Reliability Bytes™

Humans are creatures of habit. They perform along certain established “known” lines of action, and reject the unknown quantities as potential failures or as unnecessary supplementary effort quite likely to yield identical (and sometimes worse) results. Due consideration for said results may at times ignore the fact that the additional benefits are seen elsewhere by people with a different skillset (for instance, the habit of entering ALL pertinent data in a CMMS merely seems overly long and tedious, whereas the manager wishes to mine the data to yield significant indicators that may or may not be understood at the keyboard entry level).

Changing any one “train of thought” is possible, but even that requires patience and dexterity in managing the change and shifting attitudes towards new goals. Attempting to change several known parameters towards newfangled ways of doing things can thus be readily demonstrated as both dangerous and most likely ineffective in the long run. A change can be achieved in the short run whilst a constant push is maintained to hold up the massive “old ways” but the second we remove the sustaining presence of that force, the old ways will seek to return back into familiar patterns.

How does this affect reliability efforts? Another author (and I seemingly can not readily find the reference at present) calls it the “6 months rule”. People will (albeit often grudgingly) go along with new methods for a period of six months and then, if no obvious results or benefits can be identified from their point of view, these same people will stop believing (if they ever did) that potential rewards will soon appear.

Six months is an exceedingly short time when projects are handled in parallel to regular tasks. The vaunted “trial period” may be shorter than many implementations when execution is handled internally, and contracting out requires adequate budgets and an ever expanding relationship with the contractor to achieve the desired ends within a short time period.

Bottom line: if implementation must succeed, sustained efforts (and money) must be provided to deliver quickly!~

© 2008 by François Gagnon

We can likely never reach a conclusion befitting the complexity of the following question: should we buy new equipment, replacing the “old”, or should we repair what is currently installed and already paid?

Problems from an operating cost quickly arise when from a matter of policy, no “new” expenditure can take place to pay for asset replacement: maintenance falls into a rut, incapable of effectively managing reliability, and the plant becomes overly expensive for such simple matters as aging (and obsolete or “too often repaired”) assets.

The case of the electric motor comes to mind. How often should a motor be repaired or rewound, excluding purely mechanical components such as a bearing replacement? Three repair cycles is generally recognized as the upper limit (some may disagree). What is the principal cost tied to the electric motor? Its purchase price? In fact, the cost of power consumption (and waste if inefficiencies accumulate) far exceeds the purchase price, or the difference in price between a high-efficiency electric motor and a relatively inefficient one.

Failure to evaluate (or reassess in cases where the original evaluation was made years in the past) the true costs of operation tied to electric motors lead to unreliable operation and stupendously superior energy expenditures. The breakpoint of “buy new” versus “operate the inefficient” is reached much sooner than most people intuitively assess. Therefore, the payback period of such a project as buying a new motor must be set at a time-period enabling plant cost viability. Is 3 months too long a payback? Is the plant not going to stay in operation for years to come? Worse is the cumulative effect of spreading the “disease” to a large population of motors and eventually facing huge cost overruns that can then only be addressed by massive injections of capital instead of dealing with this issue progressively and constantly during the plant’s life.

“In this business climate, we know not how long we will continue production!” seems to be a common concern, but since usable assets would likely be shipped to a more viable site, the expense still holds as a reasonable approach.

© 2008 by François Gagnon

Numerous experts report the undeniable absolute necessity of management conviction and dedication for reliability efforts to result in a proper and sustained “field” (that would be the plant floor) implementation. No argument could possibly otherwise convince us or our readers. We agree on something.

Why then do we see a generalized backtracking to antiquated methods or unwitting feeble returns from reliability approaches? Where is this management commitment when reports from the field indicate reliable methods get implemented and then seem to vanish into thin air or quickly get set aside? Why is apparent regression almost inevitable?

What some may fail to mention is the capital importance of fundamentals. And these essentials may escape most of the “business model improvement” proponents due to a simple and quite ugly fact: the “business” people rarely speak with the technical personnel who get the maintenance train on track and keep it there. And when they do, as they are often used to speaking very different languages, these parties may have limited exchanges or communications due to the different focus or interests they manifest.

The communication gap may be further aggravated by a largely false perception in head offices that the technical people remain uneducated. Nowadays, their credentials and pertinent experience may even at times exceed those of decision makers. This is not to criticize anyone: the preceding merely attempts to state occasionally occurring (and previously encountered) circumstances.

The predictive maintenance and condition-based approach to maintenance and reliability are vital to success. Yet, these facets of maintenance and engineering have been in place for some time, with often poor to moderate results (the author is being kind; so many PdM or CBM programs are hobbled structurally and technically that their returns can only be qualified as hobbled). The promise of fabulous returns can not be met when the program is not “fed” properly: investment, education (training at ALL levels) and sensible recognition of efforts, to name but a few factors too often missing from the final recipe…

What makes you think that doing the same thing in the same way will now yield a better result? What will now be done to properly adjust the targeting? The liabilities (or problems) and personnel are the same. Or personnel keeps changing in turnstile-mode.

Of course, critics might glumly reply “Have you not been part of the system that created the ineffectiveness we must now endure?”, a pertinent albeit biased question. We propose a viable working platform or product to our clients. We might express it as “we sell a car”. The client then plays pick and choose, dismantling the platform to purchase (allegorically) the two left-side wheels, one rear bumper, and parts of the engine, instead of buying the whole functional vehicle. The reasons are many and they feel justified in this purchasing approach: they already have two right-side wheels (of a different size), one bumper and engine parts (likely mixing centimeters and inches), so they feel they can reassemble a working whole. The truth seems to point to “wishful thinking”.

An example? Some years back as I instructed a Vibration Analysis 1 course for one of the main vendors in our field of endeavor, two technicians showed up from an automotive parts manufacturing plant. They expressed their concerns relative to the course, having discussed with their supervisor what they felt was their need for training (they would have been more comfortable with an introductory course instead of the one they were now to attend). I assured them of my availability over lunch and after regular hours should they face serious hurdles, and also told them I ran a very open classroom where questions were welcome at any time. This can be helpful, but if fear of ridicule and timidity become the governing concern of the puzzled, our best efforts to remain available yield little in the way of improved comprehension. At any rate, they never availed themselves of the repeatedly tendered “extra” support or semi-private sessions.

Most Level 1 courses clearly state a need for 6 months prior experience and/or having attended an introductory class. These two participants were lacking in both respects. Net result: come evaluation time, these two felt that the vendor offering this training was only interested in revenue and they never should have been “allowed” to attend that course.

Everybody is entitled to an opinion. Ours would differ slightly: in the hopes of saving some training dollars, their supervisor sent these participants to a course that was above their current reach. In so doing, he wasted more training dollars than he saved. He also exposed his technicians to a little discouragement, and lower motivation due to perceived difficulties.

Could the problem have been resolved right then and there by using a different approach? Course contents did not lend itself to a quick readjustment: other participants quite liked that course and got what they came for, but then, they had the necessary bases to absorb the curriculum.

To the previous example, we should also add the unpopularity of introductory courses in certain areas of the world. The “client” (purchasing or management) feel them to be a reach for more $$$, when in fact, the participant get swamped with too much material when attending the “chosen” (not by them) higher-level course.

Worse yet, in those same areas, when a certification exam is faced at the end of a week’s training, some participants have at times been warned that failure would equate dismissal. Sitting (or writing) an exam that is meant to cull the untrained may dauntingly challenge the neophyte.

Another sad hurdle to reliability excellence remains the discrepancy in pay rate and benefits afforded those who practice it adequately. Sooner or later, if competent technical personnel find they may be given better opportunities elsewhere, they will jump ship and seek out better climes. There are management or HR theories about pay scales and bonuses (this writer will purposely stay away from them as readers might be offended by psychological aspects of remuneration), but an occasional carrot, such as two checks waiting in the wings (gold and silver medals, if you wish) might yield surprising competitive benefits. Or setting PdM program goals and tying a bonus to meeting those targets.

Proactive engineering steps used hand in hand with precision maintenance yield better reliability. The latter is undeniable. Yet, without a strong predictive program, above and beyond any scheduled preventive replacements (likely arising from an RCM study) and inspections, production and asset reliability will remain out of reach.

PdM / CBM or Condition-Monitoring ARE the technical foundation that can be encouraged, but not managed at any level other than that of maintenance and engineering. In other words, if reliability is a fortification against trouble and decay and a guarantee of productivity, the walls or battlements depend on solid groundwork called predictive maintenance.

Simply put, Asset Reliability (and maintenance) can not be driven by failure-detection if predictive efforts remain incapable of perceiving faults.

© 2008 by François Gagnon

Where does vibration come from? What causes it? Any force changing in direction, changing in magnitude or any active component interaction generating a rub even as minimal as friction within rolling element bearings or moving fluids within pipes will cause vibration movement of some small to intolerable amplitude. Any combination of the previous would generate more complex vibration patterns. In practical terms, this means a long list of potential sources whenever an analyst tries to quantify and/or decompose machinery and structure behavior.

The (presumably, unless something escapes this writer) full list breaks down into:

Rotor related sources (rotor behavior and forces at play)

- unbalance

- static or force, couple, dynamic or combined

- misalignment, residual, growth-related or dynamic (reactionary)

- angular, parallel and combined

- bent shaft

- rubs

- macro rub

- rotor-casing

- rotor-product or moved fluid (when dense or solid)

- shaft-seal

- shaft-sleeve bearing

- gear coupling-jaws

- improperly lubricated gears

- micro rub

- belt-pulley

- sliding (instead of rolling) elements

- rolling elements themselves onto raceways (through lubricant film)

- pumping action or film-creation action within the bearing

- rolling elements and retaining cage

- fluid and casing or piping

- eccentricity

- whirl (of shaft or of the shaft within a fluid-film bearing) and whip

- gyroscopic effects (fairly common in inertia wheels)

- torsional vibration

Process related sources (what the machine does)

- hydraulic or aerodynamic forces

- blade / vane pass (BPF) or blade rate (BRF) vibration

- eccentricity relative to casing

- rotor mesh (lobes or screws)

- cavitation, recirculation, turbulence, stonewalling, surging, stalling

- compressed fluid wave or pulse (pipes, etc), turbulent flow

- reciprocating forces (can come close to shock)

- shock (presses, etc)

Drive related sources
Electromagnetic torque pulses from a motor and the interaction between armature and stator components a.k.a. rotor-bar and slot pass frequency
Pulses used to recreate Variable Frequency altered electrical line frequency
Pole or coil pass frequency
Magnetic centering
Coupling problems (lock-up, wear, etc)
Belt or chain drive w. eccentricity, belt problems, belt slip, cogs
Gear mesh and gear problem related vibration
Couple transmission discontinuities or variability from load transmission from one tooth to the next (simplified to picture the matter)
Hydraulic or aerodynamic forces from gas, steam or water turbines
BPF (Blade Pass Frequency) from turbines
BRF (Blade Rate) interaction between blades and stationary elements
Reciprocating forces from engines, unbalanced cam action

Other factors may cause the appearance or perception of an excessive vibration problem, but they are REACTIONS to one or more of the above sources as opposed to being themselves a source of vibration. The most easily recognized of these are looseness and resonance. Critical speeds of a rotor could be assigned to resonance for purposes of this listing. Oil whirl on sleeve bearings also fit into this category: it is an instability reaction due to lack of static load or dynamic loads overcoming static load. In this latter case, increased tolerances facilitate overcoming the static load. From the point of view of reactions, we can also add:

Reactive Problems

- dynamic misalignment (occurring from loads moving component positions)

- resonance

- looseness (really a change in response due to lessened stiffness)

- instability (rotor, hydraulic, oil film, other)

- base and retaining / supporting mechanism or structural problems

- distortion from pipe strain

- transmitted vibration (structure borne transmission from other nearby machines)

- acoustic excitation (airborne or structure borne noise exciting a plate, casing or other component; structure borne usually or closely falls under transmitted vibration)

© 2005, 2006, 2007, 2008 by François Gagnon

“The society that scorns excellence in plumbing, because plumbing is a humble activity, and tolerates shoddiness in philosophy, because philosophy is an exalted activity, will have neither good plumbing nor good philosophy - neither its pipes nor its theories will hold water.”
–John Gardner, former Secretary of HEW

Lorsqu’en présence d’un moteur assez puissant, prenez gare à l’interaction entre l’aimant du capteur et le champ magnétique environnant ; elle peut mener à l’altération des mesures et dans les pires cas, peut conduire à un faux diagnostic. La présence ou l’importance de l’interaction peut s’évaluer en rapprochant le capteur de sa « cible » (sans avoir de contact) et en regardant en temps réel la forme d’onde temporelle ou le spectre FFT.

L’expert saura travailler aussi bien en échelle linéaire qu’en échelle logarithmique. Le linéaire présente un portrait analytique plus compréhensible (particulièrement pour le débutant), mais l’échelle log prendra toute son importance dans le diagnostic avancé ou pour les cas d’éloignement entre la sonde et la source.

Gardez toujours en tête que le spectre FFT est une réduction de l’information contenue dans la forme d’onde temporelle, et que la forme d’onde elle-même ne contient PAS obligatoirement toute l’information pertinente ou désirable, selon ses paramètres (sélectionnés par l’usager) relativement au phénomène mesuré.

Nettoyez régulièrement les aimants et assurez vous de la propreté de la cible (endroit du montage). Ne laissez pas non plus le câble ballotter au vent. N’imposez pas au câble de tension, et si vous devez absolument le faire, assurez vous que cette tension soit uniforme / constante.

L’aimant ne sert pas toujours : des matériaux non-magnétiques peuvent demander l’utilisation d’un contact direct entre capteur et point de mesure. Il est important de se rappeler qu’il est préférable d’éviter de d’exposer ses mains à de fortes amplitudes de vibration qui peuvent à la longue susciter des problèmes. Le port d’un gant ou d’un gant de caoutchouc réduira cette incidence dans la plupart des cas. C’est le HAV ou Hand-Arm Vibration.

Certains systèmes offrent l’interpolation et d’autres pas. Dans le cas d’une fenêtre Hanning (le choix habituel), l’erreur d’amplitude sur une crête dans le spectre peut atteindre 16%. Selon la position de la crête par rapport aux « lignes » du spectre FFT, l’erreur se situera donc entre 0% (une crête parfaitement centrée par rapport à la ligne) et 16% (une crête à cheval sur le seuil de deux lignes avoisinantes). Le spectre FFT interpolé élimine cette erreur. (Voir le conseil suivant)

Un moteur asynchrone (le plus commun) n’est presque JAMAIS véritablement à RPM fixe puisque le glissement dépend de la charge et la charge n’est que rarement parfaitement fixe. Donc, les crêtes se promènent sur une « toile de fond » fixe (les paramètres du spectre FFT). En balayant ainsi une petite plage de fréquence (selon les variations), la crête se déplace par rapport aux lignes et une amplitude CONSTANTE se PERCEVRA comme altérée : la crête change de place, et selon sa position en fréquence, l’erreur sera plus ou moins importante. Donc, d’une collecte à l’autre, les amplitudes montent et/ou descendent au selon la charge. L’interpolation (si elle est présente et qu’elle est utilisée) règle la question.

Dans le cas d’un test d’acceptation, hormis la calibration qui prend alors une importance particulière, les considérations énoncées dans les deux conseils précédents revêtent une importance toute particulière. L’interpolation pourra nous débarrasser de l’erreur de la fenêtre Hanning. Sinon, il faudra utiliser une fenêtre Flat Top pour s’assurer que les amplitudes (qui autrement seraient souvent altérées à la baisse) ne dépassent pas les seuils tolérés.

© 2008 by François Gagnon

…or at least it shouldn’t be! Vibration analysis corresponds to a science. Of course, the art and science of getting the proper measurement from the pertinent location(s) with adequate instruments before performing knowledgeable signal processing (if needed) also come into play, but the analytical part mostly relies on relatively simple notions or assumptions while reviewing fairly simple data.

We regularly hear about what we would deem failed predictive approaches where a lack of training or a lack of expertise seek dismantling and inspection of machinery components instead of proper analysis leading to an accurate diagnosis of the problem at hand. This approach amounts to bad (and costly) predictive maintenance management. It also favors extraneous manipulation of machine components best left alone when considering the potential human-error factor linked to intrusion (equivalent to resetting the bathtub or other curve to the infant mortality phase). Precision maintenance mitigates the previous factor, but then, it is a rare case indeed to see precision practices in a context where condition-monitoring fails to go hand-in-hand with proper diagnostics.

© 2007 by François Gagnon

Confusion reigns with respect to machinery vibration issues. Most people still hang on to vibration as a problem, instead of the diagnostic science of vibration as an indication of a developing problem.

Where does the difference lie? Vibration as a problem per say falls more in the AMPLITUDE analysis category, and remains blatantly obvious in most cases. Excessive vibration levels can be directly linked to unbalance, severe misalignment, resonance (or rotor critical speed problems) and other perceptibly notable behaviors, such as what might be exhibited by a machine or component having failed or well-advanced in its failure mode. Vibration as an indication of a problem tends to be a FREQUENCY (or time waveform contents) analysis issue. Of course, the appearance or growth of a small peak may bring us back into an amplitude context, and small amplitudes often show severe problems. Our vibration measurement will reveal anomalies or abnormalities that could yield catastrophes. The apparent insignificance of some amplitudes may well be linked to the location of the problem relative to measurement point, slow speeds, difficultly transmitted phenomena (ex: an incipient inner race problem must send the vibration wave through two thicknesses of lubricating fluid, above and below the rotating element which must also be traversed to then transmit to the outer race and subsequently, the pillow block: a long trajectory for a tiny peak lost amidst other events and noise) and other barriers to our perception. We’ll remind the reader that we advocate learning to look at data both in linear and logarithmic scales to familiarize and sharpen the analytical sense when interpreting more difficult or “veiled” problems.

The seasoned analysis veteran likely knew all of the above. But the newcomer or the merely distant onlooker (receiving reports as opposed to performing predictive tasks) may now realize that vibration is not just about crankshaft-like motion.

© 2007 by François Gagnon

We often hear the words “change management” as an adjunct to reliability efforts. Yet, if one is to trust reports of reliability effort failures and abandonment, or reversal / devolution to earlier methods (or lack thereof), something must surely be going awry in the way we attempt to do things.

Change can be good, and it is inevitable, but too much change at the same time overwhelms personnel. A new approach to data input into the CMMS or EAM requires training and a little time for old (and usually inadequate) habits to get reformed. If management simultaneously modifies a whole list of other things, the chance of success in implementation suffers a considerable negative impact.

We are all too aware of the existence of resistance to change. “Better” must be demonstrated and proven before wholehearted adoption can take place. And criticism along the way will likely occur. The arguments of “bad faith” and “you’re resisting the change” usually point to bad implementation (key word would be usually: some people will just reject anything new out of hand).

 As an example, I am reminded some 15 years back of the arrival of a software package for vibration-based condition monitoring. One of the (or perhaps just “the”) first operating on a Windows platform. It was pretty. It was easy to use. But its failings lay entirely in technical contents (or lack thereof): you could not do (at release) what had been common fare with the DOS version. As a matter of fact, I’m not entirely sure the final version could either, but that’s another story. Comments with respect the technical deficiencies or missing functions brought annoyed replies implying “resistance to change”. Was that the case? The passage to Windows and its GUI were good, no doubt. An SQL database was also a much needed improvement. The price to pay was high: the loss of technical contents needed to properly assist the analyst proved contentious for a long time.

The problems encountered while managing change often arise from a lack of understanding (or even caring) of the needs of all parties involved in the execution of the mission (production, maintenance, other). Things work out better when all parties are consulted BEFORE an initiative launches, and that means all parties at all locations of an organization (the needs, or the level of change, may differ considerably). When scepticism arises or when questions are asked, one needs to confront them head on, with pertinent answers.

Bottom line: enthusiasm and the embrace of movelty may be formidable drivers, but if the homework has not been done to convince others, support their needs and address their concerns, reliability (and other) initiatives may fail, with regressions, dismal results (in ROI terms), or simple failure to launch properly.

© 2007 by François Gagnon 

Much has been said as to the “key importance” of data from past data collections and how much this data should be kept for future reference. Is this really the case? What, in fact, is of primordial importance, and what might simply be done away with, given a little reflection on the matter?

Most vibration data becomes quickly irrelevant, UNLESS it contains pertinent traces or indications of a developing problem. A ceaseless repetition of waveforms and spectra showing minute and harmless change simply clutters a database, but most PdM software fails to adopt a design enabling quick and accurate management of such issues.

We want baselines. We want them to be accurate not only in terms of resolution, but also in terms of machine operation (load, temp, product, etc.) documentation. Multiple baselines helps us considerably, inasmuch as we may then assign different operating-conditions or perhaps post-maintenance (repair, replacement, etc.) “slots” to these reference measurements. We probably want these to be accessible in multiple parameters. Baselines are, so to speak, a “keeper” in the context of this article.

Regular, run-of-the-mill, “no defect found” data should be considered as having a limited shelf life. Identical spectra within a waterfall (or cascade) take up space for no good reason. They do, however, provide continuance of a pattern, which could easily be managed as a “replicator” function once time proves that no review is forthcoming (reviewing or self-auditing of data should occur when a failure occurs in spite of no defect having been detected by the predictive measurements, their programming and/or the analyst’s assessment of such data). Any changes to the measurement set-up should be documented as well, particularly if a change arises from the conclusions brought about by an investigation in an undetected developing failure or “crash”.

A predictive maintenance program accumulates a knowledge-base that seemingly, and quite sadly, evaporates over time. The principal cause for the volatility of this knowledge rests in the inability to “grab” a data set from a specfic date (or successive dates when trends are relevant) and form a diagnostic subset. In fact, it has long been my recommendation to our clients to keep a book of problems detected (and a hardcopy of the pertinent data) on monitored assets, simply because it becomes a critical reference for the future and a BRIDGE to pass the program over to somebody else if and when the analyst is ever called away from this condition-monitoring posting.

The answer to any question implicating old data relevance becomes obvious. Measurement set-ups, baselines, measurement reviews, problem identification documentation form the basis for a reference book that will over the years become a fabulous treasury, a fountain of wisdom for both the technicians and analysts involved in PdM work and management. Except for the previous and recent, still believed to be time-relevant to potential review, data, all the other accumulating data creates unnecessary and unwanted clutter.

© 2007 by François Gagnon