We all know power plants are hugely expensive to build
and they face a myriad of challenges to keep them operating efficiently, but of
course that is precisely what is required if they are to deliver on investment.
The adage that time is money could be more accurately replaced by power is
money certainly for power generation assets. Every hour that a power plant is
offline can cost tens of thousands of dollars in lost revenue, so keeping the
asset operating at a high level of efficiency and keeping the power flowing is absolutely
crucial.
It is no surprise then that the power generation
sector is looking for help from digital technologies. Asset performance
management (APM) is increasingly viewed as being the essential tool for
operators of asset-intensive industries. It is interesting to note that one of
the early adopters of this technology was in fact, the power generation sector.
So, what is APM? Gartner defines it as a market of
software tools and applications designed to improve the reliability and
availability of physical assets (such as plants, systems of equipment, and
infrastructure) essential to the operation of an enterprise.
According to LNS Research, APM has moved through
three-initial generations before arriving at a solution that is now aligned to
the connected digital technologies of industry 4.0. First up there were the
traditional paper-based systems, before enterprise asset management (EAM) and
computerized maintenance management systems (CMMS) replaced the pencil and
paper approach.
The next step in the APM evolution came with the
development of computer-based tools for condition-based maintenance (CBM),
reliability-cantered maintenance (RCM) and asset strategy definition, or
classic specialized APM. Now in the age of digital twins, machine learning and
advanced analytics comes the fourth generation of APM.
For asset-heavy industries such as power plants, a
full understanding of the performance of an asset and how to maximize its
efficiency moving forward is core to profitability. It allows operators to make
informed decisions on critical plant assets based on accurate data analytics.
This knowledge is crucial and will enable operators to develop proactive
strategies for long-term asset optimization that help to reduce the costs for
operation and maintenance of power plants and to reduce spare part inventories.
Aside from the improved operational efficiency and
reduced cost of maintenance, there are further vital benefits that can be
gained; not least is the increased profitability due to improved uptime. In a
world where servitization (please feel free to look up the definition) is
increasingly the preferred business model, this can be a massive boost to
revenue.
But here are several prerequisites to allow APM to
deliver this pent-up value for power station. The first, and many would argue
the most important, is specific domain expertise. The next challenge is to unlock
the data. To enable effective data analytics all data, including any dark data
or data silos, need to be identified and delivered in a standardized format, a
unified data platform. For the system to provide valuable real-world insights,
it is imperative that a current and accurate version of the power plant is
available in digital format.
All of this must be delivered across a sector that has
different infrastructures with numerous designs that include vast volumes of
data from various high-value assets often spread over large distances. Every
industry will approach APM differently and power plants, with their unique
characteristics, are no exception. Power generation covers the entire gamut
from smaller distributed generating systems to massive coal-fired power
stations, each with individual challenges.
There are however common challenges, one of which is
the lack of redundancy in its main systems, meaning that they are under
increased pressure to ensure there is an effective maintenance strategy to ensure
uptime. Another difficulty is the sheer number of assets contained in each
power plant. For a standard combined cycle power plant it can be easily more
than 15,000, with more than 5,000 of them to be supported by APM.
Big data on its own has no value. It needs to be
collected and analyzed through a filter of domain experience to deliver
actionable insights. These generation assets create an overwhelming volume of
data and interpreting that and providing an effective condition-based
maintenance strategy is a challenge of its own. Just consider that a modern
combined cycle power plant can produce 25 million archive entries from 50,000
signals every day, yes, a single day! In order to meet that demand, we
developed Omnivise Availability. It is built to support these data streams,
delivering operational insights that improve performances. Also, it can provide
APM from single assets right through to a full fleet of power plants.
APM by Omnivise Availability will help asset managers,
reliability engineers, and maintenance managers to end the daily plague of knee
jerk reaction to problems by developing a proactive and more efficient
approach. It allows operators to manage and optimize inspections, periodic
maintenance activities and condition-based maintenance, as well as balancing
operation and maintenance efforts with reliability and inventories of spares
and consumables.
There is no hiding the fact that a digital industrial
transformation can be a daunting prospect. But by adopting proven technologies
such as APM and partnering with companies that have a wealth of experience in
asset management allied with in-depth market insights it can allow companies to
gain a significant competitive edge.
Learn more about how Siemens Asset Performance
Management works and how it supports the power plant operator in my next blog –
stay tuned!
