Risk, Performance and Cost: Striking a Balance in the Power Sector
By Thomas Adams, Vice President of Power Business Development at ABS Group
To meet service obligations and financial targets, every owner and operator of power generation assets must balance three major variables: risk, performance and cost. In the past, the guiding principle of many generators was "reliability at any cost." Today's competitive power markets demand a different approach focused on achieving acceptable reliability and quantifiable risk at a predictable (preferably lower) cost. When generators succeed in optimizing these tradeoffs, a large savings in operations and maintenance costs can be achieved without incurring unacceptable risks of equipment failure and downtime.
"As the power generation industry continues to evolve with many current and near term challenges, achieving a truly optimized, risk informed view of maintenance and asset performance can yield tremendous value for proactive operators going forward."
Risk Analysis as a Key to Unlocking Hidden Value
The key to unlocking the value of this balanced approach is the application of modern asset management and sophisticated risk analysis tools. Most power generation facilities use a computerized maintenance management system (CMMS) to serve as a central repository of asset and maintenance data, but most lack analysis and tools that provide true insights into operational risks, consequences, and total maintenance costs over time.
Various analytical approaches can be applied to the data in CMMS systems to understand the impact of different maintenance scenarios on the risk of equipment failure, the costs and downtime of those failures, and the long term cost of maintenance. These techniques center on applying a consistent risk analysis to the assets that measures the probability of failure under different maintenance procedures, such as extending preventative maintenance intervals. The risk can then be quantified and compared across an entire population of assets, and if maintenance procedures are changed, the impact to the plant's risk of downtime is fully understood making an informed management decision possible.
The results of this type of rigorous analytical approach can be powerful. Hidden optimizations can be discovered which may allow for extended maintenance intervals with low impacts to overall risk, which in turn generates significant savings. Plus, an analytical approach can help sell a change in strategy within the company and overcome any "not invented here" resistance.
Different Tools to Suit Different Environments & Goals
The tools used to perform this type of analysis are available as part of an overall Enterprise Asset Management strategy, and they range from add-in software to common CMMS platforms such as IBM Maximo, to analytical packages which process asset and maintenance data outside of the CMMS, to bespoke probabilistic risk models which can delve deeply into specific subsystems where critical failures and consequences must be fully understood.
Each tool has characteristics that make it more or less suitable in any given environment, and power generators should carefully study their options to make the best choice for their situation. The good news is that large advances have been achieved in software that can streamline and automate sophisticated analysis techniques, lowering overall costs and schedules and accelerating resulting savings.
Broad Application throughout the Power Sector
Many segments of the power sector are applying these techniques. For example, the nuclear industry has adopted a mandate called Delivering the Nuclear Promise to reduce operations and maintenance costs by 30% as many plants struggle to compete with low cost gas fired generation and ever cheaper renewables. These risk analysis techniques allow nuclear operators to find that magnitude of savings without incurring unacceptable risks. The same approach can work in any power generation environment or technology, such as combined cycle gas turbine, onshore and offshore wind, and utility scale solar.
The impact of optimization will vary across these different types of plants and asset classes, but significant savings may be achieved at a quantifiable risk threshold in all of these environments.
Preparing for Implementation
Power generators have a number of options available as they consider how best to apply risk analysis methods to their maintenance optimization projects. Certain foundational work is required, which involves developing and implementing a robust Enterprise Asset Management strategy for their organization and performing asset criticality ranking, failure modes and effects analysis (FMEA), and other tasks. It goes without saying that at the outset, asset databases, preventative maintenance procedures, costs, and all related asset data need to be upto-date, complete, and accurate in the CMMS.
By investing in these initial steps, organizations be assured that their risk analysis projects will go smoothly and efficiently. On the other hand, trying to go through a detailed risk analysis without the databases and preliminary studies having been completed will likely generate frustration and no measurable results.
Phased Approaches Bring Big Advantages
Risk analysis efforts can seem daunting when looking at an entire plant or portfolio of plants, but small wins and test cases are possible by looking at systems and subsystems on a pilot project basis. By taking a phased approach, organizations can test the methodologies, tools, and most importantly the results from a maintenance optimization. These can be evaluated and adjusted as needed before scaling up the program to include more assets under management. In the meantime, the validated results from the pilot can be implemented through changed maintenance procedures and the savings can be achieved immediately, helping to fund future work on the overall initiative.
Another important aspect of many of these analysis projects is their scalability. Many power generation plants and asset portfolios have common asset types and configurations. Once an analysis has beencompleted on the first asset type, the modified maintenance plan can be applied across the portfolio with modifications needed only where specific characteristics differ from plant to plant. This can accelerate the overall implementation and corresponding results.
Asset Performance Optimization
As the power generation industry continues to evolve with many current and near term challenges, achieving a truly optimized, risk informed view of maintenance and asset performance can yield tremendous value for proactive operators going forward.