failure_analysis_of_rotating_equipment_using_root_cause_analysis_methods.pdf

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POWER-GEN International 2011, Las Vegas, U.S.A.

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Failure analysis of rotating equipment using root cause analysis methods

Graeme Keith, Lloyd's Register ODS1

Philippe Loustau, Lloyd's Register Energy Americas2

Magnus Melin, Lloyd's Register3

Increasing demand on equipment up-time in power sector

With the rapid development of technology and ever rising demand for energyconsumption, more and bigger power plant projects are being designed, built andoperated around the world. Increased portion of renewable energy in the energysystem gives increasing pressure on conventional thermal power plants to reduceemissions by adopting new technologies, for example co-firing with biomass, butalso to operate more flexibly with short windows of operation to cope with peakloads. All of this brings additional complexity to power plants and equipment(especially critical machinery), which can provide higher output and efficiencies, butalso brings greater technical and financial risks in case of failure and problemsduring the asset lifecycle.

Consequences of equipment failure range from short unexpected downtime to totalstop of production for an extended period. Despite the best intentions andprecautions, failures do occur.

Whenever equipment fails to meet expectations or fails altogether, we mustunderstand what went wrong so that we can safeguard against it ever happening

again. A good explanation not only helps you prevent a failure from reoccurring; itcan help identify systematic weaknesses that might result in other failures.

To give a good explanation is to give a full account of the relevant causes of afailure. There are a wide variety of root cause analysis (RCA) methods andprocedures for analyzing the causes of failure, including the widely used Fishbone orIshikawa diagram, the appealingly simple Five Whys, the versatile Fault TreeAnalysis and its close cousin the causal map. Each method has its particularadvantages and drawbacks. Many were developed for some particular sector orapplication and while they work very well on their home territory, they are not all asuniversally applicable as their advocates sometimes hope.

All these methods are essentially about mapping causes: identifying the immediatecauses of a failure as well as the causes of those causes and so on. In the following,we exemplify the different methods by using an example from the philosopher DavidLewis, a car accident with a drunk driver, driving too fast in a car with bald tyres.

The Ishikawa (fishbone) diagram

The different methods emphasize different aspects of causal mapping. The fishbonediagram provides a useful categorization, allowing investigators to focus on one

1

Email: [email protected], website: www.lr-ods.com2Email: [email protected], website: www.lrenergy.org

3Email: [email protected], website: www.lr.org


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category of possible causes at a time. The categories vary according to application,but a typical list is Equipment, Process, People, Materials, Environment andManagement.

Figure 1 shows the beginning of a fishbone diagram for the car accident example.The categories are drawn into a thick horizontal line leading to the problem we aretrying to explain. Drawn into these lines are the various causes identified in eachcategory and into these lines may be drawn secondary causes, i.e. causes ofcauses.

Figure 1: A fishbone (Ishikawa) diagram for the car accident.

The great attraction of the fishbone diagram is also its great weakness. Whilst thecategorization provides clarity for the discovery of causes, it imposes unnaturalrestrictions on mapping the relationships between these causes. For example, wehave identified the drivers drunkenness as a cause in the category people. Clearlythe poor mans depression may have contributed to his drunkenness, but there is nonatural way to cross categories while passing down a chain of causes in the fishbonediagram. Some more recent models of the fishbone diagram facilitate longer chains,but the fishbone diagram is severely limited for all but the simplest problems.

Causal mapping

Causal mapping dispenses with the categorization and liberates the connections sothat the relationships between causes can be made clearer and more instructive.The car accident example is sketched in Figure 2, where the causal chain has alsobeen extended beyond the crash to include the true cost of the failure in terms ofsafety, asset or business performance and environment.

Starting with these ultimate consequences, we work backwards through a series ofwhy-questions, most of which will have several answers. Why did he crash? Heskidded off the road. Why did he skid off the road? The road was icy. The tyre wasworn. There was a car coming in the opposite direction, which he served to avoid.Why did he swerve? He saw the car too late and was in the middle of the road. Why

CRASH!

Peo leProcessE ui ment

Materials Environment Mana ement

Drunkdriver

Drivingtoo fast

Baldtyres

Icy road Driverdepressed


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did he see the car too late? Why was he in the middle of the road? The corner wasblind. He was driving too fast. He was drunk and his reflexes were slow.

Causal mapping is an attempt to formalize the interaction between deterministiccauses; Bayesian networks do the same statistically, introducing a probabilistic,quantitative, element; the fault tree explicates the causal relationships using Booleanlogical operators. The Five Whys method is a simpler approach that focusesattention down single causal chains: the cause of the cause of the cause etc. (timesfive).

Figure 2: A causal map for the car accident

Causal relations, root causes and relevance

These methods are useful to establish causal relations. They help to identify rootcauses, i.e. causes that lie at the root of several chains leading to the final failure.Our drivers depression is a root cause: it causes his drinking, the neglect that leadto the bald tyre, and the recklessness that lead to speeding without a seatbelt. These

methods help us to manage and quantify complicated interdependencies, especiallywhen those interdependencies are statistical rather than deterministic.

It is not always clear how far back in a causal chain it is useful to go (though the fivewhys method has a pretty big clue in its title). Taking the causal map seriously andconscientiously following the why-methodology quickly leads to a bewilderingmultiplicity of causes and information overload. In practice, investigators use theirexperience and judgement to decide how far back to regress along a causal chainand how much to drill into it, but this can make the results too subjective anddependent on the prejudices and preoccupations of the investigator.

CRASH! Swerveto avoid

Saw cartoo late

Drivingtoo fast

Skiddedoff road

Baldtyre

Icy road Blindcorner

DrunkDriverdied

Noseatbelt

Depressed

Carwritten

Coll.damage


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The general problem here is relevance. Whether a cause is relevant or not dependson the context. The road safety expert, who wants to know why the corner is blind,has different interests from the forensic psychologist, who is interested in the

depression and who, in turn, has different interests from the insurance lawyer who isonly really interested in the drinking. When investigating equipment failure, therelevant causes are the ones that give you a solution.

Discovering Causes

But there is a much bigger problem with these methods than relevance. Thesemethods make quite extreme demands on the omnipotence of failure investigators,as they all assume that the causes of a failure are known in detail and with certainty.In reality, we often have little clue what the causes of a failure are or could be andvery often, once we start looking, we come up with a large number of contradictorycandidates, not all of which can be the case. Before we can analyse the causes of afailure, we need to find out what they are.

The great British philosopher John Stuart Mill, in his 1843 book A System of Logic,gave five methods for discovering causes. Of these, the method of difference hasproved the most fruitful for practical applications. Faced with a failure, say adamaged steam turbine, rather than asking Why did this turbine fail? you ask Whydid this particular turbine fail and not this nearly identical turbine next to it? or Whydid this turbine fail today and not yesterday?.

The idea is to look at the difference between the failure case and a case as similar to

it as possible but in which the failure did not occur. The cause of the failure must befound in the difference between the two cases. By restricting attention to thedifferences between the two cases, you essentially ignore everything they have incommon and you dramatically reduce the amount of material and the number ofpossible causes you need to consider.

By switching through a variety of similar cases, we can generate a large number ofhypothetical causes and causal scenarios. Not all these will be true, but there arewell defined criteria for evaluating causal theories and choosing between them. Andits far better to have to choose between too many than to miss the right one or not tohave any at all.

Mills difference method as a practical tool for failure analysis

The difference method forms the basis of a powerful tool for discovering relevantcauses in cases of machinery and equipment failure in the power sector. Bycomparing the case in which the failure has occurred with similar cases in which ithasnt, we dramatically reduce the field over which we must search for possiblecauses. Moreover, if a cause can be found in the difference between two real casesthen there is a much better chance that it is possible to correct the problem, bringingthe problem case closer to the case where the problem hasnt occurred. Ourcontrasts need not necessarily be real cases; often contrasting with hypothetic cases

can be very revealing.


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Now let's look at a case study from the power sector to illustrate how failure analysistheory can be applied in real life

Case study shaft failure of diesel engine generator setIn this case, critical failure of the main shaft of a diesel engine driving a generator ata power plant had occurred. The engine is a modern 18 cylinder 4-stroke gas engineconnected to a generator via a coupling. An extensive material analysis of the failedshaft suggested that the crack initiated in a weak spot and progressed throughfatigue a very common finding in material analysis related to a failure. The way thecrack had propagated is consistent with torsional vibration.

Figure 3: Failure of shaft.

Without further investigations, the client concluded that the most likely cause wasmaterial failure of that particular shaft and a new shaft was ordered and installed.The same failure occurred again shortly after the engine was taken into operation.At that time it was decided to carry out a more extensive structured failure analysisusing Lloyd's Register ODS.

Looking back, it is easy to conclude that the decision to simply replace the shaft waswrong but, to be fair, it also easy to understand the rationale behind the decision the engine was a standard design and a large number of identical engines are inoperation without problems around the world. There had been no design change tothis particular engine, to the coupling or to the generator. Consequently, the problemmust be with the shaft itself, right?


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An initial listing of potential causes included: Material defect Misfiring

Alignment Structural resonances in the base skid Torsional damper malfunction

A material defect was given a low likelihood since it is unlikely to happen twice in thesame location at two different shafts.

Misfiring could be ruled out after discussions with the operational staff.

Alignment could be a potential cause since it is individual to each engine andtherefore could explain why this particular engine and not others had failed (Mills

difference method). Again, discussions with the staff ruled out that alignment was thecause.

Structural resonance in the base skid was also seen as a potential candidate but itwas difficult to explain why this particular skid would have problems and no otherskids of identical design.

Lastly, malfunction of the torsional damper was listed as a potential cause, primarilyfor two reasons it could explain why this particular engine and not others failed(Mills difference method again) and was also in line with the findings from thematerial analysis of the failed shaft where the propagation of the crack indicated high

torsional vibrations.

It was decided to continue the failure analysis by, at least initially, focussing on apotential malfunction of the torsional damper as the (most) likely cause. Twoquestions immediately arose:

Was the torsional damper not functioning as intended? Could a malfunctioning torsional damper cause torsional vibrations high

enough to initiate and propagate a crack as fast as observed in thefailure?

In order to gain further insight, two parallel activities were launched. The first was toremove the front cover of the torsional damper this was an easy and quickoperation and could potentially give a first indication of clearly visible damage if suchwas present. The second was to measure the torsional natural frequencies of theengine to better understand if there was a problem related to torsional dynamics.

The result of the inspection of the torsional damper did at first not reveal anythingextraordinary it looked brand new without clearly visible damage. However, acloser look at the surfaces between the damper mass and the shaft showed no signswhatsoever of wear. For those not familiar with torsional dampers this may soundperfectly normal but, in fact, it means that the torsional damper was not functioning

at all since its fundamental working principle is based on relative motion between themass and the shaft. A further full disassembly did confirm that the moveable parts of


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the torsional dampers were indeed locked in position corresponding to little or nodamping effect of the torsional damper. This had most likely been caused alreadyduring assembly due to a combination of the assembly procedure and (too) tight

tolerances due to inadequate quality control.

The results of the measurement of torsional natural frequencies showed that themeasured natural frequencies deviated from the natural frequencies calculated bythe OEM. A new full torsional model was built by Lloyd's Register ODS and used tosimulate the torsional dynamics of the coupled system. The result of the simulationsconfirmed that the torsional damper was critical to attenuate resonant responsebetween the 4 order excitation and the 1st torsional natural frequency of the shaft.Further, the simulations showed that a malfunctioning torsional damper would indeedshift the natural frequencies to those measured as well as cause stresses highenough to cause a failure as observed at the shaft.

Design changes were made to the torsional damper to mitigate future problems andincluded increased clearance of the back bearing and increased lube channeldiameter. The engine was taken into operation again after the modifications withoutany new failures occurring.

Conclusions

Structured root cause analysis methods such as fault tree analysis, causal mapping,fishbone diagrams (Ishikawa), Five Whys (Toyota) and Mill's method of differencecan be useful in failure analysis of equipment in the power industry.

There are many tools and it is important to understand their strengths as well as theirlimitations and the ways in which they can lead you astray. But with a broadtechnical insight, a clear conception of the notions of cause and effect and a soundunderstanding of the criteria for a good explanation, these methods can quickly bringinvestigators close to the relevant factors.

Based on our experience from more than 30 years involvement in failure analysis ofrotating equipment, we have found that a multi-disciplinary approach includingprofessional use of RCA methods, simulations of the system including coupledsubsystems when necessary and measurements is very useful to understand

complex failures and come up with effective mitigation measures.

failure_analysis_of_rotating_equipment_using_root_cause_analysis_methods.pdf

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