Living RCM Certified® [1] procedures for work order data entry allow reliability engineers to perform reliability analysis [2]. Analysis usually precedes improvement. Living RCM Certified® adheres to the RCM terminology set in Standard SAE JA1011. Standard ISO 14224 uses a different set of terms derived from FMECA (Mil Std 1629A). Maintenance engineers analyzing and reporting data from the EAM and CBM systems tend to use terminology from both standards. Clashes in the meanings of terms can lead to misunderstandings when performing reliability analysis.
Identical words and phrases will differ in meaning depending on which lexicon (ISO 14224 or SAE JA1011) governs a discussion. The terminology differences can be confusing. If we wish to apply reliability analysis to data samples from the EAM system, we should be aware of those differences. We can consult a table that maps their respective terms between the two standards. Such a table follows:
| Term | ISO 14224 | RCM (SAE JA1011) |
| Failure mode | effect by which a failure is observed on the failed item | The event that causes the failure. Its taxonomy has three levels: 1. Object part 2. Object damage (failure mechanism) 3. Failure cause. These can be expressed in a sentence arranged as noun, action phrase, and due-to clause. |
| Failure | termination of the ability of an item to perform a required function | Same meaning as ISO 14224 except that RCM makes a point of recognizing both total and partial termination since total and partial failures will usually be caused by different failure modes and will engender differing effects, consequences, and mitigating actions. |
| Failure mechanism | physical, chemical or other process that leads to a failure | Same meaning as ISO 14224 except that the failure mechanism is included as the second element (object damage) of the failure mode. |
| Failure cause | circumstances associated with design, manufacture, installation, use and maintenance that have led to a failure | Same meaning as ISO 14224 except that the failure cause is included as the third element of the failure mode. |
| Failure effects | Not defined explicitly in the ISO standard. However the term “effect” is used (in Table 6 — Failure data) to mean impact on equipment function. | A textual narrative of the sequence of pertinent events that take place before, during, and subsequent to the failure mode event. The events described include those that occur within the object part, component, subsystem, system, equipment, organization, community, and world depending on the severity of the consequences of failure. |
| Failure consequences | Not explicitly defined in the the ISO standard. However the term is used in Note b of Table 6 – Failure data, “Failure impact on plant operations. “Failure consequence” is also used in Appendix C, table “C.1 Failure consequence classification” (p 140) as a factor in risk analysis. | The reason why the failure matters, one of: 1. Hidden 2. Health, Safety, Environment (HSE) 3. Operational 4. Non-operational Each is the starting node of a branch in the RCM decision tree leading to a failure mitigation policy targeting the failure mode under consideration. |
Conclusion
RCM definitions of the maintenance knowledge elements are concise, unambiguous and can be more easily applied than those of ISO 14224. This is important because reliability analysis counts, in a variety of ways, the number of instances of a failure mode in a sample of maintenance events. The ratio of the sum of life spans ending in failure to the count of failure mode instances approximates[3] the MTTF. Weibull analysis goes further by relating the probability of failure to age. Extended Weibull analysis[4] includes the influence of CBM condition indicators in the probability calculation. All forms of reliability analysis require a sample from the EAM (work order) database. Failure mode instances must be identified consistently in the database for purposes of analysis.

RCM’s failure mode definition is particularly convenient for reliability analysis because it packages, hierarchically, the object part, object damage, and failure cause. Should only a high level analysis be required (see diagram) or should the sample be small, we could filter failure mode instances only to the level of the object part. This high level of analysis is often appropriate for reliability improvement activities. Should the availability or reliability needs in a given context require it, we could query failure mode instances having specific failure mechanisms and / or failure causes, provided we have a large enough sample. Hence it is usually preferable to identify object parts at a higher level and include additional detail (when relevant) in the failure mechanism and cause segments of the failure mode. By keeping the needs of reliability analysis in mind the level of detail and depth in a given branch of the RCM knowledge hierarchy will continually self-adjust as a result of daily interaction between the technician, reliability engineer, and the maintenance information system.
## Post Tree Navigation
LRCM
- CMMS Impediments to Reliability Analysis
- Components of continuous improvement
- How to start LRCM
- Justifying Living RCM Certified
- Leading and lagging performance numbers
- Living RCM Certified – Consulting Services
- LRCM – Reporting failure modes of rotable components
- LRCM and HSE
- LRCM Justification Template
- LRCM reliability analyst survey results
- LRCM reliability technician survey results
- MESH – RCM knowledge continuous improvement
- Motivation, leadership, training
- PAS-55
- RCM – Dashboards
- Reliability engineer’s work cycle
- Service vs. maintenance
- Streamlined RCM and LRCM
- Structured free text
- The role of media in living RCM
- The winning paper at the XIV International Congress of Maintenance
- Two philosophies in maintenance improvement
- Waiting for CMMS maturity
- What is a pilot project?
- What is the difference between RCM and LRCM?
- Achieving Reliability from Data outline with video
- Course brochure – Living RCM Certified
- Deepwater Horizon
- Elevator description of LRCM
- How does LRCM “improve” RCM?
- Living RCM Certified
- Living RCM Certified eLearning
- Living RCM Certified® and ISO 14224
- LRCM – off the maintenance improvement radar
- LRCM-EXAKT – a general solution
- MESH Basic reliability analysis on the work order
- Mesh Living RCM Certified brochure – Mesh Cloud Service
- Obtener confiabilidad a partir de los datos – esquema del curso
- RCM – Analyst course outline
- RCM – feedback suggestion mechanism
- RCM – Living RCM
- RCM – LRCM dashboards
- RCM – feedback – suggesting a new failure mode
- Training course in achieving reliability from data
- Two kinds of decision making in maintenance
- Two LRCM purposes
- Videos
- Why Living RCM works
RCM
Reliability Analysis
- Achieving Reliability from Data
- Challenges to Achieving Reliability from Data
- Data analysis precedes reliability analysis
- Data is the key to the way forward
- Defeating CBM
- Does historical age data have value?
- Failure declaration standards
- Free text on the work order
- How much data is required for RA?
- How to assess EAM and CBM predictive capability
- Interpreting failure data
- LRCM – Reporting failure modes of rotable components
- Maintenance software
- Mesh: 12 steps to achieving reliability from data
- RA requires LRCM
- Reliability analysis in 2 dimensions-Part 2
- Sample selection
- So you’re getting an EAM
- Take the EAM data health check
- The CMMS barrier to RCM
- The data barrier to analysis
- The reliability data Catch 22
- Thoughts from a mine maintenance engineer
- Variations in a sample
- Warranty for haul trucks
- Weibull exercises
- What’s the right data?
- A survey of signal processing and decision technologies for CBM
- Achieving reliability from data
- CBM Defined
- Conditional failure probability, reliability, and failure rate
- Conditional probability of failure
- Conditional probability of failure vs. hazard rate
- Criticality analysis in RCM
- Diagnostics versus prognostics
- Difference between LRCM and EXAKT
- EXAKT’s Three Modules
- Expected failure time for an item whose maintenance policy is time-based
- Failure analysis for reliability analysis
- Failure probability prior to attaining MTTF
- FAQ
- FMEA according to Wikipedia
- Is “random failure” really random?
- Leading and lagging performance numbers
- LRCM and the Failure Finding Interval
- MTTF is the area under the reliability curve
- Myths about RCM in heavy mining equipment
- Non-rejuvenating events
- Optimal PM and spares strategies – exercises
- Performance metrics – Low and High level KPIs
- Problem statement
- Purpose of RA
- RA – Micro (day-to-day decision) analysis
- Random failure and the MTTF
- Random failure is exponential reliability decay
- RCM – Living RCM: Achieving reliability from data
- RCM vs RA
- Real meaning of the six RCM curves
- Reliability analysis is counting
- Reliability trend yes Weibull analysis no
- Remaining Useful Life Estimation Using Hybrid Monte-Carlo Simulation and Proportional Hazard Model
- Safety Instrumented Systems
- TBM or CBM?
- Terminology in LRCM
- Thinking RCM
- Time to failure
- What is PM?
- What is the scale parameter?
CBM
- A survey of signal processing and decision technologies for CBM
- Automating CBM
- Building a CBM decision model
- CBM Exercises
- CBM Optimization
- Combined analysis for early predictive maintenance
- Deploying the CBM model
- EXAKT cost sensitivity analysis
- EXAKT needs LRCM
- EXAKT vs Weibull
- Measuring and Improving CBM Effectiveness
- Optimizing a Condition Based Maintenance Program with Gearbox Tooth Failure
- RCM – Reliability analysis in more than two dimensions is CBM
- Smart CBM demo
- What is Maintenance Decision Automation?
- Confidence in predictive maintenance
- Diagnostics versus prognostics
- Inspections – CBM and others
- Inspections or CBM?
- Internal and external CBM variables
- NAVAIR and the PF interval
- Objectivity in condition based maintenance decisions
- Optimized interpretation of CBM data
- P-F Interval a red herring?
- PF interval from the failure rate
- PM, PdM, Proactive Maintenance
- Predictive analytics
- Temporary fix work orders
- The elusive P-F interval
- [1]A maintenance work order related methodology to ensure analytic grade age data in the EAM database and continuous updating of the RCM knowledge base. These are the prerequisites for model based maintenance decisions.↩
- [2]Reliability analysis is the conversion of age and condition data to decision enabling rules called “models”↩
- [3]The ratio does not consider life suspensions due to PM or lifetimes having their life beginnings or endings outside the sample.↩
- [4] called Proportional Hazard modeling (PHM)↩
Leave a Reply
You must be logged in to post a comment.