Everything you want to know about "Asset Health" but was afraid to ask

Everything you want to know about "Asset Health" but was afraid to ask

 Everything you want to know about "Asset Health" but was afraid to ask

Reliability Software – Managing the Health of the Assets. "Background – the new approach to maintaining assets"
Studies originally conducted in the airline industry and subsequently validated across other industries have shown that approximately 80% of all mechanical, electrical and structural failures are random in nature and cannot be effectively correlated to time or operating hours.  While most industrial maintenance organizations have for decades relied on time-based preventive maintenance (PM) tasks, the recognition that most failures are random has caused many companies to re-evaluate their proactive maintenance programs.  Invariably, the conclusion is that if time-based maintenance represents the majority of proactive activity, then the wrong work is being done.  And it’s not just a question of using a tool such as Weibull analysis to fine tune the timing of age-related PM’s.  Instead, leading companies are learning to develop the right kinds of proactive tasks to manage random failures. 

Developing the right proactive work program is not simple, but there are many well documented proactive methodologies; Reliability Centered Maintenance (RCM), Failure Modes and Effect Analysis (FMEA), and Maintenance Task Analysis (MTA) which can assist firms in identifying the right work. These approaches look at all of the ways that an asset can fail (Failure Modes), and they take a different approach to failure management.  Rather than attempting to use time-based tasks to manage the asset, this new approach to maintenance is focussed on mitigating the consequence of failure at the Failure Mode level.  
This approach looks at each specific Failure Mode, and determines the best proactive task or tasks to detect failure or prevent its consequences.   Done properly, the result will be a high percentage (>80%) of tasks that require some form of condition monitoring, and a much lower percentage (<20%) that rely on time-based tasks, or tasks related to operating age.  In addition, the failure analysis will identify the corrective work to be performed when early signs of failure are detected.
Condition monitoring tasks, driven by an understanding of failure modes, create a picture of equipment health from visual inspections, the appropriate use of predictive technology (thermography, vibration, non-destructive testing, etc.) and online equipment data (pressure, temperature, flow, amps, etc.). These condition-monitoring activities generate massive amounts of data related to the health of the equipment.  To be of real value to maintenance and operations, the data must be effectively centralized, analyzed, and compared against pre-defined “normal” states, allowing users to focus on just the non-normal data.  Done effectively, this management of condition information will lead to dramatic improvements in asset reliability.

Reliability Software  

Reliability software has been developed to act as a single application with which to develop the complete Asset Reliability Program - the list of all proactive tasks for optimal maintenance of each asset.  In addition, the reliability software is a tool to implement an Asset Reliability Program. Reliability software creates a single place for monitoring the effectiveness of these Asset Reliability Programs; collecting, analyzing and displaying all asset condition data. The reliability software supports developing and managing the Asset Reliability Program, and managing all of the sources of data that are needed to manage the health of an asset. 

Building an Effective Asset Reliability Program  

Effective reliability software provides a tool to capture the entire process of identifying the right work to proactively maintain assets.  In many environments today, there is an opportunity to transition from the current informal work identification (Work ID) process (Figure 5.1.1), to a process that is more formalized.    
In a typical informal Work ID process, we often find that work is identified through operations initiated Work Requests (signalling that a failure has already occurred), manufacturers generic time-based task suggestion, work that has always been done but for which the justification is non-existent or not clear, as well as some level of predictive technology. If any RCM has been done, the results of the analysis usually end up in a binder sitting on a shelf. In these environments, we often find paper records of condition inspections being conducted - but they rarely lead to new work being identified – instead they pile up on a desk and serve only as an after-the-fact reminder that a failure could have been prevented.

Reliability software helps you to develop a more formal work identification process (Figure 5.1.2), so that all proactive work is tied directly to a failure mode. Reliability software should also be seen as tool used to systematically prioritize assets, document the work ID analysis, create the asset reliability program along with health indicators and alarm levels, and specify the recommended proactive corrective actions.

 Reliability Software Puts the Asset Reliability Program into Action  

Whether the correct proactive work was identified through a formal Reliability Centered Maintenance or some other methodology such FMEA (failure modes and effect analysis) or MTA (maintenance task analysis) the software has the technology to put that proactive Asset Reliability Program into action. This is important because typically when a formal or informal analysis has been performed and a maintenance task is identified it takes additional time and effort to implement the new task. 
Reliability software will record each task in the new Asset Reliability Program, linking all condition monitoring tasks directly to the indicators to be checked. From there, check sheets instruct the operations and maintenance personnel to conduct the inspections, and through the handheld devices, current data is collected and fed to the reliability software.  This software provides a single place from which to view and respond to any non-normal data that has triggered alarms.    
A sound failure analysis will typically determine that about 33% of failure modes should be allowed to run to failure, while recommending redesign for about 4% of all failure modes.  The remaining failure modes will be the focus of Asset Reliability Program, which is managed within reliability software.  Over 80% of the tasks in a well defined Asset Reliability Program will be made up of condition/state inspection tasks, while less than 20% of the tasks will be age-based (Figure 5.1.3).  While all CMMS products can adequately handle triggering tasked based on operating age, reliability software is the only tool designed to handle both age based and condition inspection tasks.
As condition monitoring tasks are defined, appropriate indicators are set up for the inspections, along with defined normal and non-normal states.  For a temperature reading for example, the normal state may be defined by a range of temperature values.  Various levels of non-normal states may also be defined to correspond to increasingly unacceptable temperature ranges.  With each state, or temperature range in this case, a user defined alarm level can also be defined.  As temperature readings are recorded, the reliability software compares the new value to the normal and non-normal states and triggers an alarm when non-normal values are recorded.
Reliability software collects condition and state data from a variety of sources, including visual inspections, predictive maintenance technologies, process controls, sensors and data historians. Data from predictive technologies such as vibration analyses, thermography and oil analysis is also utilized within a reliability software program.  
Reliability software tracks several kinds of condition indicators including:
  • Simple numeric values     
  • Qualitative or descriptive information, with user-defined value lists     
  • Mathematical calculations     
  • Rule-based configurations 
Reliability software uses single or multiple data points, applying rules and calculations to create a true picture of equipment health.  With the transition to an effective Asset reliability Program, maintenance and operations personnel will be collecting and managing an increasing number of condition based proactive tasks.  In this environment, it’s critically important that the newly recorded readings be utilized immediately.  
The reliability software helps out with this data management challenge by sorting through the normal and non-normal data, and displaying the results in ways that are easy to understand, and utilize.  Rather than requiring users to sift through piles of paper based inspection readings, as non-normal values are recorded, alarms are triggered and displayed, drawing attention to only the few data points that currently signal the potential for equipment failure.  

The plant, all of its assets and failure-mode-specific health indicators can be displayed in two different ways.  The first display method uses an Indicator Panel, a two-panel screen showing the entire plant hierarchy and all assets on the left side (Figure 5.1.4), and relevant health indicators on the right side.  See screen to right. The reliability software equipment hierarchy must aligned with the current CMMS/EAM.
The Indicator Panel in a reliability software allows you to monitor asset condition and, at a glance, see any indications of impending failures – before the failures occur. Flashing alarms are displayed when assets are moving closer to functional failure and alarm severities are readily understood based on the type of icon displayed. Corrective maintenance decisions can be made based on asset health and risk to the business, so that the right work can be performed at the right time.
The second way to display asset health indicators is through graphics, photographs and diagrams, as shown in the compressor example (Figure 5.1.5).
As non-normal data triggers alarms, the indicators begin to flash on the drawing.  And since the alarms roll up the equipment hierarchy, a user could easily drill down from a higher level picture to the compressor in this case, to quickly zero in on the flashing alarm and the non-normal data.  This capability makes it very easy for users to respond to data immediately as it is updated, without the need to review all data.

Asset Health Trend Plotting  

Many companies have collected condition readings for years, but have lacked the tools to manage the data properly. Charting of asset health indicators allows trends in asset condition to be easily noticed. Bands of color graphically show alarm severity ranges (Figure 5.1.6).5.1.6 Condition Indicator Graph
This graphing capability dramatically improves management’s ability to proactively intervene to ensure that asset health is maintained and reliability is maximized.

Using Hand Held Devices to Collect and upload Condition Inspection Data

The software replaces the manual paper-based approach to collecting, storing and analyzing condition data (Figure 5.1.7) , allowing inspection routes to be automated using simple hand held devices.  
In the case of subjective inspections, operators will be presented with a predefined list of observation values form which to choose, making the condition data more quantifiable and useful (Figure 5.1.8).

Capturing the Experts’ Knowledge about Asset Condition and Reliability Programs

Reliability software captures the knowledge of your equipment experts, the operators and maintainers who know the equipment best.  In many companies, these employees have worked with the equipment daily for decades, and so their knowledge is invaluable.  The challenge is to find a way to store this information so that all employees can take advantage of it for their daily work.  Reliability software captures this knowledge and makes it available.  
During the failure analysis, the maintainers and operators for the target asset will be asked to contribute their knowledge of the ways the asset fails and the ways that have been found for detecting or preventing failure.  The condition monitoring detail that was previously carried around in personal pocket books becomes some of the critical knowledge stored in software, as the new Asset Reliability Program is defined.   These employees usually know exactly how the equipment operates, and how best to perform the required condition checks.  
In the context of a well defined failure analysis, we’ll capture this knowledge, formalizing it by linking the proactive tasks to specific failure modes, and gaining agreement between operations and maintenance that we’re doing the right work.  For example, the reliability software screen shown below (Figure 5.1.9), captures the calculation to determine the effectiveness of a heat exchanger. You no longer need to remember the engineering calculation since the reliability software stores the expression, making it permanently available for all to use. 
A reliability software program combines data from various indicators to determine the overall effectiveness of the heat exchanger and when a non-normal value is found, prompts the user with the predetermined corrective action.  Visual or other sensory inspections are logged via hand-held data recorders (PDA’s). Non-normal readings will trigger alarms and follow up work tasks to suggest more rigorous inspections or corrective work.

Integration to Enterprise Asset Management/Computerized Maintenance Management Systems (EAM/CMMS)

Asset reliability software helps companies to leverage and extend the benefits they are getting from current investments in any EAM/CMMS. Maintenance organizations need to incorporate predictive and proactive, condition-based maintenance capabilities upfront to monitor asset conditions and help maintenance personnel keep reliability and productivity on target. Reliability software complements EAM systems to make them more effective because they address upfront the need for work identification and processes not addressed by the EAM (Figure 5.1.10). 
While EAM/CMMS supports the maintenance control process (work planning, scheduling and execution), reliability software supports the complete equipment reliability process.

The Bottom Line

Achieving and sustaining improved levels of reliability through the monitoring and managing asset health will help manage maintenance costs, asset reliability more effectively. Asset reliability improves output and uptime, creates higher service levels, creates a safe environment and enables companies to comply with environmental regulations. Using reliability technology for managing health of a company’s assets and protecting these assets ensures business goals are met and companies stay competitive.

The chapter was developed in conjunction with Ivara Corporation who provided the information and graphics shown in this chapter. This was great company to work for as technology was advancing. Great People, Smart Engineers.

To all my friends, The Maintenance Community on Slack is an incredible free space where over 1,500 maintenance and reliability professionals like myself share real life experiences with each other.   
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