances, load directions, design limitations, lubrication mechanisms, lubricant characteristics, and metallurgy of lubricated surfaces. Equipment criticality and accessibility as well as application of other monitoring techniques (for example, vibration, ultrasound, or thermal images) are also critical information in this analysis process. In addition, detailed knowledge of the lubricating oil is paramount.  
5.3 To properly apply the FMEA methodology, users must understand the changes encountered in the system during all operating modes, their impact on design functions, and available monitoring techniques capable of detecting these changes. To demonstrate this approach, Section 6 will provide extensive descriptions of the plain bearing failure modes, their causes, and effects.
SCOPE
1.1 This guide covers an oil test selection process for plain bearing applications by applying the principles of Failure Mode and Effect Analysis (FMEA) as described in Guide D7874.  
1.2 This guide approaches oil analysis from a failure standpoint and includes both the bearing wear and fluid deterioration.  
1.3 This guide pertains to improving equipment reliability, reducing maintenance costs, and enhancing the condition-based maintenance program primarily for industrial machinery by applying analytical methodology to an oil analysis program for the purpose of determining the detection capability of specific failure modes.  
1.4 This guide reinforces the requirements for appropriate assembly and operation within the original design envelope, as well as the need for condition-based and time-based maintenance.  
1.5 The values stated in SI units are to be regarded as standard. No other units of measurement are included in this standard.  
1.6 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use.  
1.7 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.

SIGNIFICANCE AND USE
4.1 This practice is typically used to obtain in-service lubricating grease samples from machinery.  
4.2 In this practice, a consistent and repeatable method is outlined for obtaining trendable samples from the following applications including motor-operated valves, gearboxes, pillow-block bearings, electric motors, exposed bearings, open gears, or failed grease-lubricated components. This allows for analysis and inspection of in-service lubricating grease that aids in predicting the life and condition of the grease-lubricated component. This information can be combined with other technologies such as infrared imaging, vibration analysis, and ultrasonic vibration analysis to predict when a machine may fail. The knowledge gained by the aforementioned analyses, in addition to the knowledge gained from the in-service lubricating grease analysis and inspection, may allow for more overall uptime by aiding in the prediction of grease-lubricated component failures as part of a predictive maintenance schedule. The prediction of a failing grease-lubricated component will also improve the level of safety of all who work around the component.
SCOPE
1.1 This practice covers the method to obtain a trendable in-service lubricating grease sample from the following configurations including motor-operated valves, gearboxes, pillow-block bearings, electric motors, exposed bearings, open gears, or failed grease-lubricated components.  
1.2 In some cases, it may be necessary to take more than one sample from a piece of equipment to obtain more trendable results. Examples of this could be a large bearing that does not fully rotate, such as a slew bearing, or one in which sufficient mixing does not otherwise occur.  
1.3 Samples taken in the above manner may need to be mixed to form a more homogeneous sample. This may also be true of other samples such as those taken from open face bearings.  
1.4 The values stated in SI units are to be regarded as the standard. The values given in parentheses are for information only. The exception to this is a standard English units thread for which there is no metric equivalent.
Note 1: The standard pipe thread referred to is the national pipe thread tapered thread.  
1.5 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use.  
1.6 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.

SIGNIFICANCE AND USE
5.1 This guide is intended as a guideline for fluid analysis programs and serves as an initial justification for selecting fluid tests and sampling frequencies. Plant operating experience along with the review and benchmarking of similar applications is required to ensure that lessons learned are implemented.  
5.2 Selection of proper fluid tests for assessing in-service component condition may have both safety and economic implications. Some failure modes may cause component disintegration, increasing the safety hazard. Thus, any fluid test that can predict such conditions should be included in the condition-monitoring program. Conversely, to maintain a sustainable and successful fluid-monitoring program, the scope of the fluid tests and their frequency should be carefully balanced between the associated risks versus expected program cost savings and benefits.  
5.3 The failure modes monitored may be similar from one application to the next, but the risk and consequences of failure may differ.  
5.4 This analysis can be used to determine which in-service lubricant analysis tests would be of highest value and which would be ineffective for the failure modes of interest. This information can also be used to determine the best monitoring strategy for a suite of failure modes and how often assessment is needed to manage the risk of failure.
SCOPE
1.1 This guide describes a methodology to select tests to be used for in-service lubricant analysis. The selection of fluid tests for monitoring failure mode progression in industrial applications applies the principles of failure mode and effect analysis (FMEA).  
1.2 Although typical FMEA addresses all possible product failure modes, the focus of this guide is not intended to address failures that have a very high probability of unsafe operation as these should immediately be addressed by other means.  
1.3 This guide is limited to components selected for condition-monitoring programs by providing a methodology to choose fluid tests associated with specific failure modes for the purpose of identifying their earliest developing stage and monitoring fault progression. The scope of this guide is also focused on those failure modes and their consequences that can effectively be detected and monitored by fluid analysis techniques.  
1.4 This guide pertains to a process to be used to ensure an appropriate amount of condition monitoring is performed with the objective of improving equipment reliability, reducing maintenance costs, and enhancing fluid analysis monitoring of industrial machinery. This guide can also be used to select the monitoring frequencies needed to make the failure determinations and provide an assessment of the strengths and weaknesses of a current condition-monitoring program.  
1.5 This guide does not eliminate the programmatic requirements for appropriate assembly, operational, and maintenance practices.  
1.6 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use.  
1.7 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.

SIGNIFICANCE AND USE
5.1 This guide is intended as a guideline for justification of oil test selection for monitoring rolling element ball type bearing conditions in industrial applications. Continuous benchmarking against similar applications is required to ensure lessons learned are continuously implemented.  
5.2 Selection of oil tests for the purpose of detecting rolling element ball type bearing failure modes requires good understanding of equipment design, operating requirements and surrounding conditions. Specifically, detailed knowledge is required on bearing design configuration, dimensional tolerances, load directions, design limitations, lubrication mechanisms, lubricant characteristics, and metallurgy of lubricated surfaces including bearing cages. Equipment criticality and accessibility as well as application of other monitoring techniques (for example, vibration, ultrasound or thermal images) are also critical information in this analysis process. In addition, detailed knowledge on the lubricating oil is paramount.  
5.3 To properly apply the FMEA methodology users must understand the changes the system may encounter during all operating modes, their impact on design functions and available monitoring techniques capable of detecting these changes. To assist this approach, Section 6 will provide extensive descriptions on the rolling element ball type bearing failure modes, their causes and effects.  
5.4 It is recognized that in most industrial applications vibration monitoring is the primary condition monitoring technique applied to detect failure modes, causes and effects in rolling element ball type bearings—while oil analysis is primarily used to monitor the lubricating oil properties. In the recent years, however, there is a trend toward using oil analysis in order to provide earlier detection of some failures of rolling element ball type bearings. This is particularly applicable to complex dynamic systems such as compressors, gearboxes and some gas turbines where o...
SCOPE
1.1 This guide approaches oil analysis from a failure standpoint and includes both the rolling element ball type bearing wear and fluid deterioration in industrial application.  
1.2 This guide pertains to improving equipment reliability, reducing maintenance costs and enhancing the condition-based maintenance program primarily for industrial machinery by applying analytical methodology to oil analysis program for the purpose of detecting specific failure modes.  
1.3 This guide reinforces requirements for appropriate assembly, operation within the original design envelope as well as the need for condition-based and time-based maintenance.  
1.4 This guide covers the principles of Failure Mode and Effect Analysis (FMEA) as described in Guide D7874 and its relationship to rolling element ball type bearing wear in industrial application and its fluid deterioration.  
1.5 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use.  
1.6 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.

SIGNIFICANCE AND USE
5.1 Alarm limits are used extensively for condition monitoring using data from in-service lubricant sample test results. There are many bases for initially choosing values for these alarm limits. There are many questions that should be addressed. These include:  
Are those limits right or wrong?
Are there too many false positive or false negative results?
Are they practical?  
5.2 This guide teaches statistical techniques for evaluating whether alarm limits are meaningful and if they are reasonable for flagging problems requiring immediate or future action.  
5.3 This guide is intended to increase the consistency, usefulness, and dependability of condition based action recommendations by providing machinery maintenance and monitoring personnel with a meaningful and practical way to evaluate alarm limits to aid the interpretation of monitoring machinery and oil condition as well as lubricant system contamination data.
SCOPE
1.1 This guide provides specific requirements to statistically evaluate measurand alarm thresholds, which are called alarm limits, as they are applied to data collected from in-service oil analysis. These alarm limits are typically used for condition monitoring to produce severity indications relating to states of machinery wear, oil quality, and system contamination. Alarm limits distinguish or separate various levels of alarm. Four levels are common and will be used in this guide, though three levels or five levels can also be used.  
1.2 A basic statistical process control technique described herein is recommended to evaluate alarm limits when measurand data sets may be characterized as both parametric and in control. A frequency distribution for this kind of parametric data set fits a well-behaved two-tail normal distribution having a “bell” curve appearance. Statistical control limits are calculated using this technique. These control limits distinguish, at a chosen level of confidence, signal-to-noise ratio for an in-control data set from variation that has significant, assignable causes. The operator can use them to objectively create, evaluate, and adjust alarm limits.  
1.3 A statistical cumulative distribution technique described herein is also recommended to create, evaluate, and adjust alarm limits. This particular technique employs a percent cumulative distribution of sorted data set values. The technique is based on an actual data set distribution and therefore is not dependent on a presumed statistical profile. The technique may be used when the data set is either parametric or nonparametric, and it may be used if a frequency distribution appears skewed or has only a single tail. Also, this technique may be used when the data set includes special cause variation in addition to common cause variation, although the technique should be repeated when a special cause changes significantly or is eliminated. Outputs of this technique are specific measurand values corresponding to selected percentage levels in a cumulative distribution plot of the sorted data set. These percent-based measurand values are used to create, evaluate and adjust alarm limits.  
1.4 This guide may be applied to sample data from testing of in-service lubricating oil samples collected from machinery (for example, diesel, pumps, gas turbines, industrial turbines, hydraulics) whether from large fleets or individual industrial applications.  
1.5 This guide may also be applied to sample data from testing in-service oil samples collected from other equipment applications where monitoring for wear, oil condition, or system contamination are important. For example, it may be applied to data sets from oil filled transformer and circuit breaker applications.  
1.6 Alarm limit evaluating techniques, which are not statistically based are not covered by this guide. Also, the techniques of this standard may be inconsistent with the following alarm limit selection techniques: “rate-of-change,...

SIGNIFICANCE AND USE
5.1 This guide is intended to provide machinery maintenance and monitoring personnel with a guideline for performing trend analysis to aid in the interpretation of machinery condition data.
SCOPE
1.1 This guide covers practical techniques for condition data trend analysis.  
1.2 The techniques may be utilized for all instrumentation that provides numerical test results. This guide is written specifically for data obtained from lubricant samples. Other data obtained and associated with the machine may also be used in determining the machine condition.  
1.3 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.

SIGNIFICANCE AND USE
5.1 This standard is intended as a guideline for the justification of oil test selection for monitoring plain bearing conditions. One should employ a continuous benchmarking against similar applications to ensure lessons learned are continuously being implemented.  
5.2 Selection of oil tests for the purpose of detecting plain bearing failure modes requires good understanding of equipment design, operating requirements, and surrounding conditions. Specifically, detailed knowledge is required of bearing design configuration, dimensional tolerances, load directions, design limitations, lubrication mechanisms, lubricant characteristics, and metallurgy of lubricated surfaces. Equipment criticality and accessibility as well as application of other monitoring techniques (for example, vibration, ultrasound, or thermal images) are also critical information in this analysis process. In addition, detailed knowledge of the lubricating oil is paramount.  
5.3 To properly apply the FMEA methodology, users must understand the changes encountered in the system during all operating modes, their impact on design functions, and available monitoring techniques capable of detecting these changes. To demonstrate this approach, Section 6 will provide extensive descriptions of the plain bearing failure modes, their causes, and effects.
SCOPE
1.1 This guide covers an oil test selection process for plain bearing applications by applying the principles of Failure Mode and Effect Analysis (FMEA) as described in Guide D7874.  
1.2 This guide approaches oil analysis from a failure standpoint and includes both the bearing wear and fluid deterioration.  
1.3 This guide pertains to improving equipment reliability, reducing maintenance costs, and enhancing the condition-based maintenance program primarily for industrial machinery by applying analytical methodology to an oil analysis program for the purpose of determining the detection capability of specific failure modes.  
1.4 This guide reinforces the requirements for appropriate assembly and operation within the original design envelope, as well as the need for condition-based and time-based maintenance.  
1.5 The values stated in SI units are to be regarded as standard. No other units of measurement are included in this standard.  
1.6 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.

SIGNIFICANCE AND USE
5.1 This guide is intended as a guideline for fluid analysis programs and serves as an initial justification for selecting fluid tests and sampling frequencies. Plant operating experience along with the review and benchmarking of similar applications is required to ensure that lessons learned are implemented.  
5.2 Selection of proper fluid tests for assessing in-service component condition may have both safety and economic implications. Some failure modes may cause component disintegration, increasing the safety hazard. Thus, any fluid test that can predict such conditions should be included in the condition-monitoring program. Conversely, to maintain a sustainable and successful fluid-monitoring program, the scope of the fluid tests and their frequency should be carefully balanced between the associated risks versus expected program cost savings and benefits.  
5.3 The failure modes monitored may be similar from one application to the next, but the risk and consequences of failure may differ.  
5.4 This analysis can be used to determine which in-service lubricant analysis tests would be of highest value and which would be ineffective for the failure modes of interest. This information can also be used to determine the best monitoring strategy for a suite of failure modes and how often assessment is needed to manage the risk of failure.
SCOPE
1.1 This guide describes a methodology to select tests to be used for in-service lubricant analysis. The selection of fluid tests for monitoring failure mode progression in industrial applications applies the principles of failure mode and effect analysis (FMEA).  
1.2 Although typical FMEA addresses all possible product failure modes, the focus of this guide is not intended to address failures that have a very high probability of unsafe operation as these should immediately be addressed by other means.  
1.3 This guide is limited to components selected for condition-monitoring programs by providing a methodology to choose fluid tests associated with specific failure modes for the purpose of identifying their earliest developing stage and monitoring fault progression. The scope of this guide is also focused on those failure modes and their consequences that can effectively be detected and monitored by fluid analysis techniques.  
1.4 This guide pertains to a process to be used to ensure an appropriate amount of condition monitoring is performed with the objective of improving equipment reliability, reducing maintenance costs, and enhancing fluid analysis monitoring of industrial machinery. This guide can also be used to select the monitoring frequencies needed to make the failure determinations and provide an assessment of the strengths and weaknesses of a current condition-monitoring program.  
1.5 This guide does not eliminate the programmatic requirements for appropriate assembly, operational, and maintenance practices.  
1.6 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.

SIGNIFICANCE AND USE
Alarm limits are used extensively for condition monitoring using data from in-service lubricant sample test results. There are many bases for initially choosing values for these alarm limits. There are many questions that should be addressed. These include:  
Are those limits right or wrong?
Are there too many false positive or false negative results?
Are they practical?
This guide teaches statistical techniques for evaluating whether alarm limits are meaningful and if they are reasonable for flagging problems requiring immediate or future action.
This guide is intended to increase the consistency, usefulness, and dependability of condition based action recommendations by providing machinery maintenance and monitoring personnel with a meaningful and practical way to evaluate alarm limits to aid the interpretation of monitoring machinery and oil condition as well as lubricant system contamination data.
SCOPE
1.1 This guide provides specific requirements to statistically evaluate measurand alarm thresholds, which are called alarm limits, as they are applied to data collected from in-service oil analysis. These alarm limits are typically used for condition monitoring to produce severity indications relating to states of machinery wear, oil quality, and system contamination. Alarm limits distinguish or separate various levels of alarm. Four levels are common and will be used in this guide, though three levels or five levels can also be used.
1.2 A basic statistical process control technique described herein is recommended to evaluate alarm limits when measurand data sets may be characterized as both parametric and in control. A frequency distribution for this kind of parametric data set fits a well-behaved two-tail normal distribution having a “bell” curve appearance. Statistical control limits are calculated using this technique. These control limits distinguish, at a chosen level of confidence, signal-to-noise ratio for an in-control data set from variation that has significant, assignable causes. The operator can use them to objectively create, evaluate, and adjust alarm limits.
1.3 A statistical cumulative distribution technique described herein is also recommended to create, evaluate, and adjust alarm limits. This particular technique employs a percent cumulative distribution of sorted data set values. The technique is based on an actual data set distribution and therefore is not dependent on a presumed statistical profile. The technique may be used when the data set is either parametric or nonparametric, and it may be used if a frequency distribution appears skewed or has only a single tail. Also, this technique may be used when the data set includes special cause variation in addition to common cause variation, although the technique should be repeated when a special cause changes significantly or is eliminated. Outputs of this technique are specific measurand values corresponding to selected percentage levels in a cumulative distribution plot of the sorted data set. These percent-based measurand values are used to create, evaluate and adjust alarm limits.
1.4 This guide may be applied to sample data from testing of in-service lubricating oil samples collected from machinery (for example, diesel, pumps, gas turbines, industrial turbines, hydraulics) whether from large fleets or individual industrial applications.
1.5 This guide may also be applied to sample data from testing in-service oil samples collected from other equipment applications where monitoring for wear, oil condition, or system contamination are important. For example, it may be applied to data sets from oil filled transformer and circuit breaker applications.
1.6 Alarm limit evaluating techniques, which are not statistically based are not covered by this guide. Also, the techniques of this standard may be inconsistent with the following alarm limit selection techniques: “rate-of-change,” absolute alarming...

SIGNIFICANCE AND USE
This practice is typically used to obtain in-service lubricating grease samples from machinery.
In this practice, a consistent and repeatable method is outlined for obtaining trendable samples from the following applications including motor-operated valves, gearboxes, pillow-block bearings, electric motors, exposed bearings, open gears, or failed grease-lubricated components. This allows for analysis and inspection of in-service lubricating grease that aids in predicting the life and condition of the grease-lubricated component. This information can be combined with other technologies such as infrared imaging, vibration analysis, and ultrasonic vibration analysis to predict when a machine may fail. The knowledge gained by the aforementioned analyses, in addition to the knowledge gained from the in-service lubricating grease analysis and inspection, may allow for more overall uptime by aiding in the prediction of grease-lubricated component failures as part of a predictive maintenance schedule. The prediction of a failing grease-lubricated component will also improve the level of safety of all who work around the component.
SCOPE
1.1 This practice covers the method to obtain a trendable in-service lubricating grease sample from the following configurations including motor-operated valves, gearboxes, pillow-block bearings, electric motors, exposed bearings, open gears, or failed grease-lubricated components.
1.2 In some cases, it may be necessary to take more than one sample from a piece of equipment to obtain more trendable results. Examples of this could be a large bearing that does not fully rotate, such as a slew bearing, or one in which sufficient mixing does not otherwise occur.
1.3 Samples taken in the above manner may need to be mixed to form a more homogeneous sample. This may also be true of other samples such as those taken from open face bearings.
1.4 The values stated in SI units are to be regarded as the standard. The values given in parentheses are for information only. The exception to this is a standard English units thread for which there is no metric equivalent.
Note 1—The standard pipe thread referred to is the national pipe thread tapered thread.
1.5 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.

SIGNIFICANCE AND USE
This guide is intended to provide machinery maintenance and monitoring personnel with a guideline for performing trend analysis to aid in the interpretation of machinery condition data.
SCOPE
1.1 This guide covers practical techniques for condition data trend analysis.
1.2 The techniques may be utilized for all instrumentation that provides numerical test results. This guide is written specifically for data obtained from lubricant samples. Other data obtained and associated with the machine may also be used in determining the machine condition.
1.3 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.