New technologies in the power industry can introduce new, perhaps massive, maintenance costs. What to do?
As we march further into the 21st century, the power sector is undergoing a massive shift. With climate change high on the global agenda, the industry as a whole is committed to finding alternatives to conventional fossil fuels. Low-carbon power sources like wind, solar and hydro are being pursued by even the most traditional power companies.
To meet this commitment to produce a certain amount of power from renewable energies, operators must invest significant amounts of money in new technologies and new assets, which, in turn, bring a raft of other costs impacting the bottom line: Maintenance is a big one.
Consider this scenario: ACME Power is a global power generation and distribution company. It recently committed to generating 25% of its total power using renewables, and has invested $X in purchasing 250 wind turbines and siting them in an ideal, windswept location. Each turbine is capable of producing 2.3MW with a typical efficiency of 30%. The entire wind farm will contribute to 8% of the total power generation for ACME Power, which at its most efficient is 450MW. While it looks like a great investment on paper, ACME Power is concerned that maintenance—as yet an unknown entity for the new technology—will prove a costly blow.
For example, in the event that significant repairs are required to one of the massive wind turbines, the crane needed to maneuver the turbine is very hard to come by. It can take months for a crane to become available, and the costs for transport and hourly hire are huge. What is the risk of a crane not being available? Is ACME Power better off buying one outright, sharing the cost with neighboring companies or shouldering the occasional, yet very expensive, hire cost?
This is a typical scenario, and just one of the many factors that need to be considered when new technologies like wind turbines are introduced into existing operations.
New technology typically can present a host of unknowns when it comes to operations and maintenance. Even with strong support from the OEM and the provision of thorough training for the operations team, it’s still hard to quantify costs and, more important, identify ways to save on maintenance at this early stage.
RCM: Early mapping of maintenance plans
Proven reliability engineering techniques are used to plot a clear path for maintenance of new assets, and to provide management with reassurance around ongoing costs. Reliability Centered Maintenance (RCM) is one of the most beneficial techniques to use at this point. An RCM study will determine the optimal maintenance strategy for the new assets, as well as predicting the maintenance budget and spares usage over a 20-odd-year lifetime. It will also model different maintenance strategy scenarios to compare risks and improvements over this lifetime, to enable the better long-term management of the assets.
Here’s how RCM would work for the hypothetical ACME Power wind-turbine project.
First, failure data would be gathered from a variety of sources—such as work-order history, spares usage rates and interviews with the personnel responsible for maintaining the equipment. Given that ACME Power hasn’t been using wind turbines for long, the failure data may not be all that comprehensive. This shouldn’t be seen as a stumbling block.
Using this data, along with OEM maintenance manuals and spares catalogs, a preliminary RCM model is built (with the intention of fleshing out the model during facilitations with staff). During the process, technicians and engineers can have direct input into the maintenance activities that are included—which, importantly, creates a sense of ongoing ownership of the maintenance strategy.
From the facilitation process, the RCM model is validated and then optimized by assessing each failure mode by the cost, safety, environmental and operational contributions to reduce cost and risk. For example, at this point, ACME Power may identify that maintenance of the main gearbox used to power the wind turbine is problematic (given the fact that the main gearboxes cost $300,000 and the aforementioned cranes add significantly to their repair costs). It’s here that further reliability engineering techniques—like Root-Cause Analysis (RCA)—may be deemed necessary to make further improvements to the maintenance strategy.
Fig. 1. Average annual cost comparison over 20 years of the two maintenance strategies referenced in the hypothetical ACME Power example
Figure 1 shows the outcome of the RCM report for ACME Power. The first column shows what the operation’s existing strategy will cost per year; the second shows the optimized model. The latter delivers $46,000 savings annually, or close to $1 million over 20 years for each turbine.
Fig. 2. Average annual impact comparison of a failure mode over 20 years
Figure 2 shows the actual impacts of a specific failure mode where we can see that the optimized strategy has dramatically reduced the effects and costs associated with this failure mode.
An RCM study will deliver long-lasting benefits for any organization that has invested in significant new technologies. Tangible savings are generated through the reduction in unplanned downtime, the avoidance of production losses and a fall in risk-based costs. This type of study will reveal any gaps in the existing maintenance strategy, not to mention provide peace of mind that existing maintenance strategies are working.
Using the right technologies and the right facilitators, an RCM study has broader benefits for operations and maintenance teams. It can boost overall capabilities by providing training and development, and by integrating RCM software tools with other processes for continuous improvement. These tools can be used for long-term forecasting of entire fleets of assets, and to empower companies to be on the front foot when it comes to contract negotiations with OEMs for maintenance.
In short, an RCM study is a powerful technique for optimizing maintenance strategies for new and existing assets alike—and for delivering real savings in the long term. MT
This information was supplied by ARMS Reliability, a global team of consultants specializing in reliability methods.