Maintainability is an important aspect in overall system continuous improvement efforts. In fact, many times the term RAMS (Reliability, Availability, Maintainability, and Safety) or “reliability and maintainability” will be used. Similar to the way reliability prediction evaluates failures, maintainability prediction evaluates repairs. For example, if a system fails but can be repaired quickly, then system uptime, or availability, is high. For this reason, an important part of assessing your product or system availability must incorporate your repair and maintenance times.
Maintainability Prediction is a way to analyze a system to determine repair and maintenance measures, such as MTTR (Mean To Time Repair). MTTR and other metrics, such as MCMT (Mean Corrective Maintenance Time) and MPMT (Mean Preventive Maintenance Time), are the most common indictors used in maintainability analysis.
A maintainability prediction analysis uses mathematical equations defined in the widely accepted MIL-HDBK-472 standard to determine maintainability metrics. The calculations are based on the tasks or FD&I (Fault Detection & Isolation) Outputs needed to complete a maintenance activity and their associated times.
One of the main advantages of maintainability predictions is that they can be performed during the product design stage, enabling you to preview likely maintainability metrics. You can use this information to optimize your maintenance and repair activities to keep your system up and running with minimal downtime.
MTTR and Repair Metrics
MTTR (Mean Time To Repair) is the average time needed to repair a failed item. It is expressed in terms of hours. Other metrics that can be obtained from a Maintainability Prediction based on MIL-HDBK-472 include:
- MCMT: Mean Corrective Maintenance Time
- MPMT: Mean Preventive Maintenance Time
- MAMT: Mean Active Maintenance Time
- MMH/Repair: Mean Maintenance Manhours per Repair
- MMH/MA: Mean Maintenance Manhours per Maintenance Action
- MMH/OH: Mean Maintenance Manhours per Operating Hour
- MaxCMT: Maximum Corrective Maintenance Time
Maintenance activities can be corrective, meaning they are performed in order to fix a failure, or preventive, meaning they are performed in order to keep your system in good operating condition to avoid a fault. For example, replacing the air filters in your HVAC is a preventive action – you do this to avoid a HVAC system failure due to restricted air flow. If your HVAC compressor fails and you repair it or replace it with a new one, you have performed a corrective action. When evaluating system availability, both types or actions need to be taken into account for accurate metrics. Maintainability Prediction analyses support the ability to define any type of maintenance activity that has an impact on your overall system uptime.
Why do Maintainability Predictions?
There are many advantages to performing maintainability prediction analysis. The central goal is to optimize your repair and maintenance policies and procedures. It is difficult to achieve this goal without measurable statistics.
It can be especially difficult in the design stage of the product lifecycle to assess repair metrics when actual production has not yet started. In this case, maintainability predictions are helpful by allowing you to complete an evaluation of your product prior to manufacture – while design changes that improve repair times can easily be implemented.
Maintainability prediction analysis can also be performed once a system is up and operational. By evaluating all the corrective and preventive maintenance actions across your system, a maintainability prediction analysis can provide insight into the activities or components that are causing long system downtimes. Unacceptable downtimes could be caused by a number of issues such as poor repair procedures, inability to correctly isolate a fault, or inefficiencies that cause the repair process to be too cumbersome or difficult to perform. Maintainability predictions can help in evaluating all these factors and provide insight to enable you to improve.
Maintainability predictions can be used starting from early phase design concept through to manufacturing and production. In fact, maintainability predictions are most useful when used throughout your entire product lifecycle and even into next-gen product development. You can start your prediction with as much information as you have, get a quick, early assessment, then refine your analysis as your design matures to get a more and more accurate assessment. As you then move onto future product revisions, you can start with your original analysis and adapt the lessons learned into your next design. In this manner, maintainability predictions become a key element in your continual improvement process.
How do I do a Maintainability Prediction?
If you want, you can obtain a copy of MIL-HDBK-472: Maintainability Prediction, the widely accepted maintainability prediction standard, and armed with your calculator, manually perform a maintainability prediction on your system. Clearly, an easier and accurate approach is to use a tool expressly developed for performing Maintainability Prediction analyses. This makes your analysis much faster and less error-prone, and successive iterations become a snap.
Relyence Maintainability Prediction
Relyence Maintainability Prediction is a browser-based, mobile-friendly, comprehensive package for performing maintainability prediction analysis. Relyence Maintainability Prediction fully implements MIL-HDBK-472 and offers a host of features to make your maintainability prediction tasks quick and efficient.
Read more about Relyence Maintainability Prediction, contact us today so we can talk about your maintainability prediction needs and how Relyence Maintainability Prediction can help, or sign up today for our free trial to see Relyence Maintainability Prediction in action.