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Condition Based Maintenance Gap Analysis by Jason Lawler and Douglas Felker, US Army AMRDEC

Abstract

Condition Based Maintenance (CBM) has become an Army Aviation Priority.  The objective of CBM is not just the insertion of prognostics on an airframe, it is also to maximize the time on wing for all components and optimize maintenance practices, as well as Operational Readiness. The current maintenance strategy involves managing components by fleet based on statistical methods and safety factors. This strategy dictates intensive scheduled maintenance, unpredictable maintenance (failures), and scheduled removals. Successful CBM implementation requires a change to this maintenance strategy. 

Traditional Reliability Centered Maintenance (RCM) has demonstrated the great CBM utility when applied airframe wide to a new system; however, aviation improvements are now made continuously and under tight budget constraints. This dynamic cost conscience environment has curtailed the application of full traditional RCM. These factors have caused AMRDEC to develop a streamlined product which can deliver the CBM utility of a full blown RCM analysis, but has flexibility and value to be implemented in the current product development environment. The product which AMRDEC has developed is called the CBM Gap Analysis. Where the traditional RCM output is an optimized maintenance philosophy, the CBM Gap product is a list of design gaps preventing each line replaceable unit from becoming condition monitored. 

This paper presents the fundamentals of the CBM Gap Analysis and how it was applied in a case study on army aviation. The benefits of the CBM Gap analysis are the following: it identifies failure modes applicable to CBM; it identifies the hardware, sensor, software, and airframe requirements for CBM implementation and ranks the implementation changes in order of practicality; it assesses the applicability and utility of proposed diagnostic or prognostics and quantifies the return on investment in terms of increased reliability and maintenance; and finally it identifies the areas where research and development resources should be focused.

Background

In order to fully describe the CBM Gap Analysis, it must first be put in the context of CBM as defined by both CBM as defined in the current Department of Defense (DoD) CBM+ environment and by RCM practitioners. The DoD CBM+ initiatives strive to push inspection and scheduled replacement failure strategies toward CBM (to improve safety readiness and cost), DoD CBM+ has broadened this definition to include technologies such as Interactive Training, Item Unique Identification (IUID), and Integrated Information Systems.

All of the activities within the CBM+ initiative can be broken into the following three categories:

CBM Analysis Tools – Activities which define, analyze, or optimize the failure strategies. These tools can define maintenance for developing systems, optimize maintenance for existing systems, or suggest system improvements. Examples – RCM, FMECA.

CBM Enablers – Activities which change the failure strategy from a non-CBM action (ex. inspection, scheduled replacement) to CBM. This can only be done by a change to the system. Examples – Active and/or passive sensors or other monitoring capabilities.

CBM Ancillary Enablers – Activities that do not directly impact the CBM maintenance strategy, but are included in CBM+. It could be said that these activities increase CBM proportionally by decreasing the overall maintenance burden. Examples – Re-designs that remove failure modes that cannot be monitored.

These relationships are graphically represented in Figure 1.

Figure 1. Relationship between CBM+ activities

The RCM practitioners define CBM as a failure management strategy for a particular failure mode that meets a certain criteria such as:

• There shall exist a clearly defined potential failure.

• There shall exist an identifiable P-F interval.

• The task interval shall be less than the shortest likely P-F interval.

• It shall be physically possible to the task at intervals less than the P-F interval.

• The shortest time between the discovery of a potential failure and the occurrence of the functional failure shall be long enough for predetermined action to be taken to avoid, eliminate, or minimize the consequences of the failure mode.

Both of these interpretations of CBM are accurate in the context they are used; however, the actual implementation of CBM is not the only function in which they serve.

The CBM+ initiative also focuses on providing the support net required to perform condition based maintenance, while the RCM uses CBM as one of four primary failure management strategies. This relationship is shown graphically in Figure 2.

Figure 2. RCM/CBM/CBM+ Relationship

In this context, the CBM Gap Analysis is a CBM Analysis tool that will assist in focusing resources in implementing/advancing the overlapping areas shown in Figure 2.

It will not move the system maintenance toward CBM, only a CBM enabler will do that.  It will point program mangers in the right direction.

CBM Gap Analysis Concept

Traditional RCM analysis is a proven tool. During the analysis, an operating context is defined that describes the environment, usage, and configuration of the design that is fixed throughout the analysis. RCM then selects the best maintenance alternative based upon the fixed inherent design characteristics of the system. Its function is to optimize the maintenance strategies for each individual failure mode analyzed. The process is illustrated in figure 3.

Figure 3. Traditional RCM Process

Rather than fixing the system design, the CBM Gap Analysis fixes the maintenance strategy on condition monitoring and modifies the system design. The concept of the

CBM GAP is the following:

• RCM - Analyze failure modes of components to identify optimal failure management strategies.
• CBM Gap - Analyze failure modes of components to identify design/technology gaps that prevent the implementation of a CBM maintenance strategy.

As the RCM analysis team determines the applicability of CBM maintenance to a particular failure mode, the team determines what system modifications are required to drive the maintenance to condition monitoring. These modifications form a list of notional system add-ons that become CBM design gaps. The RCM team forces the RCM logic tree to a CBM conclusion. This process is shown in figure 4. 

The goal of the CBM Gap Analysis is to take advantage of the expertise gathered in an RCM analysis team. While the team is considering condition monitoring on an items particular failure mode, this extra task yields a product that determines CBM requirements. The CBM gaps can be as straightforward as taking advantage of symptoms already monitored (ex. vibration) or as difficult as the implementation as sensors which are currently beyond the state-of-the-art.

Figure 4. CBM Gap Analysis Process

 

CBM Gap Analysis in Practice

Due to the nature and level of expertise required to perform RCM and CBM Gap analyses combined with the continuous improvements and modifications current systems undergo it is imperative that these analyses focus on components that truly have an operational or maintainability impact. Currently, these components are identified through the AMRDEC ASAP (Aviation System Assessment Program). 

ASAP is a program that teams engineers with retired maintainers and operators with the mission of transforming maintenance records into operational and reliability metrics. This tool is used to identify top drivers in Mission Aborts, Mission Affecting Failures, Essential Maintenance Actions, Unscheduled Maintenance Actions, Scheduled Maintenance Actions, and Maintenance Man-hours (both Scheduled and Unscheduled).

This information is critical in down-scoping the RCM and CBM Gap Analyses to components that have the greatest impact. An example of this data is shown in Figure 5. As parts are identified, the analyst must have clear understanding of the existing maintenance philosophy and its relationship to each failure mode for each piece of equipment in the system. If CBM or RCM is to reduce or eliminate inspections, it must be clear which failure mechanisms each inspection is trying to find. It is for this purpose that the Preventive Maintenance/Failure Mode (PM/FM) was developed. The PM/FM matrix for an intermediate gearbox is shown in figure 5. This tool serves as a reference during any RCM or CBM Gap Analysis.

Figure 5. Sample ASAP Data 

The following example, using figure 6, demonstrates how the matrix can be used. Suppose vibration detection was added to the gearbox through the implementation of a health usage monitoring system (HUMS). How would the HUMS reduce preventive maintenance? The PM/FM matrix tells the analyst that the 120 hour inspection checks for metal on the magnetic plug, contamination, and internal failure. Since the 40 hour inspection already checks for metal on the magnetic plug and contamination, internal failure is the only new failure mode checked by the 120 hour inspection. If the HUMS engineer is confident that that all gearbox internal failure can be predicted by vibration monitoring, all failure modes of the 120 hour inspection would be covered. Further detailed analyses or testing would have to be completed before any inspection could be eliminated, the PM/FM matrix give the analyst a clear indication on where to start.

Figure 6. Preventive Maintenance/Failure Mode Matrix
 

Once the preliminary PM/FM matrix is completed, the RCM analysis can be conducted. The Analysis is conducted in the standard facilitated group approach. When the group determines that the answer to the CBM decision block is no, the RCM analysis is begun. The first step is to determine all symptoms of the failure mode. Examples of symptoms include change in temperature, pressure, or vibration. Other examples include changes in dimension, contamination, or increased fuel consumption.  

Next, notional design changes are made to the system to capture the symptom, communicate the symptom data, and determine from the data that a failure has occurred.

Notional design changes could be the addition of a sensor, wiring, caution light, or development of a vibration signature algorithm. For example, the loss of flow though a cooling fan would cause a change in pressure. To capture this symptom a notional system may include the addition of a pressure sensor that emits pressure data through a radio signal to a warning light which captures the signal and lights when a predetermined pressure dropped in reached. These notional changes are the CBM gaps. 

It is important that the analyst capture as much specific data on possible condition monitoring options as possible while the experts are in the room; however, the CBM Gap

Analysis is a living document and can be reviewed and updated by engineers and subject matter experts at any time. Also, the CBM Gap Analysis may require a more detailed breakdown of failure modes than that required by the RCM analysis. For example, for an

RCM analysis, it may be sufficient to “Black Box” all the gear and bearing failures of a gearbox into an “internal failure” failure mode. For a CBM Gap Analysis, each failure would have to be considered separately because the failure would emit a different vibration signature frequency.

Following the development CBM gaps for each symptom, each of the gaps are ranked for feasibility and divided into the following categories.

• Black – CBM is already being conducted to a sufficient level.

• Green – CBM could be conducted with existing design. (analysis of existing HUMS data)

• Blue – CBM requires a system design change (ex. addition of a sensor)

• Orange – CBM requires research and development (ex. requires miniaturization of state-of-the-art optical sensors)

• Red – CBM beyond the state-of-the-art.

It must be remembered at this point that this categorization is not driven by cost consideration, just technical feasibility. Following this, the gaps are ranked according to their practicability. A sample page of the CBM Gap Analysis is shown in figure 7.

Figure 7. CBM Gap Example

By presenting the CBM Gaps in this manner, several objectives can be met.

1. Green gaps are identified for immediate CBM consideration.

2. The analysis illustrates any benefits of partial CBM implementation (only some failure modes) on a component.

3. CBM Gap Analysis readily identifies what failure modes of a particular part can and cannot be affected by implementing CBM technologies.

4. The CBM Gap Analysis is a living document. As new technologies are applied to the system, the gaps change in color and rank.

5. Prognostic and sensor advancements can be analyzed globally by symptom.

(e.g. look at each component/failure mode gaps in vibration)

6. Reoccurring identical orange CBM Gaps throughout the system would give concrete justification for research and development efforts.

7. Failure modes with only red CBM Gaps provide a convincing argument against mandates to “do CBM on everything.”

Conclusion

The application of CBM/CBM+ to a weapon system is a noble endeavor. It has the potential to provide benefits such as improved safety, decreased maintenance, improved readiness, and reduced logistical burden to the war fighter; however, any engineer or program manager finds that the application of CBM grows quickly in complexity and scope as details are defined. The CBM Gap Analysis offers the engineer/manager a tool to track and manage CBM implementation.