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5 Principles of Asset Reliability Management

5 Principles of Asset Reliability Management

Asset Reliability Management (ARM) is a practice that systematically manages physical assets to maximize availability, dependability, performance, and overall efficiency. Asset reliability generally refers to the ability of a physical asset or piece of equipment to perform its intended function without failure or breakdown over a specified period.

Industrial organizations such as manufacturing, energy, transportation, and others heavily rely on different types of assets, such as machinery, equipment, and instruments, to achieve their operational objectives.

Reliability practice is a key aspect of asset maintenance management. The goal is to prevent unexpected operational failures and disruptions, which can lead to increased costs, safety hazards, and a negative impact on overall business performance.


Key Values of Asset Reliability Management (ARM)

There are three key values of asset reliability management:

  1. Availability
  2. Performance
  3. Lower TCO.

Generally, Asset reliability is often achieved through proactive Maintenance. These approaches involve regularly inspecting, monitoring, and maintaining assets to identify and address potential issues before they result in equipment failures.

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Principles of Asset Reliability Management

1. Proactive Maintenance Strategies:

Generally, Asset reliability is often achieved through proactive Maintenance. These approaches involve regularly inspecting, monitoring, and maintaining assets to identify and address potential issues before they result in equipment failures.

It is important to move from a reactive to a proactive maintenance approach for reliable plant operation. This transformation involves implementing preventive and predictive maintenance strategies to identify and address potential issues before they lead to equipment failure. Proactive Maintenance can significantly improve asset reliability and reduce unplanned downtime.

  • Preventive Maintenance: Preventive Maintenance is scheduling maintenance tasks periodically to prevent equipment failures, ensuring optimal performance and longevity.
  • Predictive Maintenance: Using the data generated by assets, execute data analytics to forecast equipment issues, execute maintenance service, minimize downtime, and optimize performance predictably.
  • Prescriptive Maintenance: Using the data generated by assets, identify and recommend specific maintenance tasks such as “replace filter” to optimize asset performance and prevent potential failures

2. Risk-based Maintenance:

Asset reliability management involves making decisions based on a thorough understanding of the risks associated with asset performance and reliability. The risk-based maintenance approach includes:

  • Identifying and assessing potential failures.
  • Understanding the consequences of those failures.
  •  Prioritizing actions based on risk mitigation.

Risk-based maintenance practice requires an IoT-based Asset Condition Monitoring solution to detect the health conditions of the asset to identify the potential risk factors. 

In addition to detecting asset health conditions, performing root-cause analysis can identify underlying issues, address problems, and enhance overall reliability.

3. Continuous Improvement :

The continuous improvement practice establishes a culture by regularly reviewing asset management procedures. Continuous improvement ensures that asset reliability management strategies evolve and adapt to changing conditions, technologies, and business requirements.

  • Maintenance Checklist:

Enforce maintenance checklists and capture operator feedback for continuous improvement based on past lessons learned from failures and successes.

  • Maintenance Summary:

It is a health summary report prepared after maintenance tasks to provide a concise overview detailing activities, issues addressed, and equipment status for proactive decision-making.

4. Asset Life Cycle Management:

Asset lifecycle management involves tracking asset utilization and performance over time to understand downgrades that may lead to asset replacement. There are three key activities required to track the asset’s lifetime.

  • Usage Metering:

Install an IoT-based automated metering system to read the usage level of the asset to keep track of up-to-date asset life. Tracks usage data for informed decision-making, optimizing resource allocation, and enhancing efficiency.

  • Maintenance History:

It required CMMS or Maintenance Software to keep track of all assets’ maintenance history, past activities, repairs, and inspections for insights into equipment performance and reliability.

  • Warranty Management:

Keeping track of warranty information in a single repository helps to monitor warranty details for timely claims, cost savings, and effective risk management.

5. Collaboration:

Maintenance team collaboration is vital for efficient asset management. Shared expertise, effective communication, and coordinated efforts maximize productivity, enhance problem-solving, and ensure the longevity of critical equipment and systems.

Implement better collaboration among teams requires the following three key practices:

  • Knowledge Management:

A knowledge management system must capture maintenance knowledge in a centralized system to organize and share insights for informed decision-making and continuous improvement.

  • Team Communication:

Typically, different teams or shift engineers are involved in the maintenance operations, which require strong communication among themselves. Information sharing or messaging ensures seamless collaboration, quick issue resolution, and efficient task coordination for success.

  • Data Accessibility: 

Proving tools (e.g., mobile apps) to access maintenance data from anywhere facilitates easy retrieval for informed decisions, enhancing efficiency and optimizing asset reliability.

Fogwing Asset+ for IoT Data-Driven Asset Reliability Management (ARM)

Fogwing Asset+ is the comprehensive software for data-driven asset reliability operations. Fogwing Asset+ offers the following features by default so that the maintenance team can practice the above five principles without pain.

  • Preventive Maintenance through automated scheduling.
  • Condition-based Maintenance through IoT device connectivity 
  • Predictive maintenance recommendation based on sensor data
  • AI-based maintenance checklist generation and enforcement
  • Automated maintenance summary and user feedback capturing.
  • In-built Asset Performance Monitoring
  • Team communication through work order tasks summary
  • Knowledge management through documentation repository for asset spec and instruction management.
  • Maintenance history data accessibility through web and mobile application


Implementing these principles in asset reliability management can help organizations enhance the performance, efficiency, and longevity of their assets while minimizing risks and improving overall operational reliability.

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