Asset Maintenance Data, a crucial component in the industry, is used to collect and exchange reliability and maintenance data for equipment. Understanding the significance of an Asset Management Data Standard (AMDS) is key, as it provides guidance on the data required for analysis (MTBF, MTTR, bad actor, etc.) and benchmarking against industry peers.
Asset Management Data governance is essential to any successful asset management data strategy. AMDS should be part of a company's overall data framework. Ideally, executives and other representatives of an organization's business operations, as well as IT and data management teams, should all be involved in AMDS governance efforts.
A monster challenge in today's world is the enormous amount of data collected, modified, and stored daily. An Asset Management Data Standard provides guidelines on what data needs to be collected. However, a structured approach is required to understand how the data will be collected, consumed, analyzed, and sustained to drive decisions. The intent is to provide a simplified process to drive decision-making. The six key areas are:
1. Develop an asset hierarchy standard
An Inconsistent asset hierarchy makes it difficult to understand the location of the physical asset in the facility as well as its relationship to other equipment within the process. ISO14224 provides guidelines for what the asset hierarchy should look like. Impacts from a consistent hierarchy will provide potential impacts as mentioned below:
- Work identification—A well-defined hierarchy makes it easy to locate the asset in the system and assign work to it. This improves planning efficiency, wrench time, and safety, which can reduce maintenance costs.
- Cost visibility – By identifying work to the correct asset, costs can be tracked against the asset. In today's low-cost environment, this helps in the Pareto analysis of what are the high-cost assets.
2. Define equipment classes and characteristics
Develop a standardized list of minimum equipment characteristics required for each specific asset class. This will ensure that:
- The operating limits (safe operating limit and integrity operating limit) for your equipment have been defined in the CMMS and are easily accessible. This should be used as a triggers for alerts during condition monitoring programs and operator rounds.
- Classifying assets in asset classes will help the maintenance and reliability engineering teams "bucket" data in a way that dedicated teams with specific skill sets can address.
For example - centrifugal pumps within the rotating equipment class have the highest maintenance repair costs.
3. Define maintenance work categories
ISO14224 provides excellent guidelines on the categories of maintenance work and related activities. By enforcing a process and monitoring it on a frequent basis, maintenance work coming through the CMMS can be categorized. This categorization of maintenance work provides the foundation of what data will be analyzed from a reliability perspective. Some key definitions include breakdown repairs, failures, operator basic care, etc. This is essential because:
- It defines the data set that will be used to analyze maintenance and reliability performance
- It helps understand the reactive versus proactive nature of maintenance
- Provides maintenance team the tools necessary to improve business processes
4. Define maintainable item codes, failure codes, and cause codes
Defining a set of maintainable item codes, failure codes, and causes codes in a structured hierarchy will provide end users with a small set of relevant codes. For e.g., Centrifugal Pump, Seal, Leaking, and installation. By having this information over a period of time, reliability improvement efforts can be targeted, and maintenance cost optimization can be achieved. Defining these codes in a methodical way will:
- Provide end users with small set (10-15) of codes to pick from
- Set up measurement of performance for work order completion and close out
- Provide reliability and engineering teams specific and relevant information to define the problem. Typically, the cause code may not be known at the time of work execution, but efforts and metrics can be put in place to track the number of outstanding work orders/ notifications that do not have a cause code, etc.
Implementation should also define how that data will be consumed and what decisions will be made based on the data. For that purpose, the last two processes are as follows:
5. Develop an integrated maintenance and reliability business processes
As part of the implementation, a set of business processes need to be defined to understand how information and data flow, how the maintenance work will be identified, planned, scheduled, executed, and closed out, as well as, how reliability will consume the data, analyze it, validate it and provide recommendations. I must emphasize that Maintenance and Reliability (and, for that matter, operations) are joined at the hip. One cannot function without the other.
6. Governance, change management, and performance measurement
This is where leadership, governance, and performance measures are required to sustain the implementation of the program. While this piece is applicable to any implementation program, from an M&R implementation perspective, it is critical to pay attention to this because:
- Maintenance is seen as a cost center and is under pressure to reduce cost instantaneously.
- Reliability is often relied on after significant events and is not part of the continuous improvement philosophy.
- Results from reliability analytics and usage of codes are often not communicated back to the shop floor. It is important for people to realize that the codes used and the information put into CMMS are used to make data-driven decisions.
- History, History, History...It is difficult to prove that a failure was prevented and cost was avoided if it was never documented correctly.
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