Strategies for Reducing Operational upsets and Downtime in particularly in Refining and Petrochemical assets - An Instrumentation & Control View Point

In the process industries, such as refining and petrochemicals, instrumentation and control systems are the eyes, ears, nose, and heartbeats of operations. They constantly monitor the flow of processes, detect early warning signs of deviations, and provide real-time data that drives critical decision-making. Without these vital systems, operators would be blind to the complicated balance required to run complex industrial processes safely and efficiently.

Instrumentation and control systems not only ensure the accurate measurement and control of variables such as temperature, pressure, flow, process analytics and many more process variables but they also act as the first line of defense in identifying issues before they escalate into costly failures or downtime. Just as the human senses alert us to our surroundings and help maintain equilibrium, these systems continuously sense, process, and respond to the dynamic needs of a plant.

Malfunctions in field instrumentation, whether due to common causes factors such as grounding issues, systematic errors, misconfigurations, or the absence of robust predictive maintenance strategies and practices, can disrupt the entire production line, leading to unplanned downtime. This is why leaders invest heavily in preventive maintenance (PM) and predictive maintenance (PdM) and now a days step ahead to prescriptive maintenance (RxM) systems, integrating IoT-enabled sensors, digital twins, and machine learning analytics to keep a constant watch on critical assets.

The optimization of these systems is crucial to achieving and maintaining plant availability levels above 90 or 95% (depending on Organizational maturity in terms of maintainability strategy), minimizing downtime, and ensuring the seamless operation of vital processes. By leveraging real-time diagnostics, predictive technologies, and rigorous maintenance programs, these companies are not just preventing failures but actively enhancing the reliability and longevity of their equipment, ensuring that every pulse of the plant remains in perfect synchronization.

In the process industries, such as refining and petrochemicals, plant downtime caused by field instrumentation malfunctions varies depending on the complexity of the system, maintenance strategies, and the reliability of the instrumentation. However, some industry averages and benchmarks can help provide an estimate.

Here's a breakdown based on typical causes:

1. Downtime due to Field Instrumentation Malfunction:

• Earthing/Grounding Issues: Poor earthing, grounding and shielding can cause significant failures in instrumentation, especially in critical process control loops and safety interlocks. This can account for 5-10% of downtime.
• Misconfiguration (Calibration/Setup Errors): Incorrectly configured instruments can lead to process instability and shut down critical operations. Misconfiguration typically causes 2-5% of downtime.
• Random Failures (Due to Lack of Preventive Maintenance and Proof Tests): Instruments that are not part of a preventive maintenance (PM) program or lack predictive maintenance OR defined proof test not followed as per defined Safety Requirement Specification (SRS) measures tend to experience random failures. These failures can account for 10-15% of downtime.
• Non-utilization of Predictive Maintenance (PdM) Features: Many modern instruments and smart sensors/field instruments come with self-diagnostic or predictive features that remain unused due to lack of legacy cultural gaps, integration or training. This missed opportunity can contribute 5-10% of downtime, as PdM could prevent unforeseen failures.

Average Total Instrumentation-Related Downtime:

• Based on industry data and operational practices, it is estimated that 20-30% of unplanned plant downtime can be attributed to field instrumentation malfunctions. This figure includes the combination of common causes factors, systematic errors, configuration errors, lack of PM, and non-utilization of predictive maintenance features.

Benchmark and Industry Indicators:

Leading Indicators (Proactive metrics):

1. Preventive Maintenance (PM) Schedule Compliance: Percentage of scheduled preventive maintenance activities completed on time.
2. Utilization of Predictive Maintenance Tools: Usage rate of predictive analytics tools embedded in smart instruments (e.g., vibration analysis, real-time diagnostics).
3. Calibration Accuracy: Frequency of miscalibrations detected during routine checks.
4. Training on Instrumentation Asset Management Systems (IAMS): Percentage of staff trained on modern instrumentation management systems to minimize configuration errors.

Lagging Indicators (Reactive metrics):

1. Mean Time Between Failures (MTBF): Average time between field instrument failures.
2. Mean Time to Repair (MTTR): Average time taken to repair or replace faulty instrumentation.
3. Unplanned Downtime Percentage: Proportion of plant downtime attributed to instrumentation failures compared to total downtime.
4. Cost of Downtime: Financial losses incurred due to instrumentation-related downtime.

Industry Benchmarks:

• Plant Availability Target: Many refining and petrochemical plants aim for plant availability levels above 90-95%, meaning downtime (including instrumentation-related issues) is kept below 3-5%.
• MTBF for Instrumentation: In high-reliability operations, MTBF for critical instruments is typically aimed at 4-10 years (accounted with proof test interval, safety manual data & FMEDA) for well-maintained equipment.
• PM Program Effectiveness: An effective PM program should reduce unplanned downtime by 10-30% and increase overall reliability by 20-40% when combined with predictive maintenance techniques.

Key Takeaway: Instrumentation issues can cause significant plant downtime, but with robust PM and PdM programs, as well as proper lifecycle management, the downtime can be minimized, contributing to higher plant availability.

NOTE: Percentage statics shown above are taken from open sources articles, research, survey reports, case studies and advisories such as Advisory and Consulting Groups, Process Automation System Integrators and Asset Owners/End-users, Society for Maintenance and Reliability Professionals (SMRP) etc. from industry leaders in particular segment.