Offshore RCM

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Martin Meisner Fondt
Product Development & Innovation (MSc.)
Master thesis
Student ID: 303195
Supervisors:
Erik Skov Madsen (University of Southern Denmark)
Kristian Petersen (Vattenfall A/S)
ECTS: 30
Fall 2014
University of Southern Denmark
Hand in date December 18th
2014

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Acknowledgements
This thesis has been authored to earn me the title of MSc. in Product Development and
Innovation. However, there would be no thesis if not for the aid and support of the people
around me.
I would like to thank the following people for their contributions to this work:
PhD. Erik Skov Madsen for his support and supervision throughout this project. As well as
building the bridge between me and Kristian
Kristian Petersen for his friendship, support, supervision and for giving me the opportunity to
contribute to his PhD project.
All the good people of Vattenfall Nordic BU Wind Esbjerg, for quickly accepting my presence at
the office and answering my every question without reserve. I would also like to thank Mogens
Forsom for his input and assistance regarding storage and SAP information. And I would
especially like to thank Steen Bode and Ian Lauridsen for their participation in the RCM
workshop.
A special thanks to Kasper, Christiane, Mia, Søren, Rasmus, Christina, Luise, Rene, and especially
Erik. Their friendship was a constant light on the horizon.
Finally I would like to thank my family for their love and support, and Marthe who has filled my
heart with love and joy every day. You are my rock.
Martin,
Odense, December 2014

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Abstract
An important part of the total costs of offshore wind turbines is the cost connected to
operations and maintenance (O&M). O&M of offshore wind farms accounts for 25-30% of the
total cost of wind energy across the turbine’s lifecycle. In spite of this, operators do not seem to
be conducting O&M based on theory and strategy, but rather the recommendations of the
turbine supplier and general discoveries that are made during the operating lifetime of the wind
turbine.
This Master thesis uncovers the challenges a wind turbine operator is currently facing in the
implementation of a theoretically founded maintenance strategy. It is part of a PhD project
currently under development in the organization, and as such aims to assist the PhD fellow in his
continued work.
The focal point of the thesis is how a maintenance concept can be applied in the organization in
order to reduce wind turbine failure rates and downtime connected therewith. The thesis has
selected a specific concept, which has then been implemented in a small scale through the use
of a workshop with the participation of relevant stakeholders. Findings from the workshop have
been synthesized into an example of how the maintenance concept can reduce O&M spending.
The thesis has also uncovered several challenges which, if surpassed, will simplify the
implementation of a theoretically founded maintenance concept.
Keywords: Offshore wind energy, operations, maintenance, reliability centered maintenance,
maintenance concepts, organizational knowledge.

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Abbreviations
NW-G Vattenfall branch Nordic Wind – Generation
NW-GH Vattenfall branch Nordic Wind – Generation Horns Rev 1
WT Wind Turbine
O&M Operations and maintenance
RCM Reliability centered maintenance
ALCM Asset lifecycle management
LTA Logic tree analysis
HR1 Horns Rev 1
VAWT Vertical axis wind turbine
HAWT Horizontal axis wind turbine
OEM Original equipment manufacturer
PLC Product lifecycle
ROI Return on investment
CMS Condition monitoring systems
PM Preventive maintenance
CM Corrective Maintenance
OEE Overall equipment effectiveness

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Content
1 Introduction......................................................................................................... 1
1.1 Context........................................................................................................................3
1.2 Research question.......................................................................................................3
1.3 Presentation of case....................................................................................................5
2 Methodology......................................................................................................10
2.1 Section 1 – Establishing theoretical foundation. .......................................................11
2.2 Section 2 – Applying selected RCM method on Horns Rev 1......................................12
3 Literature Review ...............................................................................................13
3.1 Knowledge within a firm ...........................................................................................13
3.2 Wind turbines............................................................Fejl! Bogmærke er ikke defineret.
3.3 Operations and Maintenance....................................................................................17
3.4 Maintenance concepts ..............................................................................................26
3.5 Reliability Centered Maintenance (RCM) ..................................................................29
3.6 RCM guidelines..........................................................................................................32
4 Empirical Study part 1: Current O&M conditions at NW-GH.................................34
4.1 Front-end activities and conditions ...........................................................................34
4.2 Empirical Study part 2 – Operations at NW-GH.........................................................36
4.3 Current O&M practices at Horn Rev 1 .......................................................................37
5 Empirical Study 2 (RCM ANALYSIS)......................................................................40
5.1 Step 1 – System selection and information collection ...............................................43
5.2 Step 2 – System boundary definition.........................................................................48
5.3 Step 3 – System description and functional block diagram........................................49
5.4 Step 4 – Functional description and functional failures.............................................51
5.5 Step 5 – Failure mode and effect analysis..................................................................52
5.6 Step 6 – Logic tree analysis........................................................................................53
5.7 Step 7 – task selection...............................................................................................56
6 Discussion of RCM theory vs. empirical research performed at Vattenfall ............65
6.1 Critique of RCM .........................................................Fejl! Bogmærke er ikke defineret.
6.2 RCM workgroup setup...............................................................................................66
6.3 Suitability of guideline...............................................................................................67
Content

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7 Implications for Vattenfall.................................................................................. 69
7.1 Challenges found within Vattenfall........................................................................... 69
7.2 Data quality at NW-G................................................................................................ 70
7.3 Recommendations .................................................................................................... 72
7.4 Further iterations of the RCM analysis...................................................................... 70
8 Self-reflections on the thesis process .................................................................. 73
9 Conclusion ......................................................................................................... 74
10 References...................................................................................................... 76
11 Appendix........................................................................................................ 81
11.1 Appendix 1 – Vattenfall Organization Chart.............................................................. 81
11.2 Appendix 2 – Transcript of RCM workshop ............................................................... 83
11.3 Appendix 3 – Communique with ABB contact......................................................... 117
11.4 Appendix 4 – RCM analysis spreadsheets................................................................ 118

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Figures
Figure 1: Installation costs of offshore wind turbines. Adopted from Blanco (2009) ..................... 1
Figure 2: Research areas of Kristian Petersen's PhD project........................................................... 6
Figure 3: Proposed general model of empirical research in operations management. Adopted
from Westbrook (1995). ................................................................................................................ 10
Figure 4: Evolved model of action research in operations management, adopted from Westbrook
(1995)............................................................................................................................................. 11
Figure 5: Components of a wind turbine, adopted from Pinar Pérez et al. (2013) ....................... 16
Figure 6. Geared generator concept adapted from Arabian-Hoseynabadi et al. (2010)............... 17
Figure 7: System reliability as a function of average element reliability and number of elements
in system. Adopted from (Smith & Hinchcliffe 2004).................................................................... 17
Figure 8: Bathtub curve patterns adopted from ABS (2004)......................................................... 20
Figure 9: Planned maintenance failure rate pattern, adopted from ABS (2004) .......................... 22
Figure 10: A P-F curve depicting the deterioration of a gearbox (Petersen et al. 2014; Petersen et
al. 2013; Moubray 1997)................................................................................................................ 23
Figure 11: Event tree for offshore repair decision making............................................................ 25
Figure 12: Break-down model of a Vestas V80 2MW wind turbine .............................................. 43
Figure 13: Failure distribution of HR1 systems.............................................................................. 44
Figure 14: Estimated loss of production for the electrical system ................................................ 46
Figure 15: Schematic of the main electrical electrical system of a Vestas V80 2.0MW WT
collected in Step 1 of the RCM analysis......................................................................................... 48
Figure 16: Functional block diagram developed prior to workshop.............................................. 50
Figure 17: Corrected functional block diagram ............................................................................. 50
Figure 18: Logic tree analysis for step 6 adopted from Smith & Hinchcliffe (2004)...................... 54
Figure 19: Step 7 decision tree. Adopted from Smith & Hinchcliffe (2004) .................................. 56
Figure 20: Probability of single, double, and triple failure on same Q8 circuit breaker over the
years............................................................................................................................................... 61
Figure 21: The relationship between thesis research, core action research, and thesis writing.
Adopted from Zuber-Skerritt & Perry (2002)................................................................................. 73

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Tables
Table 1: Description of maintenance concepts generations, adapted from Pintelon & Parodi-Herz
(2008) .............................................................................................................................................27
Table 2: Grouping of maintenance activities at HR1......................................................................37
Table 3: Annual number of Q8 replacements according to storage data......................................43
Table 4: Outtake of SCADA alarm codes for HR1 ...........................................................................45
Table 5: List of the functions and functional failures of the electrical system...............................51
Table 6: Estimated cost savings for Q8 design modification..........................................................59
Table 7: Results of Weibull Analysis...............................................................................................60
Table 8: Estimated cost of failure and restoration.........................................................................62
Table 9: Annual costs for restoration intervals ..............................................................................62
Table 10: Cost benefits of TD-maintenance task on the Q8 circuit breaker. Spare part investment
accounted for. ................................................................................................................................64
Table 11: Example of SAP work orders for failure correction of the Q8 circuit breaker................70

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1 Introduction
Since the first global oil crisis in 1973 interest in renewable energy has been increasing (Lund
2007). Since the 1990’s, with the signing of the Kyoto Protocol, where countries agreed on
collective reductions in greenhouse gas emissions, global climate debate has expresses a need
for a change from reliance on fossil fuels towards renewable energy (Pinar Pérez et al. 2013).In
2007 the European Union published “Renewable Energy Road Map. Renewable Energies in the
21st
century: building a more sustainable future”. In the publication the Commission put forth a
suggestion of setting a mandatory 20% target for renewable energy’s share of total electricity
production in the EU by 2020 of which, wind energy should supply 14% (EU Commission 2007).
Renewable resources are defined as resources which are replaced by natural processes faster
than the consumption of humans; sources of renewable energy are e.g. wind energy, solar
energy, and geothermal energy. The wind power industry has reacted to the EU commission’s
proposal and in 2013, wind power’s market share in the EU was 8% of all energy produced
(EWEA 2013).
Much of this can be attributed to the development and installation of larger and more effective
wind turbines, from 500kW in the late 1990’s to the 8MW currently available. However, with the
design of larger and more effective turbines, price and size have also gone up. Another, less
positive, development has been that larger turbines tend to have a higher failure rate .This may
be due to the fact that larger turbines have more
components, and as many turbine parts are
subject to a constant or slightly increasing failure
rate, the number of failures per turbine also
increases. Larger turbines also mean higher
maintenance costs as well as higher loss of
production whenever the turbines face
downtime, increasing the cost of operations and
maintenance (O&M) activities for the operators.
(Spinato et al. 2009)
Figure 1: Installation costs of offshore wind turbines.
Adopted from Blanco (2009)

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In September 2014, in an attempt to make wind energy more appealing to investors, Dong
Energy A/S declared a goal of lowering the cost of wind energy by 40% per installed MW by
2020. In October 2014 Vattenfall’s CEO Magnus Hall followed suit in this goal; stating that
Vattenfall’s goal was to either match Dong Energy or be better (Bindslev 2014).
The total cost of a wind farm can be separated into four sections; Planning, installation,
operations and maintenance, and decommissioning. Planning, installation, and decommissioning
costs account for approximately 70% of the total lifecycle costs whilst O&M account for the
remaining 30% (Blanco 2009), the installation costs of offshore wind turbines is shown in
Figure 1.
Vattenfall is a provider of electrical energy based in Sweden. The company is divided into two,
Nordic and Continental/UK, and each has several business units each accounting for each their
type of production e.g. Heat, Hydro, and Renewables. Energy derived from wind power accounts
for approximately 2.5% of Vattenfall’s annual production, using wind turbines both on- and
offshore. All turbines are monitored from Vattenfall’s control center in Esbjerg; one of these
farms is Horns Rev 1. Horns Rev 1 is an offshore wind farm, and was at its time of completion in
2002 the world’s biggest wind farm with a production capacity of 160MW. The farm uses 80
Vestas V80-2.0 MW turbines located approximately 7.5 nautical miles west of Blåvandshug. The
farm annually produces about 600 GWh equal to 2% of annual Danish consumption or that of
150.000 Danish households(Vattenfall & Dong Energy 2014).
Currently, with both prices on fossil fuels and resistance against nuclear energy and CO2
emissions connected with fossil fuel consumption, many governmental agencies are looking
towards other sources for energy. This search, combined with an international increase in
environmental awareness, has resulted in a higher global demand for wind energy (Jennings
2009). With space and efficiency being in demand onshore, the installation of offshore wind
farms is becoming increasingly popular (Petersen et al. 2013). However, by moving the
installations offshore, utility companies, such as Vattenfall, are experiencing an increase in costs
in both installation, operation, and maintenance of the turbines (Petersen et al. 2014). As the
technology is still new, no major offshore wind farms have yet been de-commissioned. However,
it can be expected that these costs are also higher than with on-shore wind farms.

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1.1 Context
Vattenfall is the operator of their wind farms, and O&M is an area where there is a significant
potential in terms of cost reduction. In an attempt to minimize O&M costs of the wind farm
Horns Rev 1, Vattenfall has initiated a project which seeks to determine how the methods
modularization, reliability centered maintenance (RCM), and asset lifecycle management (ALCM)
can be used to formulate an optimal O&M strategy. The overall project is conducted by Kristian
Petersen, an Industry PhD student, and the objective of this thesis is to assist with the RCM
section of the project by performing a pilot-study on how RCM can be applied on a Vattenfall
wind turbine. RCM is a maintenance methodology originally created for the aviation industry,
specifically for the Boing 747, and has since become the industry standard within aviation(Smith
& Hinchcliffe 2004). By selecting relevant systems within a wind turbine, analyzing this using an
RCM methodology, and using the RCM results to formulate improvement suggestions for the
next iteration of the RCM study.
1.2 Research question
As O&M accounts for up to 30% of the total cost of an offshore wind turbine farm (Blanco 2009),
it is important to have an effective O&M strategy. However, this is often not the case and as
stated by Andrawus (2008)
“owing to the current maintenance practices and failure characteristics of wind turbines,
there exists a need to determine an appropriate maintenance strategy that will effectively reduce
the total LCC of wind turbines and maximize the return on capital investment in wind farms”
(Andrawus 2008)
Many operators build their O&M strategies based on recommendations from the Original
Equipment Manufacturer (OEM) with improvements are being made ad hoc as experience on
each turbine is assimilated by the personnel involved in the O&M activities (Vattenfall 2014). At
the same time, the majority of O&M spending is caused by corrective maintenance of failures;
which can be dangerous as failures can affect other systems than the failing one leading to
increased wear to the overall equipment. As spare parts for wind turbines can be quite large,
spare part storage is also a significant cost to the operator, and in cases where spare parts are
not available, both downtime and costs are higher than if failures are avoided, or planned for to
a higher degree. As the offshore wind industry can still be considered immature (Petersen et al.
2014), there currently does not exist a suitable template for the creation of O&M strategies,

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thus many advances and improvements in offshore O&M strategies are based on experimental
test projects (Vattenfall 2014).
Another issue identified within the industry, is that generally data concerning wind turbines have
been found lacking in quality, e.g. Petersen et al.( 2014) was not able to utilize any of the data
from prior to 2010 as the general structure of the data was too poor to analyze. Within
Vattenfall, the data collection method has also varied over the years due to varying IT systems,
resulting in data that is difficult to compare because the level of detail has been insufficient in
the early years of HR1. Therefore it has been decided to use the qualitative method Reliability
Centered Maintenance. RCM is a step-based method which selects and analyses equipment in
order to move maintenance activities from a reactive mindset to a proactive mindset. Whilst
RCM to an extent relies on historical data for its initial steps, the later analysis relies more on
including the knowledge and experience of people to formulate maintenance strategies, which
will be discussed further later in the thesis.
The aforementioned aim of this project can be reformulated into the following research
question:
How can failure rates and related downtime be reduced in the offshore wind farm Horns Rev 1
by the use of the RCM maintenance concept?
1.2.1 Delimitations & explorative questions
In order to reduce scope, and reduce the project to a more manageable scale the project will be
bounded by the following delimitations.
The research question is subject to the following delimitations:
1. The RCM analysis will focus on Horns Rev 1
2. The RCM analysis will only be done on selected systems/subsystems
3. The data used for system selection will be that already existing within Vattenfall and
only data concerning Horns Rev 1 and its Vestas V80 2.0MW turbines, no other sites or
turbines will be used in the selection process.
4. It is also important to keep in mind that this project serves as a first attempt of applying
RCM in Vattenfall and it is part of a much larger project; the consequences and impacts
of this will be explained further in the methodology chapter.

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Exploring questions:
5. How is O&M currently being carried out at Horns Rev 1?
6. What are the boundaries between systems, subsystems, and components?
7. On which level of assembly should the RCM analysis be carried out?
8. Which challenges is Vattenfall facing in regards to the implementation of and RCM-
based maintenance strategy?
1.3 Presentation of case
1.3.1 Vattenfall A/S
As previously mentioned, Vattenfall is a Swedish utility company owned by the Swedish
government. The company is divided in two branches; Nordic and Continental/UK. The Nordic
branch consists of 5 departments and 7 business units (BU), one of these being BU Wind.
Vattenfall’s office in Esbjerg is a part of BU Wind, generally named Nordic Wind – Generation,
and identified by the code NW-G, which basically means Nordic Wind - Generation. NW-G is
home to five branches, one of these being Offshore Horns Rev (NW-GH), which is managed by
the site manager of Horns Rev 1, Steen Bode. (See Appendix 1 for further details.)
The Vattenfall office in Esbjerg serves several functions. It is the home of Vattenfall’s wind
turbine (WT) surveillance center from where all WTs owned by Vattenfall, a little over 1000, is
being monitored, the surveillance center it part of the Vattenfall Continental/UK Renewables
business unit.
Kristian Petersen, PhD fellow at Vattenfall, works out of the NW-G office. The goal of his
research is to strengthen the BU Wind organization by moving the basis of the NW-G O&M
strategy to being, in a much higher degree, based on explicit theory, rather than the tacit
knowledge possessed by Vattenfall’s employees. He is researching how three methods,
modularization, reliability centered maintenance (RCM), and asset lifecycle management
(ALCM), can be applied and strengthen three organizational levels, operational, tactical, and
strategic, within NW-G as shown in Figure 2.

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Figure 2: Research areas of Kristian Petersen's PhD project curtesy of Kristian Petersen
On the short-term operational level the PhD project seeks to explore how modularization, or
grouping, of tasks can reduce time spent on service operations of the WTs in Horns Rev 1. Whilst
the effects may be small on the individual level of each service visit, the research may lead to
high cost reductions in the grand scheme, improving upon the profitability of the wind farm. On
a medium-term tactical level, the project seeks to explore how RCM can be used effectively to
reduce failure rates and improve upon the availability and subsequent production capabilities of
the wind farm. Whilst on the long-term strategic level, the PhD project seeks to uncover
previously hidden possibilities by using ALCM to analyze the lifetime impacts of a wind farm’s
from five different perspectives; technical, economical, commercial, compliance, and
organizational.
As mentioned, this master thesis works with the initial steps of the RCM analysis, working with
an action research methodology to perform the first iteration of action research theory building
on how RCM can be applied to a wind farm.

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1.3.2 Contact area within Vattenfall
Within Vattenfall the direct contact person has been Kristian Petersen, PhD fellow. He is
positioned outside the regular NW-G branches, answering directly to Bent Johansen, Head of
Generation (NW-G). Kristian’s focal area is Horns Rev 1, which means he works closely with
Steen Bode, Site Manager of HR1. Apart from Kristian, Steen, and Bent, access to the
organization and the people in it has been gained through placement in the organization twice a
week.
1.3.3 Data available
Through Kristian Petersen, the author of this thesis has access to the following data sources:
SCADA
For turbine failure data the project will utilize internal Vattenfall data, specifically data which has
been documented in SCADA. In 2011 NW-G updated its SAP system which meant changes to the
documentation process and due to differences in documentation method as well as data quality,
the project will focus of data gathered after 2011.
SCADA is an abbreviation for Supervisory Control And Data Acquisition, it is an industrial control
system which controls and monitors industrial processes which exist physically, i.e. it monitors
and controls equipment and not software processes. SCADA is used by Vattenfall to monitor
their WTs both offshore and onshore. It continually monitors the equipment and whenever
performance varies beyond a specific threshold, an alarm goes off. E.g. when turbines pitch the
blades to optimize for the wind conditions, the turbines controller calculates the blades degree
of pitch, when the calculated pitch defers too much from the actual pitch, an alarm, classified by
an error code (in this case error code 74), goes off and the turbine is stopped automatically. It is
then up to the surveillance personnel to evaluate whether or not to attempt a remote restart of
the turbine, or if technicians have to be dispatched to inspect the turbine manually. The turbines
at HR1 have more than 800 error codes defined, and annually more than 5000 alarms,
concerning HR1 alone, are handled by the Vattenfall surveillance center in Esbjerg.
SAP
All turbine related work within the organization is registered in SAP through the use of work
orders. These work orders are classified depending on the type of work. Generally three types
are identified; Turbine service orders, failure correction orders, and project orders.

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Service work orders:
As the name implies, service work orders are directly linked to all operations related to the
carrying out of turbine service. Generally NW-GH performs service on a turbine twice a year, a
small service visit requiring four technicians for one day, and a larger service visit, requiring four
technicians for two days.
Failure correction work orders:
Failure work orders are initiated by SCADA alarms which cannot be resolved remotely and
therefore require the presence of a technician in the turbine, an example of failure correction
will be given in chapter 0. Currently, work orders are classified by an issue date, a notification
description i.e. which alarm code was sent by the turbine controller to the surveillance center,
the functional location i.e. which turbine requires the technician. Technicians going to the
turbine will then perform inspections based on the notification description, upon returning to
shore, the technician will document damage type i.e. electrical or mechanical, a damage code
and description, and the code and description of which activities which were performed at the
site. They then have the possibility to briefly describe the activity, 2 or 3 words, and add an
additional, longer, description of secondary activities performed such as testing of boundary
components or systems.
The changes in 2011 to the SCADA system, also affected the formulation of the SAP work orders,
allowing for the alarm code which initiated the failure correction, along with its title, to be
included in the work order, prior to this change only the alarm code title was included and the
formulation, and subsequently the quality of this, depended on the issuing surveillance
technician. This means that work orders issued prior to 2011 greatly vary in quality, making
analysis of this data much more difficult.
Project work orders:
Project work orders are work orders related to visits made to the turbines for reasons other than
performing service or correcting failures. An example could be inspection for research purposes
or the installation of either turbine upgrades or additional monitoring systems.

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1.3.4 Information in the organization
Much of the information available in NW-G is kept within the individuals of the organization.
Through his familiarity with the organization Kristian Petersen generally knew who to ask
whenever a question arose that was not readily available through either SCADA or SAP. Typically
this was information regarding costs and operational practices.
A lot of information has been gained through the placement within the organization. The NW-G
office in Esbjerg is one of three NW-G offices in Denmark, with the others in Fredericia and
Copenhagen, an NW-G also has a few offices in Sweden. This means that the functions, and thus
many knowledge resources, are spread throughout northern Europe, and as a result of this,
many meetings and workshops are conducted with one or more people participating through
video-conference means.
1.3.5 Horns Rev 1
This thesis focuses its efforts on the offshore wind farm Horns Rev 1 (HR1). The construction of
HR1 began in February 2002 and began commissioned production in December the same year.
HR1 is owned by Vattenfall (60%) and DONG Energy (40%), and it is operated entirely by
Vattenfall.
The wind farm was commissioned with 80 Vestas V80 2.0MW turbines, laid out in an 8 x 10
layout. They are geared turbines, having a three-stage gear with two planetary stages and one
helical stage, with a doubly fed induction generator. Production of electricity starts at winds
speeds of 4m/s, they reach maximum production capacity at 16m/s and cut out at 25m/s. The
wind farm operates with a capacity factor of about 50% , more than double of the average
European wind farm (Boccard 2009), making HR1 an excellent wind farm in terms of production
capabilities. (LORC 2014)
In 2013, HR1 experienced two fires in a turbine, both causing catastrophic damage to the
turbines. The first turbine was replaced with a second-hand onshore turbine of the same type,
which was refitted for offshore use and installed in HR1. Shortly after the installation, the
generator broke down, resulting in the need to use a crane vessel for repairs, adding significantly
to the cost of the turbine. Due to various factors, the replacement turbine did not come with
blades. Luck would that NW-GH had had three spare blades in storage since the commissioning
of the wind farm, and these blades were installed in the replacement turbine. It was then

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decided to not keep major spare parts such as blades on hand in storage, as that came at a
considerable cost. Shortly after the replacement turbine was installed, a blade broke on a
different turbine. After the second fire, the experiences with the first showed that the business
case for acquiring a replacement turbine was very weak; this prompted the overall decision that
turbines suffering catastrophic damage would no longer be replaced, as there was no business
case to support it. This means that the current number of turbines in HR1 is 79.
2 Methodology
The overall process of this project has followed the model of empirical research in operations
management depicted in Figure 3 (Westbrook 1995; Flynn et al. 1990). The actions performed to
answer the research question and which produced the results can be divided into two sections.
The first section was aimed at familiarizing the author with the terminology of operations and
maintenance (O&M) in relations to the WT industry, and selecting a RCM guideline to apply on
the offshore WTs at Horns Rev 1, represented by the first three blocks in Figure 3. The second
section will consisted of an implementation of the selected guideline which has provided data
that was to be analyzed in an attempt to determine how RCM can be used within Vattenfall,
which challenges exist as well as how to set up the project in terms of analysis group
configuration and work method.
Figure 3: Proposed general model of empirical research in operations management. Adopted from Westbrook
(1995).
The findings will be presented to the two co-projects working with RCM on WTs within
Vattenfall, and integrated into their continued work. As the author of this thesis is directly
involved with the development of an RCM program, this thesis used an action research
approach. Action research is similar to case studies. However, it differs from case studies by
being characterized as focusing on research in action rather than research about action. What
this means is that the researcher assumes a more active role, shaping and creating the results
rather than deducting them from inquiries e.g. interviews, observations, etc. (Westbrook 1995;

11
Coughlan & Coghlan 2002). Zuber-Skerritt and Perry (2002) state that, whilst action research is
an iterative process, a master thesis project need only to progress through one execution of the
action research/theory building steps shown in Figure 4.
What is interesting about the Vattenfall case is the coincidental occurrence of another wind farm
RCM project under development in a different branch of the Vattenfall Corporation; the
Vattenfall UK/Continental Renewables business unit in the Netherlands is currently in the initial
phases of an RCM centered master thesis project which is set to commence field work in
February 2015. With learning being shared between projects, the learning of how an application
of RCM to Vattenfall’s WTs can be explained through Westbrook's (1995) model of action
research in operations management, shown in Figure 4, with iterations being conducted by each
new project group.
Figure 4: Evolved model of action research in operations management, adopted from Westbrook (1995)
2.1 Section 1 – Establishing theoretical foundation.
As the PDI course has limited teachings on the topics of operation and maintenance, there was a
need to assimilate knowledge on the topic. In addition to that there also was a need to
understand the WT industry. The project started out with a comprehensive assimilation of
secondary data, through the use of a literature review on the following topics:
1. Knowledge in an organization
2. Operations and maintenance (O&M)
3. History and past tendencies of O&M
4. Offshore WTs
5. O&M of WTs

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6. Challenges of O&M of offshore WTs
7. Examples of how RCM has used to handle similar challenges in other industries
8. Reliability Centered Maintenance (RCM)
9. RCM in the WT industry
The literature reviewed featured a mix of journal papers, conference papers, books,
dissertations and theses published in modern history.
To gain insight into the Vattenfall organization, its employees, working conditions, and corporate
culture an average of two days per week was spent in the company throughout the entire
project. This allowed for a more dynamic research process. However, it also resulted in a
complete lack of necessity to conduct interviews, as whenever a question emerged during the
project, competent resources which could answer the questions were consistently available.
To gain knowledge and insight regarding the conditions related to maintenance of the Horns Rev
1 turbines, a visit to a test turbine was conducted. The turbine is located in Tjæreborg close to
Esbjerg, and is an exact replica of the turbines placed offshore at Horns Rev 1.
2.2 Section 2 – Applying selected RCM method on Horns Rev 1
The research method applied in the second section of this project was action research in which
the researcher acts as both a research scientist and an agent of change (Westbrook 1995;
Coughlan & Coghlan 2002). The aim of this section was to generate sufficient primary data to
enable the researcher to formulate design recommendations which enables Vattenfall’s PhD
fellow to continue the iterative process of action research by applying a better and broader RCM
analysis on the wind farm Horns Rev 1.
Applying the selected RCM method to Horns Rev 1 will serve as a one-off action research study
with analysis being performed on multiple levels of the organization in an attempt to create
improvement recommendations across the NW-G organization (Eisenhardt 2007). Due to the
immaturity of the offshore wind sector (Petersen et al. 2014), it is assumed that O&M processes
are highly similar between the various functional locations in the organization, and lessons
learned from applying the method on a single wind farm can be transferred to other sites.

13
3 Literature Review
This chapter will serve as an overview of the literature which has been reviewed to create a
theoretical foundation for the project. The subjects described in the chapter are outlined in
chapter 2.1
3.1 Knowledge within a firm
Knowledge can be split into two categories; explicit and tacit knowledge. Explicit knowledge can
be formally and systematically stored, articulated, and disseminated in various forms, e.g.
manuals and computer files, whilst tacit knowledge is derived from actions, experiences,
thoughts, and involvement of the person possessing the knowledge. (Chen et al. 2011)
Kogut & Zander (2008) argue that the capabilities of the firm rests in the organizational
principles which structure relationships between the individuals, within and between the
groups, and among adjacent the organizations of said firm. They put forth the notion that
knowledge within a company can be categorized as being either information or know-how. They
analyzed the two categorizations in terms of both codifiability and complexity, where
codifiability refers to ability of the firm to structure knowledge into easily communicated sets of
rules and relationships, and complexity refers to the ease with which this can be achieved; a
general parameter of measurement is that increases in complexity measures out as increases in
costs.
(Bock et al. 2005) tested the relationship between motivational factors and intention to share
knowledge. The article is quite interesting in relation to this thesis, as Hypothesis 9 examines the
relationship between the organizational climate and intention to share knowledge and found:
“The greater the extent to which the organizational climate is perceived be characterized by
fairness, innovativeness and affiliation, the greater the intention to share knowledge will be”
(Bock et al. 2005)
(Hansen 1999) examines the relationship between tie strength, transfer complexity, and search
benefits in knowledge sharing across organizational sub-units. It found that strong ties between
members are important in cases where knowledge is tacit, but in cases where knowledge is
codified, ties matter less, and the benefits of searching outside the unit in search of “new”
knowledge can often be higher. Hansen (1999) attributes this to, as ties are built within a unit,

14
codified knowledge tend to be exchanged increasing the pool of “common knowledge” within
the unit.
3.2 Wind Turbines
This chapter shortly introduce to reader to the history of wind power, as well as the current
construction and production processes of modern day WTs.
Proof that humanity has been harnessing wind for mechanical energy dates back to year 644
A.D. Early use of wind energy was tasks that were otherwise hard, such as milling grain. Through
the years windmills developed, grew in size, power, and number, and by the middle of the 19th
century the estimated number of windmills in Europe was approximately 200.000 (Hau 2013),
with uses such as milling of grain and powering water pumps. The first electricity generating WT
was developed in the 1880s by Paul La Cour, a Danish professor. The turbines used a “dynamo”
to create a DC current, which was used for electrolysis, and the hydrogen produced there was
used to power gas lamps at La Cours’ school in Askov. The success spread, and by the end of the
First World War, there were about 120 WTs in operation. Interest in wind power declined after
the First World War as fuel prices also fell. Interest was re-kindled with the start of the Second
World War. The turbines typically functioned in small grids in connection with a buffer-battery
and a fuel generator, generating DC, which still was the typical setting of rural Denmark.
The concept of harnessing wind for generating electricity had also caught the eye of German
engineers and in the 1930s there was a lot of activity in the theoretical and design fields. The
engineers designed giant turbines with 130m rotor diameter, three or four blades, 10.000 kW
rated power, and a direct-drive generator, highly similar to contemporary offshore turbine
design. However, the production of these turbines was prevented by the outbreak of the Second
World War.
Whilst at the beginning of the 20th
century there were many different design types for wind
energy converters all were based on the two principles of either using a vertical axis of rotation
(VAWT) or a horizontal axis of rotation (HAWT), research programs focused on both. However,
the use of VAWT design for large-scale production was discontinued after the Canadian Éole
project in 1985 showed that such a design could not compete economically with HAWT designs.
As a result all modern day designs use a HAWT where overall design differentiations center on
whether the turbine uses a direct-drive or a geared generator concept. (ibid)

15
Polinder et al. (2006) compares five types of generator concepts;
1. Direct-drive electrically-excited synchronous generator (DDSM),
2. Direct-drive permanent-magnet synchronous generator (DDPM),
3. Permanent-magnet synchronous generator with single-stage gearbox (GPM),
4. Doubly-fed induction generator with single-stage gearbox (GDFIG)
5. Doubly-fed induction generator with three-stage gearbox (DFIG)
The article concludes that the DDPM generator seems to be the optimal solution as the
production yield is a few percent higher than that of the other four designs, and the DDPM has
fewer mechanical parts which should result in less wear, and as a result less downtime.
(Arabian-Hoseynabadi et al. 2010) compares differences between direct-drive and geared
generators using reliability as a measure which was modelled using Markov modelling. The study
concludes that whilst the data is insufficient to make a definite conclusion, availability and
downtime of both design types appear to be equal. However the study does not take into
account the costs connected to the repairs, these costs increase considerable should a failure
require special vessels and cranes for repairs, and therefore whilst production yield from the two
turbine types may be equal, O&M spending can differentiate making one of the designs more
appealing than the other. Spinato et al. (2009) conducted a similar study and concluded that
geared turbines is a mature technology, and therefore significant advances in reliability
improvement of this type of turbine is unlikely, whereas, whilst direct-drive WTs in their study
has higher failure rates, the failures are typically in individual repairable electrical components
and the elimination of the gearbox could result in lower downtime, compared with geared WTs,
as the need for requisition of special resources e.g. crane vessels and major spare parts which
may be subject to high lead times, is significantly lower.

16
The overall construction of a WT can, as shown on the left side of Figure 5, be divided into three
main sections:
1. Rotor
2. Nacelle
3. Support structure (tower and foundation)
The various systems in a WT are shown on the right side of Figure 5. The rotor consists of three
blades (3) mounted on a blade bearing which in turn is mounted on the hub. The angle of each
rotor blade is controlled by a pitch system (6) mounted on the blade bearing. The rotor is
mounted on the nacelles (5) main bearing (8). The rotations of the rotor is transferred to the
gearbox (10) through a low speed shaft (9), from the gearbox, a high speed shaft (12) enters the
generator (13) where power is produced, the power is converted in the converter (15) to a rate
and frequency matching that of the grid the turbine is connected to. The base (16) of the nacelle
is mounted on the tower (2), and a yaw system (14) ensures that the nacelle is always positioned
upwind.
Figure 5: Components of a wind turbine, adopted from Pinar Pérez et al. (2013)

17
In general, a turbine’s processes to transform wind to electrical energy can be explained through
Figure 6. The yaw positions the nacelle upwind, whilst the pitch controls the angle of the blades
ensuring optimal utilization of the wind. When the blades rotate, the relatively slow rotations of
are converted to high-speed rotation in the gearbox, the high speed rotations are used for
power generation in the generator, and the converter converts power generated to a level
which is suitable for transmission to the substation. (Arabian-Hoseynabadi et al. 2010)
A Vestas V80-2.0MW turbine consists of more than seven easily separable working systems each
with several sub-systems. However, in an effort to reduce weight, cost, and size of the turbine,
there are no redundant systems per se. The lack of redundant systems means that every failure
within key systems will result in a lack of
performance of the turbine. Smith &
Hinchcliffe’s (2004) model, shown in Figure 7,
shows how the reliability of a system is highly
dependent on the average reliability of the
elements within that system as well as the
number of elements within the system. It is
important to remember that whilst there are
no redundant systems, many of the support
structures have been over-dimensioned, both
in mass and number in order to reduce stress
and strain of individual components. This
means that the average element reliability is
very high, and ultimately most errors are the
result of uneven wear, faulty production, or
human error. (Smith & Hinchcliffe 2004)
Figure 6: Geared generator concept adapted from Arabian-Hoseynabadi et al. (2010)
Figure 7: System reliability as a function
of average element reliability and
number of elements in system. Adopted
from Smith & Hinchcliffe (2004)

18
3.3 Operations and Maintenance
This chapter provides a theoretical background to the operations and maintenance (O&M)
terminology used in the thesis. The chapter first introduces the basic terminology that will be
used in relation to O&M, and then moves into a more in-depth definition of O&M methodologies.
The last section will introduce the challenges related to O&M of offshore WTs. It should be noted
that definitions and abbreviations found in literature tend to vary from author to author.
However, in this thesis, an emphasis has been put on the definitions found in literature dedicated
solely to RCM as it seemed very consistent, whilst the definitions and abbreviations found in
general maintenance literature has been converted to that of RCM literature.
3.3.1 Terminology
This chapter will utilize the following definitions of the terms commonly used in O&M, adopted
from (IEEE 2000)
 Reliability: The ability of an item to perform a required function under stated conditions
for a stated period of time.
 Failure: The termination of the ability of an item to perform a required function.
 Maintenance: The combination of all technical and corresponding administrative actions
intended to retain an item in, or restore it to a state in which it can perform its required
function.
 Component: A piece of electrical or mechanical equipment viewed as an entity for the
purposes of design, operation, and reporting.
 System: A collection of interacting, interrelated, or interdependent elements forming a
collective, functioning entity.
3.3.2 General maintenance
Manufacturing companies rely on the development and manufacturing of sellable goods. To do
this, corporations use equipment. The equipment used is subject to a Product Lifecycle (PLC).
Generically one can divide a PLC into three sections; design and manufacturing by the original
equipment manufacturer (OEM), use by the buyer, and decommissioning. Operations and
Maintenance (O&M) accounts for a range of activities intended to retain or restore equipment
to a specific state in which it can satisfactory perform its functions. i.e. O&M activities aim to
maximize the return on investment (ROI) on equipment by keeping the availability rate as high

19
as possible. However, equipment is subject to systems failure causing downtime, maintenance
activities aim to reduce downtime as much as possible by correcting or preventing failures that
occur and restore the reliability and performance of the specific equipment item. (Smith &
Hinchcliffe 2004; ABS 2004)
ABS (2004) state that failures can be caused by a variety of factors such as:
1) Design Error
2) Faulty material
3) Improper fabrication and construction
4) Improper operation
5) Inadequate maintenance
6) Maintenance errors
Causes for factors 1-3 are located with the OEM whilst factors 4-6 are dependent on the skill and
management of O&M activities. A system can have several failure modes, i.e. different ways the
equipment can fail, with several failure effects i.e. consequences resulting from a failure mode.
Equipment failure can be modelled using statistical distribution and from the failure distribution
it is possible to determine the mean time to failure (MTTF), another useful measurement
derived from the failure distribution is the conditional failure rate (λ). λ as a function of time
(λ(t)) enables the illustration of failure patterns, shown in Figure 8. (Nowlan & Heap 1978) was
one of the first to depict the failure rate patterns, which are predominantly remembered as “the
bathtub curve”. The bathtub curve depicts the three scenarios related to a product’s lifecycle. In
the early stages of the PLC, the product has a high infant failure rate; design and manufacturing
errors that were not discovered during development tests can be a cause of these failures. As
the design and manufacturing errors are resolved, the failure rate decreases until it reaches a
point where failures are relatively random, and the failure rate is considered constant. As the
product reaches the end of its PLC it enters a wear-out zone in which the failure rate starts to
increase exponentially. It is interesting to note that whilst bathtub curve is the recognized name,
the actual pattern account for only a small portion of failures. In fact failure A-C account for 11%
of failures of systems, whilst D-F account for 89%. (Nowlan & Heap 1978)

20
Until the late 1970s corporate strategies tended to prioritize product development and
manufacturing engineering whilst O&M took a back-seat. However, in later years corporations
have acknowledged that although design and manufacturing is what generates income, O&M is
one of the prime costs meaning that all inefficiencies directly affects profit potential. The
realization has brought a shift in corporate strategies elevating priority on O&M to a level
equaling that of development and manufacturing. (Smith & Hinchcliffe 2004)
Maintenance actions can be divided into two categories corrective maintenance (CM) and
preventive maintenance (PM). Each specific maintenance action is directed by a maintenance
policy which consists of a rule, or a set of rules, that describe the triggering mechanism for a
maintenance action, i.e. what state is the equipment in, and what should be done about it.
These maintenance policies are in turn informed by maintenance concepts which are general
decision structures that devise the foundational rules upon which the maintenance policies are
built. (Pintelon & Parodi-Herz 2008)
CM activities are informed by a failure-based maintenance (FBM) policy. These occur after
equipment has suffered system(s) failure, often causing downtime, and often in cases where the
organization has had no warning of the failure, and is thus reactive meaning corrective
Figure 8: Bathtub curve patterns adopted from ABS (2004)

21
maintenance relies heavily of the availability of technicians, transport equipment, spare parts, as
well as other conditions that can be hard to always have at hand, which in turn means that CM
often comes with a considerable cost. In spite of the higher cost of corrective maintenance,
many production facilities have historically operated from a strictly reactive position, taking
pride in the speed with which they were able to restore system failures, without realizing that
they had the highest cost per unit amongst their peers (Smith & Hinchcliffe 2004). However, CM
can sometimes be an appropriate solution in cases where the equipment is subject to a constant
failure rate and/or low breakdown costs (Pintelon & Parodi-Herz 2008).
PM focuses on the prevention of failures. PM activities accept a smaller duration of downtime
upfront in order to restore equipment prior to a failure which will cause higher downtime with
both increased costs and increased loss of productivity. There are different kinds of PM:
Time Directed Maintenance (TD): TD tasks are performed at specific intervals regardless of the
systems condition, this type of maintenance is often connected with systems where no condition
monitoring task is applied. A variation of TD tasks is use based maintenance (UBM) which
assumes that the failure is predictable, and sets a maintenance interval dependent on use, e.g.
1000 working hours. (Pintelon & Parodi-Herz 2008)
Remembering the failure rate patterns, notice that patterns D-F does not have distinctive wear-
out zone, meaning there is no defining point to monitor or plan for, and systems and
components displaying these failure patterns do not benefit from preventive maintenance and
should be run-to-failure. Although pattern C doesn’t have a wear-out zone either, the risk of
failure continually increases and therefore at some point reaches a level where PM is necessary
to avoid failures. The PM will then restore function to an earlier point in the failure rate pattern.
The timing of the planned maintenance is highly dependant on the severity of a potential failure,
as well as the stadard deviation of the MTTF, if a failure would result in severe safety or
environmental effects, or the effect poses a high risk to the system, then the tasks are planned
well ahead of MTTF. If the effects are less severe, or MTTF has a low standard deviation, planned
maintenance tasks can be put closer to the MTTF for economic efficiency. Examples of systems
receiving TD maintenance in WTs are: Hydraulic system, grease system, and the gearbox. (Smith
& Hinchcliffe 2004; Nowlan & Heap 1978; ABS 2004; Fischer et al. 2011)

22
For TD tasks where no good statistical data is available for determining the task interval,
(Nowlan & Heap 1978) and (Smith & Hinchcliffe 2004) suggest the use of age exploration. Age
exploration as a technique is purely empirical; it works in the way that the initial maintenance
interval changes depending on the condition of the maintained component at the time of
maintenance. Say a component initially is replaced once a year, then after the first series of
replacements, the condition of the replaced components is inspected and recorded. If the
inspection shows that the component could have performed its function, the period until the
next overhaul is extended by a certain amount. This process is repeated until the inspection
reveals clear signs of an approaching wear-out of the component, and the TD interval is either
kept at that timer interval, or reduced slightly to allow for a certain period of grace.
Condition Based Maintenance (CB): CB tasks are tasks that seek to detect the onset of a failure in
order to take actions that prevent the failure. On onset of failure is a condition that either
indicates that a failure is about to occur, or that something has happened which will cause a
failure within a certain time-frame, an example would be vibration analysis of the gearbox, a
steady increase in gearbox vibration could indicate the onset of a failure in components such as
bearings or gears (Lu et al. 2009). As failure rate pattern D, E, and F show, most failure modes
are not age-related, as stated, equipment can show indications that a failure is about to occur.
The P-F Diagram, displayed in Figure 10, show how a WT gearbox has several indicators om
impending failures prior to the onset of the failure, this is of course dependent on the exact
failure type. If the indicators are identified, it is possible to plan for the failure, if possible restore
Figure 9: Planned maintenance failure rate pattern, adopted from ABS (2004)

23
the equipment prior to failure, or at the very least plan for CM as effectively as possible to
reduce downtime (Moubray 1997; Petersen et al. 2013; Petersen et al. 2014).
Figure 10: A P-F curve depicting the deterioration of a gearbox (Petersen et al. 2014; Petersen et al. 2013; Moubray
1997)
Failure Finding Maintenance: Failure finding maintenance tasks are used to discover failures
which are undetectable during regular operations(ABS 2004). These types of hidden failures are
often located within redundant systems, and in these cases are not discovered until the primary
system fails. However, WTs have very few redundant systems and those that exist are limited to
those required to ensure turbine safety, such as backup power supplies for the control and pitch
systems (Walford 2006).
3.3.3 The need for O&M improvements
Although the wind power industry is one of the most discussed power generation technologies
compared to its share of global power production, it is also a very fragile industry. The low price
of electricity makes the industry heavily reliant on subsidies provided by the government. As
O&M account for 30% of the total cost of an offshore wind farm(Blanco 2009), improvements in
this area will go a long way to improve upon the business case of an offshore wind farm
(Besnard et al. 2010; Fischer et al. 2012; Fischer et al. 2011).
An easily observable trend in the offshore wind sector is the development and deployment of
larger WTs (Hofmann & Sperstad 2014). Due to the general rules connected with WT placement
that a turbine needs approximately 10 ha/MW of space the increase in the size of turbines

24
means a decreasing amount of turbines (Emami & Noghreh 2010). One of the key reasons for
this tendency is the decrease in installation costs as factors such as foundations, substructures,
electrical infrastructure, and project management decreases in complexity and/or number.
Although the installation costs are reduced, the levelized cost of an upscaled WT, i.e. the $/MW
will increase, this is due to the fact that the weight of the turbine increases faster than the
power output when upscaling. Taking into account technological developments as well, it can be
expected that the levelized costs will remain stable (Sieros et al. 2012). Whilst the cost of the
sub-structure itself increases linearly with the rated power of the turbine, the costs of
installation, electrical infrastructure, and de-commissioning is highly dependent on the number
of turbines, and therefore these costs will decrease (Fingersh et al. 2006).
The increase in power level and size of each individual turbine also means an increase in
individual costs of WT O&M. With O&M costs being dependent on the costs of vessels,
personnel and spare parts needed for maintenance. And as the turbines are physically larger, so
are the loads within the turbines and, suffice to say, so be the spare parts which means they also
are more costly. Hofmann & Sperstad (2014) concludes that there is a small cost advantage by
using larger WTs; this advantage is quickly counterbalanced by increases in failure rates. This
means in order for companies to fully utilize the advantages of larger turbines, much effort has
to be put into the prevention and handling of failures.
3.3.4 O&M of offshore WTs
An article by (van Bussel 2002) states that after year 2000, the focus of the wind energy sector
has shifted from onshore wind farms towards offshore wind farms. However, this shift also
brings along a new set of challenges to the sector, and although the industry has changed
significantly since the publishing of the article in 2002, many of van Bussel’s arguments are still
rather interesting, and it helps outline challenges which are still present in the industry.
Challenge 1- Installation: The installation of offshore WTs is time-consuming, typically taking 3-5
days per turbine. With large sites featuring more than 50 turbines, installation times could easily
take more than 6 months, as a comparison, Horns Reef 1 consists of 80 turbines and it took 10
months from construction started in February 2002 to it was activated on the grid in December
2002, in spite of using parallel operations. As a comparison it took a little over two years, March
2011 to April 2013, to construct the 175 turbine London Array 1 showing that construction
speed has not changed much (LORC 2014).

25
Challenge 2 – Reliability: As earlier determined, WTs are just as any other piece of equipment
subject to systems failures. According to van Bussel (2002) onshore turbines would typically
require an average of 4.5 visits per year, two of which were service related. Which, when the WT
is located onshore does not present an actual problem. However, in an offshore environment it
could due to challenge nr. 3.
Challenge 3 – Accessibility: Whilst onshore WTs are accessible year-round at all times of the day,
access to offshore turbines is highly dependable on weather conditions. Access to Horns Reef 1
is only possible either by boat or helicopter, and some days not at all possible because of the
harsh conditions that are present offshore, in fact, Breton & Moe (2009) estimates that access to
offshore WTs is only possible 50-70% of the year. Decision making related to failure corrections
extends from being a matter of spare part and technician availability, to also include weather
considerations. Feuchtwang & Infield (2013) depicts the extension of the decision making as
shown in Figure 11
Figure 11: Event tree for offshore repair decision making, adopted from Feuchtwang & Infield (2013)
Challenge 4 – Special Resources: Maintenance of offshore wind farms in many cases require the
use of special resources, and the lack of these can lead to increased downtime compared to
similar failures in an onshore environment. Conducting major repairs in an offshore wind farm
often requires the assistance of a crane vessel. Due to the cost of these vessels operators
doesn’t own these and instead they are supplied by a third party and, due to the low number of
crane vessels in service, they are a limited resource (Thomsen 2011). At the same time, many of
the older offshore wind farms, such as Horns Reef 1, consist of turbines that were originally
designed for onshore operation and have then been adjusted for offshore operation through e.g.
extra protective coatings and sealing of bearings and nacelle against salt water. This means large

26
parts of the major spare parts, such as blades, are not suited for offshore service, and have to be
refitted for offshore use prior to installation (van Bussel 2002).
3.4 Maintenance concepts
Although RCM was already selected as the applied maintenance methodology for this thesis, it is
still important to understand which methodologies already exist within maintenance
management theory, and determine why RCM is a valid candidate for application in the offshore
wind industry. Pintelon & Parodi-Herz (2008) categorizes some of the major maintenance
concepts, based on the era in which they emerged, into “generations”, depicted in Table 1. The
authors assume that newer generations of maintenance concepts are superior to their
predecessors in that they are, to a higher degree, able to account for the increasing complexity
of maintenance decisions. The first maintenance concept in existence was the Ad hoc concept. In
the past, equipment in general was a lot less complex which meant that maintenance policies
could be and were developed as failures occurred and were resolved. As installations, along with
technology, grew increasingly complex, the intermediary Questions & Decisions (Q&D) concept
was born in order to more effectively deal with these developments. The Q&D concept allows
for establishing of maintenance policies through yes/no answer to relatively simple questions.
Pintelon & Parodi-Herz (2008) note that whilst the concept lacks the holistic view needed for the
development of thorough and sophisticated maintenance programs, the concept is still widely
used due to its simplicity. Amongst the 2nd
generation of maintenance concepts, Pintelon &
Parodi-Herz (2008) presents Life Cycle Costing (LCC), Total Productive Maintenance (TPM), and
RCM.
LCC was developed in the late 1960’s and is based on two principles. The first principle is the
cost iceberg structure, which illuminates that when considering maintenance or equipment
purchasing alternatives, one should not be limited to view the “top of the iceberg” e.g. the direct
maintenance costs in terms of materials and labor, but also the underlying costs which affects
the overall costs in the long run, e.g. operational expenses, training costs, inventory costs etc.
(Blanchard 1992; Bertsche 2008). The second principle concerns that the further into the
lifecycle of the equipment you progress, the more costly it is to make modifications. The LCC
concept lies as a foundation of many other maintenance concepts which in turn couldn be
classified as generation 2nd
→ 3rd
. An important aspect of LCC is that the key focus of the concept
is financial, not technical. It aim at maximizing the ROI on assets by providing the information

27
needed to make the optimal cost-effective decisions from deployment to decommissioning
(Pintelon & Parodi-Herz 2008).
The TPM concept was defined by Nakajima (1988). The concept includes a companywide
approach to asset care, requiring active participation from the entire workforce, from top
management to shop-floor workers, to improve asset performance by eliminating the six big
losses in asset performance; downtime, set-up and adjustment, speed, reduced speed, defects,
and reduced yield. The concept relies, to great extent of the performance of the operators to
maintain their own machines through a daily routine of maintenance checks, adjustments,
lubrication, and minor repairs. In short, eliminating and preventing equipment failures at the
lowest level possible. The effectiveness of TPM is measured primarily by the overall equipment
effectiveness (OEE), and an OEE of 85% is considered the goal. (Sharma et al. 2005)
Generation Concept Description Main strengths Main weaknesses
1st Ad hoc Implementing FBM and
TD/UBM policies
Simple Ad hoc decisions,
means no foresight
1st
→ 2nd Q&D Easy-to-use decision chart. It
helps to decide the right
maintenance policy.
Consistent,
Allows for priorities
Rough questions and
answers
2nd LCC Detailed cost breakdown
over the equipment’s
lifetime helping to plan
maintenance logistics
Sound basic
philosophy
Resource and data
intensive
TPM Approach with overall view
on maintenance and
production.
Especially successful in the
manufacturing industry
Considers
human/technical
aspects, fits in kaizen
approach.
Extensive tool box
Time consuming
implementation
RCM Structured approach focused
on reliability. Initially
developed for high tech/high
risk environments
Powerful approach.
Step-by-step
procedure
Resource Intensive
2nd
→ 3rd RCM-based Approaches focused on
remediating some of the
perceived RCM shortcomings
Example: RCAM
Improved
performance through
e.g. the use of sound
statistical analysis or
cost optimization
tools
Sometimes an
oversimplification
3rd Customized In-house developed; “cherry-
picking” from existing
concepts
Exploiting a firm’s
strengths and
considering the
specific business
context
Ensuring consistency
and quality in the
developed concept.
Table 1: Description of maintenance concepts generations, adapted from Pintelon & Parodi-Herz (2008)

28
The 2nd
→ 3rd
generation of maintenance concepts consists of updated and evolved versions of
the 2nd
generation maintenance concepts. One of these is RCAM which was proposed by Bertling
et al. (2005). RCAM is a combination of RCM and Quantitative Maintenance Optimization (QMO)
techniques. It seeks to counteract the drawbacks of both techniques; RCM, due to being a purely
qualitative method, lacks the capability of determining the most cost effective maintenance
strategies, whilst QMO techniques due to their focus on cost effectiveness do not always ensure
that maintenance efforts are applied to the most relevant components. (Bertling et al. 2005)
3.4.1 Reasoning for choosing RCM
The three maintenance concepts presented in this chapter; LCC, TPM, and RCM, are all very
powerful, but also quite different. The prerequisites, strengths, and weaknesses of three provide
valuable insight into why RCM could be the optimal solution of the three.
TPM as a maintenance concept requires to a great extent the presence of operators in
conjunction with the equipment. It is evident that the concept is designed primarily for
production companies with manually operated equipment. TPM conflicts with the wind farm
industry on several areas. First is the requirement of operators to prevent and correct minor
failures, also TPM’s measure of excellence, the OEE, can be compared to the capacity factor
measurement used in the wind industry. As WTs are dependent on specific wind speed intervals
to perform at its maximum as well as turbine availability, capacity factors above 50% is rare, and
even the best estimates of what is possible in best-case scenarios, put WT capacity factors at
around 60% (Boccard 2009)
LCC is, as mentioned focused, on the financial aspects of the asset, and the optimization of
these. However, whilst the financial aspects are important to remember, they should not be
considered the first area of improvement as the average wind energy business cases is currently
made profitable and competitive through the heavy use of government subsidies (Cullen 2013).
However, there is much room for technical improvement within the offshore wind industry.
Whilst the availability, i.e. the time in which the WT can produce power, is typically in the range
of 95-98% for onshore WTs, many offshore projects have an availability as low as 60%. This is
largely attributed to serial failures and tough weather conditions, and shows a clear potential for
technical improvements in offshore O&M practices. (Besnard 2013)
(Pintelon et al. 1999) present a case study where an automotive manufacturer had to decide
upon a concept which could develop an effective and efficient maintenance concept. The focus

29
was on fully automated equipment with at the same time was relatively new, and thus providing
very little in terms of failure data and maintenance behavior. The study examined four different
methodologies, and decided upon a slightly customized RCM II (Moubray 1997) as the best
suited methodology. The selection was made based on a set of requirements for the
maintenance concept that were developed from the situation on hand. Interestingly, the
situation of the automotive manufacturer and the offshore wind industry is highly similar. Both
deals with:
 Large and complex installations – this is of course relative and difficult to quantify.
However, compared to onshore wind farms, offshore wind farms can be defined as
larger and more complex
 Limited data available
 A fundamental approach which allows for redesign of equipment as a maintenance
solution
 An operational situation where planned maintenance intervals are better than “on-
need” maintenance.
 Clustering of maintenance – this is not provided by RCM in any form, the case study
added a clustering step to the methodology, and in this project, modularization of
maintenance tasks, or clustering if you will, is a part of Kristian Petersen’ overall PhD
project.
The high similarity of the conditions of the case study and the situation of offshore wind farms
indicate that RCM could provide highly beneficial inputs to the development of a maintenance
strategy in the offshore wind industry.
3.5 Reliability Centered Maintenance (RCM)
RCM is a qualitative approach to maintenance management which directs maintenance efforts
towards parts and systems where reliability is critical (Garg & Deshmukh 2006). The RCM
methodology was initially developed for the consumer aviation industry, specifically
maintenance of the Boeing 747, in the 1960s and it is not until 20 years ago it started gaining
traction in other industries. The name originates from a desire to put emphasis on the role
reliability and statistical probability plays in centering PM activities towards retaining
equipment’s function (Smith & Hinchcliffe 2004). The method relies on the basic concepts of
reliability as well as the tool failure mode and effects analysis (FMEA) to determine which

30
systems possess the highest risk of causing downtime, and assist in determining when and
where maintenance activities should be directed. It is an empirical, yet sophisticated method,
which combines the experiences of the personnel involved in the analysis with the general
recommendations from the OEM. Summarizing it is possible to describe RCM using four
characteristics or goals of the analysis.
1. Preserve function of the system.
2. Identify all failure modes that can defeat the function.
3. Prioritize function need (through failure modes).
4. Select applicable and effective PM tasks for the failure modes with high priority.
It is important to note that maintenance carried out with the aim of preserving or improving the
aesthetical appearance of the equipment is not considered in the RCM analysis, unless these
aspects have an effect of a systems’ function (Rausand 1998)
3.5.1 Project group composition
When doing an RCM analysis, (Moubray 1997) propose the formation of groups which will
analyze a system within their particular area of expertise. A group will have to be well-rounded
with representatives from various areas of the organization. Generally the group should consist
of:
 A Facilitator
 An Engineering Supervisor
 A Craftsman
 An Operator
 An Operations supervisor
 A Specialist
The facilitator is an expert in RCM with a profound knowledge of how to conduct group
research. The facilitators’ primary task is to facilitate the analysis by asking the questions needed
to extract the knowledge possessed by the participants, and ensure all relevant knowledge has
been extracted, whilst at the same time keeping the analysis moving forward in a suitable pace.

31
The engineering supervisor is a person possessing extensive knowledge on how the analyzed
equipment is supposed to function, the functional areas and their limits are standard knowledge
for the engineering supervisor.
The craftsman role is upheld by a person with extensive knowledge and experience with
maintaining and repairing the analyzed equipment. Their knowledge on the present state of the
equipment as well as the conditions that apply for providing maintenance is unique as they can
function as a primary source.
The operator is the person who operates the equipment on a day-to-day business, this role
usually know some of the first indicators of imminent failures, and well as tacitly founded
estimations of the most common/most annoying failures. In relation to WTs the role of operator
is not entirely present as the WTs operate fairly autonomously, and as such, the position closest
to the role of operator is found as the personnel in the surveillance center.
The operations supervisor is, as the name suggests, the person in charge of the operation of the
analyzed equipment. This role is able to provide valuable insight into the more strategic
considerations encountered in the analysis, providing the why to the what.
The specialist role is the only role which according to Moubray (1997) does not have to be
present throughout the entirety of the analysis. Specialist can be brought into the workflow in
case their specified area of expertise is needed. For instance a CMS specialist is rarely needed
prior to the development of CB tasks for the prevention of various failure modes.

32
3.6 RCM guidelines
Whilst the concept for maintenance optimization has been selected, the guidelines for the actual
analysis differ slightly from author to author depending on each authors experience and
preferences (Besnard et al. 2010; Smith & Hinchcliffe 2004; Rausand 1998). Reason for the high
similarity between guidelines can be attributed to the industry standard covering RCM (JA1012
2004).
Smith & Hinchcliffe (2004)
1. System selection and data
collection
2. System boundary definition
3. System description and
functional block diagram
4. System functions and
functional failures
5. Failure mode and effect
analysis
6. Logic tree analysis (LTA)
7. Task selection
Bertling et al. (2005)
1. Define reliability model and
required input data
2. Identify critical components
by reliability analysis
3. Identify failure causes by
failure mode analysis
4. Define failure rate model
5. Model effect of PM on
reliability
6. Deduce PM plans and
evaluate model
7. Define strategy for PM:
When, what, how
8. Estimate composite failure
rate
9. Compare reliability for PM
method and strategies
10. Identify cost-effective PM
strategy
Rausand (1998)
1. Study preparation
2. System selection and
definition
3. Functional failure analysis
(FFA)
4. Critical item selection
5. Data collection and analysis
6. FMECA
7. Selection of maintenance
actions
8. Determination of
maintenance intervals
9. Preventive maintenance
comparison analysis
10. Treatment of noncritical
items
11. Implementation
12. In-service data collection and
updating.

33
Common for all RCM guidelines is the reliance on a failure modes, effects, and criticality analysis
(FMECA). The FMECA offers, apart from a basis for the analysis, a complete list of all potential
failure modes, their effects and symptoms. This acts as a valuable piece of information which
can function as a basis for failure diagnostics as well as a checklist for technicians performing
maintenance. The FMECA is very effective in cases where system failures are caused by single
components; as failure modes are singled out without regard for preceding or subsequent
failures, it loses some effectiveness in systems with a high degree of redundancy. However, as
previously established, WTs contain few redundancy features, and as failures leading to a
turbine shutdown are predominantly caused by single or few components, the FMECA should be
highly effective for use in this sector.
3.6.1 RCM in the wind power industry
Over the years several papers and theses on the application of RCM, or RCM-based maintenance
concepts in the wind power industry have been published. Andrawus (2008) performs a RCM
analysis on the top level of assembly of a WT, resulting in an analysis which uncovers one
function of a WT, three functional failures; i.e. states in which the equipment does not perform
as intended, and 33 failure modes; i.e. causes of functional failures. Whilst the analysis performs
as intended in relation to the thesis in which it was published, it can be argued that the analysis
fails to find specific maintenance tasks which can improve upon the equipment’s ability to
perform its intended function. Another application of the RCM maintenance concept in the wind
power industry is presented by (Fischer et al. 2011). The article used a guideline presented by
Bertling (2001), and performed the RCAM analysis on a different level of assembly of the turbine
than what was presented by Andrawus (2008), which resulted in PM task suggestions. However,
as the article was limited in its scope, it presented no suggestion on specific tasks selection or
task intervals, nor did it present any indication of implementation of the discovered results.
During the literature review, no examples were found presenting actual implementation of a
RCM based maintenance strategy.

34
4 Empirical Study part 1: Current O&M conditions at
NW-GH
This section aims to outline the current O&M conditions for both front- and back-end
operations. In NW-G front end operations refers to the maintenance of their WTs, whilst back-
end operations are the services done at the office which allow for the maintenance to be
conducted e.g. data processing, administration, and planning. To gain knowledge on the front-
end O&M activities, a site visit to a WT was conducted in October, whilst information on back-
end activities have been collected through presence in the NW-G organization, and through
questions posed to the head of NW-GH.
4.1 Front-end activities and conditions
In order to understand the working conditions of the maintenance technicians on HR1, a site
inspection was conducted at a Vattenfall test turbine located in the onshore wind park
Tjæreborg close to Esbjerg. The Tjæreborg turbine is an exact replica of the turbines located at
HR1. Present at the site, apart from myself was; Kristian Petersen, PhD fellow at NW-G, Richard
Ruitenburg, PhD fellow at Liander – a Dutch energy provider, and turbine technician and service
leader Anders Stokkebæk.
On arrival the visitors changed into coverall, safety shoes, and climbing harness. We then
proceeded to the turbine. Prior to entry the control center in Esbjerg was contacted informing
them that the turbine was about to be turned off manually. On the first level, the technician
switched the turbine from production status to idle status by first turning a key in the ground
controller, which changed control of the turbine from Remote to Local, and then changing
operating status of the turbine via a control panel. When idling, the rotor rotates very slowly this
is preferable to a complete stop, as the complete stop is considered to apply increased wear on
individual rollers in the main bearing. Because of this, the rotor is only put to a complete stop
when technicians need to enter the rotor, or when technicians are transported to the turbine by
helicopter.
As the lift could only contain two people, and for science reasons it was decided by Martin,
Richard and Kristian to climb to the top on the ladder inside the tower. The climb to the top
could be classified as a small physical challenge. The main ladder ended a short climb (2m) below
the entrance to the turbine. And after pushing ourselves through the entrance under the

35
gearbox we found ourselves in the nacelle. The nacelle is fairly cramped, e.g. to access the rotor
one first has to climb over the gearbox, squeeze through a hole and climb of the outside of the
hub in order to enter through a hole in the tip. Inside the hub there is access to the blades’
interior. Another observation was that the distance between the generator and the converter is
just wide enough for two people to squeeze past each other.
The descent from the turbine was quite simple. And once we were all down, contact was made
to the surveillance center informing them of the imminent restart of the turbine, which was
done via the ground control panel, after which the key in the controller was turned to Remote,
returning control of the turbine to the control center.
4.1.1 Observations
During the visit several observations were made.
1. When switching the turbine from production mode to idle, the key was only turned for a
few seconds, and once the information display on the controller showed the turbine
went into idling the key was put in to “Local” mode. When the turbine is in local mode, it
cannot be controlled from the control center. At the ALCM workshop it was learned that
the key had to be turned for at least 15 seconds to avoid sending an alarm code to the
surveillance center. The surveillance center was aware that the turbine had visitors, but
the alarm would still be recorded through SCADA and due to the length of the visit, it
would register as a failure in the internal Vattenfall statistics rather than a service visit.
2. Climbing to the top can be considered very requiring if the person making the climb has
to carry and significant weight, highlighting the importance of the lift.
3. The lift ends 2-3 meters below the nacelle meaning the technicians has to either hoist or
carry spare parts the remainder of the way up.
4. The entrance to the nacelle itself is quite narrow putting a significant size limit of spare
parts entering this way; this is made fairly insignificant as the challenge of carrying or
hoisting parts and equipment from the lift seems larger.
5. Fairly little room for moving around inside the nacelle and according to the technician
movement inside the hub presented an even larger challenge due to very limited space.
6. There is an option of using the internal nacelle crane to hoist spare parts from the
surface through a hatch in the nacelle; this requires the transport vessel to be present,
which in turn means the other technician teams cannot be transported whilst the
hoisting is going on. Therefore is avoided as much as possible.

36
4.2 Operations at NW-GH
This section will outline the different functional areas present in the NW-GH organization as well
as which processes each functional area is concerned with. It will also compare these processes
and operating procedures with those which are deemed necessary for an RCM analysis.
Roughly put, NW-GH consists of three functional areas that can be discerned from the NW-G
organization. The areas are:
 Front-end Operations which consists of the technicians and transport vessel crew which
are directly involved with performing service and failure correction at HR1
 Back-end Operations which consists of employees engaged in planning, data analysis,
turbine surveillance, etc. The dilemma of the back-end operations is that many of the
employees are not devoted to HR1. The CMS team is responsible for large parts of the
CMS installations in Vattenfall’s WTs, the surveillance team monitors all of Vattenfall’s
WTs, and they are part of a different business unit altogether. Apart from the Site
Manager, no other employee of Vattenfall’s solely devoted to HR1 has been
encountered within the Back-end operations group,
 Storage; the storage facilities at NW-G’s Esbjerg office contains the spare parts needed
for servicing and maintaining the turbines in its region. Whilst spare part management
could be considered a Back-end function, it has been isolated as the area is kept by a
single person. The storage manager, as noted by the Site Manager of HR1 during the
ACLM workshop, has up until now been a key figure in the detection of components
with less-than-optimal reliability.

37
4.3 Current O&M practices at Horn Rev 1
At HR1, maintenance activities are conducted and planned throughout the year they vary in both
complexity and size, and based on strategic considerations a portion these activities are
outsourced. The activities are grouped into three groups shown in Table 2
Group Typical tasks Execution strategy
1 – Simple tasks Service visits and other
repetitive tasks, e.g.
biennial tightening of
tower bolts
It has by NW-GH been decided that the knowledge
and experience connected with group 1 activities is
too insignificant compared to the cost of keeping
these activities in-house. Therefore all group 1
activities are outsources
2 – Medium
difficulty tasks
Failure finding, failure
correction, and upgrade
installation. I.e. tasks
related to corrective
maintenance and design
modifications.
As these activities require a high level of quality as
well as efficiency, the competencies associated with
group 2 activities are considered very valuable to the
organization are kept in-house.
3 – Difficult tasks Specialist tasks requiring
expert competence and
advanced equipment. E.g.
Inspection and repairs
related to foundation and
blades
Due to the limited number of group 3 activities, the
cost of keeping these activities outweigh the
organizational value of keeping the activities in-house.
Therefore these activities are outsourced.
Table 2: Grouping of maintenance activities at HR1
Service visits are conducted twice a year with one being a small service visit, and the other being
a larger one, respectively requiring a two and four days, with two technicians each day. Service
visits usually entail testing of various systems, the replacement of certain time-directed
components as well as a general overhaul e.g. tightening of bolts in the tower. Service actions
vary from visit to visit, some are standard such as refilling of lubricants and oils, checking for
leaks etc., whilst others only occur once every few years, e.g. tightening of bolts in the tower or
exchanging the oil in the gearbox. Service visits are quite interesting in terms of lowering the
cost of O&M, as this post represents approximately 10% of the O&M costs per MWh produced
as well as approximately 55% of total turbine downtime(NW-GH 2014). However, as this thesis
focuses on how RCM can improve failure rates and the downtime related to these; service
operations will not be discussed in depth. It should be noted that a large portion of the service-
related costs are caused by the downtime of the turbines being serviced, and the LOP related to

38
this. NW-GH are aware of this, although they attempt to plans the majority of the planned
maintenance in periods with low winds, increasing time effectiveness of service visits can do
much to lower the costs; which is researched in depth in the Modularity section of the PhD
project conducted by Kristian Petersen.
Failure correction is planned and performed on a case basis. Depending on the type, the activity
can last anywhere from three hours to four months (typically)1
. The long duration failure
correction activities are typically a result of a failure occurring in a major component such as
gears. These failures do not always cause high downtime, as major components are to a high
degree monitored by a condition monitoring system which enables an estimation of time-to-
failure. This allows for planning of which activity should be conducted. This is best explained
through an example:
A major component which is continuously condition monitored in the HR1 turbines is the
gearbox. Gearboxes are equipped with vibration monitoring, and the CMS team at NW-G is able
to detect increases in gearbox vibrations. From these vibrations, not only can the failing
component is the gearbox be specified, but also the components status on the P-F curve can also
be determined (Petersen & Madsen 2013; Petersen et al. 2014). Depending on the failure type,
the gearbox may have to be replaced. Replacing the gearbox requires the use of a crane vessel
which is then requisitioned at an appropriate time. When the crane vessel is available the failure
correction is then conducted. NW-GH has due to its proximity to the Esbjerg harbor had a very
ad hoc approach to the requisition of crane vessels which came forth during the ALCM
workshop, where typically crane vessels would be engaged by making contact to crane vessels
docked in the harbor; and thus was not engaged in other assignments at the time.
Minor failure corrections are typically handled on a day-to-day basis. From the NW-GH capacity
plan, it is known that every day, a technician team is dedicated to the correction of failures. July
15th
2012 at 06:18AM, the HR1 turbine WH1221 experienced a failure which triggered alarm 353
in SCADA. The surveillance center was unable to restart the turbine, which prompted the
opening of a SAP work order. As working conditions were suitable, a technician team was routed
to the turbine, once in the turbine, the team inspected the turbine, from the SCADA alarm code
they knew the most likely cause of the stop was the Q8 breaker. From SAP work orders it is seen
that the Q8 breaker was replaced, and the turbine was turned back on the same day at 11:36.
1
The interval was reached based on SCADA data, and
information which appeared during the two workshops.

39
The technicians work 12-hour shifts from 6am to 6pm. This means that failures occurring after
6pm at the earliest will be inspected the next morning. By comparing SCADA and SAP data
examples of Q8 replacements were found with turbine downtime ranging from 71 minutes to
just over two days. This considerable high interval for Q8-replacement dependent downtime is
most likely due to weather conditions which can prevent technicians from reaching the turbines.
Spare parts for HR1 are mainly stored at the Esbjerg facility. However, one of the service vessels
stock a small supply of the most common spare parts e.g. lubrication, oils, circuit breakers, etc.
in order to be able to accommodate the daily failures occurring during work hours.

40
5 Empirical Study 2 (RCM ANALYSIS)
Throughout the years, several improvements to the RCM concept have been developed, many of
these are dependent on the application area, examples of this are: RCM 2 (Moubray 1997)
,RCAM (Bertling 2002) which was developed for electrical distribution systems, Streamlined RCM
(Bookless & Sharkey 1999) which was developed for application in the nuclear energy sector,
and SRCM (SKF Reliability Systems 2008). Whilst the specifics of each concept varies, each of
these concepts are all founded in the original RCM methodology developed by Nowlan & Heap
(1978). As previously mentioned this project will use the guideline provided by Smith &
Hinchcliffe (2004), this is due to the advances made especially in the area of condition
monitoring, which potentially renders Nowlan & Heap’s concept obsolete, whilst the steps are
the same, the activities in this newer guideline takes into account these technological advances.
The execution of a RCM analysis follows a series of steps. Smith & Hinchcliffe (2004), Nowlan &
Heap (1978), Fischer et al. (2012), and ABS (2004) all emphasize the importance of following the
steps and not “jumping ahead” as one has to make sure every aspect of the current step is
covered before moving on, otherwise important aspects may be overlooked. Some authors such
as Fischer et al. (2012) combine some of the points. However, as the results from the articles,
which have adapted the guidelines and then applied them in the wind industry predominantly
are limited, this thesis follows a simpler and more traditional guideline which is defined by
Smith & Hinchcliffe (2004):
 Step 1: System selection and collection of information
Step 2: System boundary definition (where does it start, where does it end)
 Step 3: System description and functional block diagram (what does the system look like,
and how is it connected with other systems)
 Step 4: System functions and functional failures – Preserve functions (what does the
system do, and when does it not perform satisfactory, e.g. a faucet which performs its
function when flow-rate is >10L/min. A flow-rate <10L/min would constitute a functional
failure)
 Step 5: Failure mode and effect analysis (FMEA - identification of all failure modes which
can prevent fulfillment of intended function)
 Step 6: Logic tree analysis (LTA)(Nowlan & Heap 1978) – Prioritization of function need
via the failure modes.

41
 Step 7: Task Selection – Only useable and effective PM tasks will make it through this
process, but all possible solutions will be listed in case they become relevant in later
updates of the RCM program.
Note that steps 4-7 are practically the same as the four characteristics of RCM, whilst the first
three steps serve to ensure a thorough and sufficient level of knowledge for the analysts
allowing clear-cut definitions and a higher level of rigor in the analysis. To fully complete the
RCM program, two additional steps are needed. However, these will not be included in this
thesis as they involve actual implementation of the results found in the analysis
 Step 8: Task packaging – Initiatives which will bring the selected PM tasks into action
 Step 9: Living RCM program - Comprising the actions need to ensure long-term
commitment to the beneficial results given through steps 1-8
As mentioned, the guideline presented by Smith & Hinchcliffe (2004) was selected as it was
determined that it was more suited for using a systems approach in an environment with little
data available. The guidelines presented by Rausand (1998) and Besnard et al. (2010) both rely,
to a great extent, on selection of critical components primarily based on reliability data of said
component. However, the system selection process in the selected guideline allow for system
selection based on costs of maintenance or costs related to loss of production. As reliability data
can be unreliable for very young systems, due to the wear-in period often present in the
reliability of systems (Nowlan & Heap 1978; Crow 1975), the application of Smith & Hinchcliffe’s
(2004) model is more likely to be beneficial in younger wind farms, and as the workshop was
joined by two representatives from Vattenfall’s UK/Continental Renewables branch, who were
exploring how RCM could be applied to the young Prinses Alexia wind farm in the Netherlands, it
was determined that they would have more to gain from a guideline which was more suitable to
their needs. Another factor was the complexity of creating the reliability data for Horns Rev 1,
due to the quality of the data available from SCADA and SAP, which will discussed later in this
thesis.
The workshop was conducted at NG-G in Esbjerg in November 2014. The workshop was aimed at
determining several things:
1. To test how suited this RCM methodology is for the offshore wind energy sector.
2. To test how suited a workshop based approach is for conducting an RCM analysis.

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