“The best way to predict the future is to study the past.” – Robert Kiyosaki
This is especially true when it comes to preventing equipment failures.
A high percentage of equipment issues reoccur. Approximately 70 to 80 percent of corrective maintenance happens again. History repeats itself. Why not learn from it and use that knowledge to prevent future equipment failures?
Using equipment failure histories to improve asset reliability is a best practice. The key to making that happen lies in the data.
Historical equipment failure data…
- Can be used to build targeted reliability programs (e.g., PMs, PdMs, and IIoT Sensors) to prevent equipment issues from reoccurring.
- Can be aggregated to know where the operation is spending their time and money, and to know which pieces of equipment and which problems to tackle first. Operations are getting leaner. A focused approach is required.
- Can be used for capital planning and budgeting purposes. Failure data and equipment lifecycle costs are key drivers in knowing what equipment to replace first.
Complete, accurate, and timely failure data Getting there is a two-step process.
Step One – Build the Foundation
Getting insightful equipment failure data begins with your EAM system master data.
EAM system master data is the foundational building block of the EAM system. It drives system use, provides context for system transactions, such as work orders, and supports KPI reporting and analysis.
EAM master data is master for a reason. It includes such critical entities as the equipment master and related coding structures.
The equipment master contains all of the physical, maintainable assets in the plant. The data in it should be structured and the naming standardized. Consistent, descriptive information will help users find records more easily.
An example of a standardized equipment naming and classification convention is below:
Equipment Class Codes like the ones above (sometimes called Type Codes) should be developed and assigned to all equipment records.
Equipment Class Codes can group assets together that share similarities. For example, pumps, motors, chillers, and compressors are all examples of equipment classes.
Equipment Class Codes can help drive “bad actor” and MTBF reporting.
Once classes are defined, then Problem-Failure-Action Codes can be developed and assigned to each equipment class.
Problem-Failure-Action Codes are captured on the EAM/CMMS work order and provide granularity into corrective maintenance issues.
- Problem Codes identify the initial issue with the asset.
- Failure Codes identify the initial cause of the issue.
- Action Codes identify the action the technician took to correct the issue.
Some example codes for a centrifugal fan are:
Problem-Failure Codes allow maintenance the ability to capture specific details surrounding equipment failures. They make it possible to look under the hood, so to speak, and to drill down into equipment issues. They provide granularity, transparency, and visibility.
Action Codes identify the maintenance action that fixed the problem. Next time around, maintenance will have a better idea of how to address the issue.
Historical failure data can also be rolled up and aggregated by frequency and/or costs. See cost rollup image to the right. This information allows maintenance to focus their energies on the areas that have the biggest impact on the organization.
More transparency leads to better reporting and a better understanding of the equipment. Asset classifications and failure codes will provide the information organizations need to improve asset reliability.
Step Two – Capture the Work
All corrective maintenance on the physical assets of the plant must be captured in a complete, accurate, and timely manner. This is done through the EAM/CMMS work order. This is a requirement. Without the data, we can’t do the analysis.
Examples of corrective maintenance work types are below. These types are assigned to work orders so that corrective maintenance can be easily sorted, grouped, and reported on.
Corrective maintenance work orders receive problem-failure-action codes. The importance of properly capturing and classifying corrective maintenance activities cannot be overstated.
Summary
By analyzing historical equipment failure data, we can better understand the present. We can then use this data to predict and shape the future.
In enterprise asset management, failure data drives informed decisions. Informed decisions create value. Complete, accurate, and timely equipment failure data can help the organization reduce unplanned maintenance and lower MRO costs. Guaranteed.
Analyzing equipment failure data can:
- Help us better understand the equipment and what stresses it.
- Identify the most common problems with equipment and the most common causes of its failure.
- Predict when that failure is going to happen again and drive a corrective action to catch it before it’s too late.
- Determine trends and help us make informed decisions about how those trends are likely to continue.
With complete and accurate failure histories we can track where problems originate, their causes, and the impact they have on an organization.
Understanding equipment failure history can help you think through the causes, effects, and significance of things that happened in the past.
Rich and actionable equipment failure histories are guaranteed to reduce unplanned equipment downtime. Which will lower maintenance costs and stabilize operations. This is a pre-requisite to meaningful and sustainable improvements.
The past can help predict the future as well as shape it. Accurate equipment failure histories give you insights.
If your asset reliability needs a jumpstart, please let us know. We offer the industry’s most comprehensive equipment failure library. We also provide custom problem-failure code development services. Contact us at info@swainsmith.com for a complimentary Problem-Failure-Action Code sample.