How can reliability engineering principles reduce your operational downtime?

Successful implementation of Reliability Engineering principles moves a company away from a fire fighting (reactive) approach to a more predictable domain. That way operational downtimes for inspection and maintenance can be proactively planned and contained to cause the least amount of disruption. As operators obtain clear understanding of their assets through data driven maintenance, it is easier to fulfil production obligations to their customers.

No doubt, reliability engineering has pivot role in plant availability by defining risk assessment, review existing maintenance plans and reducing or elimination of bad actors through team collaboration.

Though small, the word 'reliability' encompasses a profound meaning. Per my experience, RE principles from ISO 55000 and IEC 60300 reduce operational downtime by: 1. Preventive Maintenance (ISO 55000): Regular inspections and condition-based monitoring. 2. FMEA (IEC 60812): Identifying and prioritizing potential failures. 3. RCM (SAE JA1011/JA1012): Developing optimized maintenance strategies. 4. RCA (ISO 31010): Identifying and addressing root causes of failures. 5. Redundancy (IEC 61508): Ensuring system continuity with redundant components. 6. Reliability Testing (IEC 62506): Using stress testing and historical data for failure prediction. 7. Design for Reliability (ISO 9001): Integrating reliability into design and component selection.

FMEAs are good at describing the impact of failures on single items of equipment but to fully understand the impact of an equipment failure the criticality of the failure needs to be looked at too. This is done by looking at the whole system and assessing the whole system effect of the asset/equipment failure and what the outcome of the failure will be in relation to what the desired output of the system is. For example a pump failure on a system that has 10 pumps installed but only requires 5 to meet the desired output is far less critical to the whole system compared to a pump failure on a system with 2 pumps installed where both are required to meet the desired output. By adding criticality to a FMEA the exercise is far more informative.

Spot on Ed, having a robust EA method in place can positively impact the process. To fully consider all of the risks it often requires input from several departments.

Adopting a continuous improvement mindset is absolutely critical, however, it is important to stress that adoption of this mindset comes with understanding the "why" behind reliability practices. Training cannot be underestimated as it ensures that there are correct behaviours at play. When a team feels as though they are a part of the solution, they are more likely to feel empowered to take ownership on new processes, technology etc rather than feeling it is yet another change they are required to adopt. Recording and sharing of lessons learned is also of great importance as it isn't enough to identify areas for improvement in reliability practices, it is imperative to understand what you do with this information to ensure implementation.

Leveraging advanced predictive analytics tools can transform the reliability of rotating equipment in industrial operations. These tools use real-time data, historical records, and machine learning algorithms to forecast potential equipment failures and proactively prescribe maintenance actions. By enabling real-time monitoring and predictive maintenance, they significantly reduce unplanned downtime, ensuring continuous operation and optimal performance of critical assets. With advanced analytics providing actionable insights, maintenance teams can make data-driven decisions, improving the effectiveness of their strategies. Examples: APA by AVEVA, CORDANT by BH