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Building a Holistic Reliability Strategy

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The strongest reliability programs don’t rely on a single tactic. Instead, they combine multiple, complementary strategies that address assets across their entire lifecycle. Here’s how each component fits into the bigger picture.

Predictive and Preventive Maintenance

Traditional maintenance schedules, such as changing parts at a fixed frequency whether they need it or not, often waste resources. Predictive and condition-based maintenance, by contrast, uses data to act only when needed:

  • Condition-Based Monitoring (CBM): Vibration, temperature and pressure sensors provide real-time asset health insights. By detecting early anomalies – such as abnormal heat or vibration – plants can intervene before a breakdown occurs.
  • Risk-Based Inspections (RBI): Not all assets carry equal risk. RBI prioritizes inspection efforts on equipment where failures would have the highest safety, environmental or financial impact. A word of caution here.  Employing RBI in an unreliable older brown field plant may actually increase the cost of inspection and repair as you bring the equipment into serviceable condition.
  • Digital Twins: Virtual replicas of assets or processes simulate how equipment will behave under different conditions. Operators can test “what-if” scenarios – such as process changes or equipment failures – without risking real-world downtime.
  • Sensor-driven Artificial Intelligence (AI) solutions that can take notification actions and, in some cases, corrective actions are in use today. 
    Together, these approaches shift maintenance from reactive firefighting to data-driven prevention. 

Reliability-Centered Maintenance (RCM)

RCM is a structured process for determining the most cost-effective maintenance strategy for each piece of equipment. Instead of over-maintaining low-risk assets or under-maintaining critical ones, RCM asks:  

  • What’s the function of this equipment?  
  • What happens if it fails?  
  • What’s the best balance of preventive vs. corrective action only?  

This framework ensures resources are used where they deliver the most reliability impact.

Asset Integrity Management (AIM)

AIM takes a lifecycle view of reliability. It ensures assets continue to perform safely and effectively, from installation to decommissioning. Key practices include:

  • Corrosion monitoring to track material degradation.
  • Stress analysis and Non-Destructive Testing (NDT) to detect hidden flaws.
  • Compliance management to meet strict industry and regulatory standards.

Strong AIM programs, integrated with the engineering document system and the EAM system, reduce unplanned shutdowns and extend asset life while minimizing safety and environmental risks.

Integrated Operations and Data Analytics

Today’s plants are data-rich but insight-poor. By integrating data systems and applying analytics, operators can move beyond dashboards to actionable intelligence. Examples include:

  • Predicting compressor surges that could otherwise cause costly downtime.
  • Monitoring heat exchangers in facilities to prevent failures that compromise production.
  • Optimizing boil-off gas recovery systems to improve efficiency and reduce waste.

Integration transforms raw data into decision-support information for reliability.

Safety and Environmental Systems

Even the most reliable plant faces risks, which is why safety systems are non-negotiable.

  • Safety Instrumented Systems (SIS), Emergency Shutdown (ESD) and Fire & Gas (F&G) systems must undergo rigorous testing to guarantee performance.
  • Redundancy and fail-safe design ensure critical protection works even if a component fails.

In high-stakes industries, these layers of protection safeguard lives, assets and compliance.

Human Reliability

Technology alone can’t guarantee reliability – people play a decisive role. Human error is a leading cause of failures, but strong measures can mitigate risk:

  • Ongoing operator training ensures teams are prepared for normal, abnormal and emergency conditions.
  • Standard Operating Procedures (SOPs) create consistency and reduce mistakes. Add to it the use of a modern learning management system and you’ll have a much better overall solution.
  • Disciplined Management of Change (MoC) ensures no system or process change introduces hidden vulnerabilities.

When operators are confident and well-trained, plants run smoother, safer and more profitably.

Key Performance Indicators (KPI) and Continuous Improvement

You can’t improve what you don’t measure. Effective reliability programs track:

  • MTBF (Mean Time Between Failures) - The average time equipment operates between one failure and the next. It measures reliability for repairable systems.
  • MTTR (Mean Time to Repair) - The average time required to fix a failed component or system and restore it to normal operation.
  • Availability / Uptime % - The percentage of total time that equipment or a system is operational and performing as intended. Calculated as uptime ÷ total time.
  • MTTF (Mean Time to Failure) - The average time a non-repairable component operates before it fails.
  • Unplanned Downtime - Periods when equipment or systems are unexpectedly out of service due to failures or other unforeseen issues.

“What gets inspected, gets respected.”  - Peter Drucker

Tools such as Pareto charts help identify the “vital few” problems driving most reliability losses, while Root Cause Analysis (RCA) ensures lessons are learned from every major failure. Over time, this creates a feedback loop for continuous improvement.

Culture, Leadership and Strategic Alignment

Reliability is as much cultural as it is technical. These programs don’t succeed by technology alone. They require leadership, alignment and cultural adoption across the organization. The following elements are critical.  

Clear Leadership Vision and Alignment to Profit & Loss (P&L)

Reliability must be positioned as a business strategy, not just a maintenance initiative. When leadership ties reliability directly to profit and loss (P&L), it elevates reliability goals from engineering checkboxes to financial imperatives. For example: showing how every percentage point of availability translates into millions in additional revenue makes reliability a boardroom-level priority.

Strong Inter-Plant Communication

Large organizations often operate multiple plants or sites, each with their own reliability challenges. Without structured communication, valuable lessons remain siloed. Effective programs establish inter-plant forums, cross-site KPIs and shared reliability playbooks, ensuring that best practices from one site can be replicated across the enterprise.

Talent Management to Upskill Workforce

Even the most advanced predictive analytics tools are useless without skilled people to interpret and act on them. Upskilling operators, engineers and technicians through ongoing training ensures that staff can leverage AI tools, apply root cause analysis and follow reliability-centered maintenance practices. Strong programs treat training as an investment in resilience, not an expense.

Strategic Customer and Supplier Partnerships

Reliability extends beyond plant walls. Suppliers of critical equipment must be vetted for quality, lifecycle support and availability of spare parts. Customers, especially those bound by long-term contracts, should be engaged in conversations about uptime expectations and risk-sharing. Strategic partnerships transform suppliers into long-term collaborators in reliability performance.

Robust Data Collection and Knowledge Management Systems

Without reliable data, it’s impossible to make good reliability decisions. Strong programs implement integrated Enterprise Asset Management (EAM) and Asset Performance Management (APM) systems, ensuring that maintenance histories, inspection records and sensor data are available in one place. Knowledge management systems also ensure that insights from past failures are captured and used to prevent recurrence.

A Reliability Culture that Enforces Accountability

Culture drives behavior. A true reliability culture means employees at every level – from executives to technicians – understand their role in asset performance. Metrics must be owned by individuals, accountability must be enforced and successes should be celebrated. The culture must shift from reactive firefighting to proactive prevention, with leadership consistently reinforcing the message that reliability is everyone’s job.

Strategic Planning Framework

Reliability efforts succeed when they’re part of a structured strategic plan. This ensures that day-to-day activities are aligned with long-term business goals.

Objectives: What Are We Trying to Accomplish?

Objectives are broad statements of intent. For example: “Improve overall plant availability by 5% within three years” or “Reduce unplanned downtime to less than 2% annually.” Objectives establish the “why” behind reliability programs.

Goals: Measurable and Time-Phased

Goals break down objectives into measurable outcomes. For example:

  • Decrease Mean Time to Repair (MTTR) by 20% within 18 months.
  • Extend Mean Time Between Failures (MTBF) for critical compressors by 30% over two years.
  • Train 100% of operators on new digital twin software by Q4.

Strategies: Initiatives to Achieve Goals

Strategies outline how the goals will be met. For example:

  • Implement predictive maintenance using vibration and temperature sensors.
  • Deploy risk-based inspection (RBI) for high-criticality assets.
  • Introduce quarterly reliability review meetings across all plants.

Measures: Metrics Owned by Individuals

Metrics ensure accountability. Each KPI, whether uptime %, MTTR or availability, must be assigned to a responsible person. This prevents reliability from becoming “everyone’s problem but no one’s job.” For example, the maintenance manager may own MTBF targets, while operation supervisor's own uptime % metrics.

Tactics: Specific Actions to Drive Outcomes

Tactics are the daily, tangible steps that move strategies forward. Examples include:

  • Scheduling predictive analytics training sessions for technicians.
  • Updating EAM systems with standardized failure codes.
  • Running root cause analysis (RCA) on every major failure within 48 hours.

Together, objectives, goals, strategies, measures and tactics form a closed-loop system where reliability is tracked, managed and continuously improved.

    

Next Up: In Part 3, The Role of AI and Machine Learning in a Reliability Culture, discover how predictive analytics, automated FMEA and digital twins are helping operators eliminate unplanned downtime and drive smarter, safer operations. Also, don’t miss Part 1, Plant Reliability: Your Biggest Untapped Revenue Lever, explore how downtime, safety risks and poor reliability practices silently drain millions in lost revenue—and why addressing reliability early delivers lasting business value.