The supply of electricity is important in modern society, so the outages of the electric grid should be few and short, especially for the transmission grid. A summary of the history of the Swedish electrical system is presented. The objective is to be able to plan the maintenance better by following the condition of the equipment. The risk matrix can be used to choose which component to be maintained. The risk matrix is improved by adding a dimension, the uncertainty of the probability. The risk can be reduced along any dimension: better measurements, preventive maintenance or more redundancy. The number of dimensions can be reduced to two by following iso-risk lines calculated for the beta distribution. This thesis lists twenty surveys about circuit breakers and disconnectors, with statistics about the failures and the lifetime. It also presents about forty condition-measuring methods for circuit breakers and disconnectors, mostly applicable to the electric contacts and the mechanical parts. A method for scheduling thermography based on analysis of variance of the current is tried. Its aim is to reduce the uncertainty of thermography and it is able to explain two thirds of the variation using the time of the day, the day of the week and the week number as explanatory variables. However, the main problem remains as the current is in general too low. A system with IR sensors has been installed at the nine contacts of six disconnectors with the purpose of avoiding outages for maintenance if the contacts are in a good condition. The measured temperatures are sent by radio and regressed against the square of the current, the best exponent found. The coefficient of determination $R^2$ is high, greater than 0.9. The higher the regression coefficient is, the more heat is produced at the contact. So this ranks the different contacts. Finally a framework for lifetime modelling and condition measuring is presented. Lifetime modelling consists in associating a distribution of time to failure with each subpopulation. Condition measuring means measuring a parameter and estimating its value in the future. If it exceeds a threshold, maintenance should be carried out. The effect of maintenance of the contacts is shown for four disconnectors. An extension of the risk matrix with uncertainty, a survey of statistics and condition monitoring methods, a system with IR sensors at contacts, a thermography scheduling method and a framework for lifetime modelling and condition measuring are presented. They can improve the planning of outages for maintenance. Finally a framework for lifetime modelling and condition measuring is presented. Lifetime modelling consists in associating a distribution of time to failure with each subpopulation. Condition measuring means measuring a parameter and estimating its value in the future. If it exceeds a threshold, maintenance should be carried out. The effect of maintenance of the contacts is shown for four disconnectors. An extension of the risk matrix with uncertainty, a survey of statistics and condition monitoring methods, a system with IR sensors at contacts, a thermography scheduling method and a framework for lifetime modelling and condition measuring are presented. They can improve the planning of outages for maintenance. / Elförsörjningen är viktig i det moderna samhället, så avbrotten bör vara få och korta, särskilt i stamnätet. En kortfattad historik över det svenska elsystemet presenteras. Målet är att kunna planera avbrotten för underhåll bättre genom att veta mera om apparaternas skick. Det är svårt att planera avbrott för underhåll och utbyggnad. Riskmatrisen är verktyg för att välja vad som ska underhållas och den kan förbättras genom att lägga till en dimension, sannolikhetens osäkerhet. Risken kan minskas längs med varje dimension: bättre mätningar, förebyggande underhåll och mer redundans. Antalet dimensioner kan igen bli två genom att följa linjer med samma risk, som är beräknade för betafördelningen. Denna avhandling tar upp tjugo studier av fel i brytare och frånskiljare med data om felorsak och livslängd. Den har också en översikt av ett fyrtiotal olika metoder för tillståndsmätningar för brytare och frånskiljare, som huvudsakligen rör de elektriska kontakterna och de mekaniska delarna. Ett system med IR sensorer har installerats på de nio kontakterna på sex frånskiljare. Målet är att minska antalet avbrott för underhåll genom att skatta skicket när frånskiljarna är i drift. De uppmätta temperaturerna tas emot genom radio och behandlas genom regression mot kvadraten av strömmen, då den bästa exponenten för strömmen visade sig vara 2,0. Förklaringsfaktorn $R^2$ är hög, över 0,9. För varje kontakt ger det en regressionskoefficient. Ju högre koefficienten är, desto mer värme utvecklas det i kontakten, vilket kan leda till skador på materialet. Koefficienterna ger en rangordning av frånskiljarna. Systemet kan också användas för att minska eller öka den tillåtna strömmen baserat på skicket. Slutligen förklaras ett ramverk för livslängdsmodellering och tillståndsmätning. Livslängdsmodellering innebär att koppla en fördelning för tiden till fel med varje delpopulation. Med tillståndsmätning avses att mäta en parameter och skatta dess värde i framtiden. Om den överskrider en tröskel, måste apparaten underhållas. Effekten av underhåll visas för fyra frånskiljare. En utveckling av riskmatrisen med osäkerheten, en sammanställning av statistik och metoder för tillståndsövervakning, ett system med IR-sensor vid kontakerna, en metod för termografiplanering och ett ramverk för livslängdsmodellering och tillståndsmätningar presenteras. De kan förbättra avbrottsplaneringen. / El suministro de energía eléctrica es importante en la sociedad moderna. Por eso los cortes eléctricos deben ser poco frecuentes y de poca duración, sobre todo en la red de transmisión. Esta tesis resume la historia del sistema eléctrico sueco. El objetivo es planificar los cortes mejor siguiendo la condición de los aparatos. La matriz de riesgo se utiliza muchas veces para escoger en qué aparatos debería realizarse mantenimiento. Esta matriz se puede mejorar añadiendo una dimensión: la incertidumbre de la probabilidad. El riesgo puede ser disminuido siguiendo cada una de las tres dimensiones: mejores mediciones, mantenimiento preventivo y mayor redundancia. El número de dimensiones puede reducirse siguiendo líneas del mismo riesgo calculadas para la distribución beta. Esta tesis presenta veinte estudios de fallos en interruptores y seccionadores con datos sobre la causa y el tiempo hasta la avería. Contiene también una visión general de cuarenta métodos para medir la condición de seccionadores e interruptores, aplicables en su mayoría a los contactos eléctricos y los componentes mecánicos. Se ha instalado un sistema con sensores infrarrojos en los seis contactos de nueve seccionadores. El objetivo es disminuir los cortes de servicio para mantenimiento, estimando la condición con el seccionador en servicio. Las temperaturas son transmitidas por radio y se hace una regresión con el cuadrado de la corriente, ya que el mejor exponente de la corriente resultó ser 2,0. $R^2$ alcanza un valor de 0,9 indicando un buen ajuste de los datos por parte del modelo. Existe un coeficiente de regresión para cada contacto y este sirve para ordenar los contactos según la necesidad de mantenimiento, ya que cuanto mayor sea el coeficiente más calor se produce en el contacto. Finalmente se explica que el modelado de tiempo hasta la avería consiste en asignar una distribución estadística a cada equipo. La monitorización del estado consiste en medir y estimar un parámetro y luego predecir su valor en el futuro. Si va a sobrepasar un cierto límite, el equipo necesitará de mantenimiento. Se presenta el efecto de mantenimiento de cuatro seccionadores. Un desarrollo de la matriz de riesgo, un conjunto de estadísticas y métodos de monitoreo de condición, un sistema de sensores IR situados cerca de los contactos, en método de planificación de termografía y un concepto para explicar la modelización de tiempo hasta la avería y de la monitorización de la condición han sido presentados y hace posible una mejor planificación de los cortes de servicio. / <p>QC 20170928</p>

Significant advances in wind turbine technology have increased the need for maintenance through condition monitoring. Indeed condition monitoring techniques exist and are deployed on wind turbines across Europe and America but are limited in scope. The sensors and monitoring devices used can be very expensive to deploy, further increasing costs within the wind industry. The work outlined in this thesis primarily investigates potential low-cost alternatives in the laboratory environment using vibration-based and modal testing techniques that could be used to monitor the condition of wind turbine blades. The main contributions of this thesis are: (1) the review of vibration-based condition monitoring for changing natural frequency identification; (2) the application of low-cost piezoelectric sounders with proof mass for sensing and measuring vibrations which provide information on structural health; (3) the application of low-cost miniature Micro-Electro-Mechanical Systems (MEMS) accelerometers for detecting and measuring defects in micro wind turbine blades in laboratory experiments; (4) development of an in-service calibration technique for arbitrarily positioned MEMS accelerometers on a medium-sized wind turbine blade. This allowed for easier aligning of coordinate systems and setting the accelerometer calibration values using samples taken over a period of time; (5) laboratory validation of low-cost modal analysis techniques on a medium-sized wind turbine blade; (6) mimicked ice-loading and laboratory measurement of vibration characteristics using MEMS accelerometers on a real wind turbine blade and (7) conceptualisation and systems design of a novel embedded monitoring system that can be installed at manufacture, is self-powered, has signal processing capability and can operate remotely. By applying the conclusions of this work, which demonstrates that low-cost consumer electronics specifically MEMS accelerometers can measure the vibration characteristics of wind turbine blades, the implementation and deployment of these devices can contribute towards reducing the rising costs of condition monitoring within the wind industry.

Monitoring and controlling smart grid assets in a timely and reliable manner is highly desired for emerging smart grid applications. Wireless Sensor Networks (WSNs) are anticipated to be widely utilized in a broad range of smart grid applications due to their numerous advantages along with their successful adoption in various critical areas including military and health care. Despite these advantages, the use of WSNs in such critical applications has brought forward a new challenge of ful lling the Quality of Service (QoS) requirements of these applications. Providing QoS support is a challenging issue due to highly resource constrained nature of sensor nodes, unreliable wireless links and harsh operation environments. In this thesis we critically investigate the problem of QoS provisioning in WSNs. We identify challenges, limitations and requirements for applying QoS provisioning for WSNs in smart grid applications. We nd that the topic of data prioritization techniques at the MAC layer to provide delay bounds in condition monitoring applications is not well developed. We develop six novel QoS schemes that provide data di erentiation and reduce the latency of high priority tra c in a smart grid context. These schemes are namely; Delay-Responsive Cross layer (DRX), Fair and Delay-aware Cross layer (FDRX), Delay-Responsive Cross layer with Linear backo (LDRX), Adaptive Realistic and Stable Model (ARSM), Adaptive Inter-cluster head Delay Control (AIDC) and QoS-aware GTS Allocation (QGA). Furthermore, we propose a new Markov-based model for IEEE 802.15.4 MAC namely, Realistic and Stable Markovbased (RSM). RSM considers actual network conditions and enhances the stability of the WSNs. We show through analytical and simulation results that all of the presented schemes reduce the end-to-end delay while maintaining good energy consumption and data delivery values.

Submitted by Fabio Sobreira Campos da Costa (fabio.sobreira@ufpe.br) on 2016-04-13T12:14:28Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Henrique Azevedo - Tese de Mestrado - Finalizada_Rev13_Hen_Alex_Nad_Rob_ABNT_Gus_Bib-1.pdf: 2536238 bytes, checksum: 092410d49ebfec82ff6f89b7a23f93e3 (MD5) / Made available in DSpace on 2016-04-13T12:14:28Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Henrique Azevedo - Tese de Mestrado - Finalizada_Rev13_Hen_Alex_Nad_Rob_ABNT_Gus_Bib-1.pdf: 2536238 bytes, checksum: 092410d49ebfec82ff6f89b7a23f93e3 (MD5) Previous issue date: 2015-08-28 / Desde a década de 1980, a tecnologia de energia eólica sofreu um imenso crescimento em relação tanto ao tamanho da turbina quanto à capacidade instalada a nível mundial. Como a demanda por turbinas eólicas de grande escala e de custo mais baixos de operação e manutenção continua a crescer, o interesse nos sistemas de monitoramento de condição (CMS, do inglês Condition Monitoring System) tem aumentado rapidamente. Os principais componentes (MC, do inglês Main Components) das turbinas eólicas são o foco de praticamente todos CMS já que eles provocam um elevado custo de reparo e tempo de parada. Entretanto, uma grande parte das falhas em MC é causada por danos secundários devido a uma falha de um subcomponente. O objetivo deste trabalho é apresentar e propor um método de análise para identificar defeitos em componentes principais ou subcomponentes de uma turbina eólica. O método de análise proposto se baseia em técnicas de sinais temporais de vibração, nas transformadas rápidas de Fourier e análises envelope obtidas através da transformada de Hilbert. A aplicação do método, em uma turbina eólica instalada em um parque eólico real, permitiu a identificação, com sucesso, de um defeito no rolamento, o qual foi substituído confirmando a falha. / Since the decade of 1980s, wind energy technology has undergone tremendous growth over both turbine size and worldwide installed capacity. As the demand for wind turbines of large-scale and lower cost of operation and maintenance continues to grow, interest in condition monitoring system (CMS) has increased rapidly. The main components (MC) of the wind turbines are the focus of almost all CMS since they cause a high repair cost and downtime. However, a large portion of the MC faults are caused by secondary damages due to a subcomponent failure. The objective of this work is to present and propose a method of analysis to identify defects in major components or subcomponents of a wind turbine. The proposed analysis method is based on time wave analysis, fast Fourier transforms analysis and envelope analysis through Hilbert transforms. The application of the method in a wind turbine installed in a real wind farm, identified a bearing defect successfully, which was replaced confirming the failure.

Most drill wear monitoring research found in the literature is based on conventional vibration technologies. However, these conventional approaches still have not attracted real interest from manufacturers for multiples of reasons: some of these techniques are not practical and use complicated Tool Condition Monitoring (TCM) systems with less value in industry. In addition, they are also prone to give spurious drill deterioration warnings in industrial environments. Therefore, drills are normally replaced at estimated preset intervals, sometimes long before they are worn or by expertise judgment. Two of the great problems in the implementation of these systems in drilling are: the poor signal-to-noise ratio and the lack of system-made sensors for drilling, as is prevalent in machining operations with straight edge cutters. In order to overcome the noise problems, many researchers recommend advanced and sophisticated signal processing while the work of Rehorn et al. (2005) advises the following possibilities to deal with the lack of commercial system-made sensors:  Some research should be directed towards developing some form of instrumented tool for drill operations.  Since the use of custom-made sensors is being ignored in drilling operations, effort should be focused on intelligent or innovative use of available sensor technology. It is expected that the latter could minimize implementation problems and allows an optimal drill utilization rate by means of modern and smart sensors. In addition to the accelerometer sensor commonly used in conventional methods, this work has considered two other sensor-based methods to monitor the drill wear indirectly. These methods entail the use of an instrumented drill with strain gauges to measure the torque and the use of an encoder to measure the Instantaneous Angular Speed (IAS). The signals from these sensors were analyzed using signal processing techniques such as, statistical parameters, Fast Fourier Transform (FFT), and a ii preliminary Time-Frequency (TF) analysis. A preliminary investigation has revealed that the use of a Regression Analysis (RA) based on a higher order polynomial function can very well follow and give prognosis of the development of the monitored parameters. The experimental investigation has revealed that all the above monitoring systems are sensitive to the deterioration of the drill condition. This work is however particularly concerned with the use of IAS on the spindle of the drill, compared to conventional monitoring systems for drill condition monitoring. This comparison reveals that the IAS approach can generate diagnostic information similar to vibration and torque measurements, without some of the instrumentation complications. This similitude seems to be logical, as it is well known that the increase of friction between the drill and workpiece due to wear increase the torque and consequently it should reduce or at least affect the spindle rotational speed. However, the use of a drill instrumented with a strain gauge is not practical, because of the inconvenience it causes on production machines. By contrast, the IAS could be measured quite easily by means of an encoder, a tachometer or some other smart rotational speed sensors. Thus, one could take advantage of advanced techniques in digital time interval analysis applied to a carrier signal from a multiple pulse per revolution encoder on the rotating shaft, to improve the analysis of chain pulses. As it will be shown in this dissertation, the encoder resolution does not sensibly affect the analysis. Therefore, one can easily replace encoders by any smart transducers that have become more popular in rotating machinery. Consequently, a non-contact transducer for example could effectively be used in on-line drill condition monitoring such as the use of lasers or time passage encoder-based systems. This work has gained from previous research performed in Tool Condition Monitoring TCM, and presents a sensor that is already available in the arsenal of sensors and could be an open door for a practical and reliable sensor in automated drilling. iii In conclusion, this dissertation strives to answer the following question: Which one of these methods could challenge the need from manufacturers by monitoring and diagnosing drill condition in a practical and reliable manner? Past research has sufficiently proved the weakness of conventional technologies in industry despite good results in the laboratory. In addition, delayed diagnosis due to time-consuming data processing is not beneficial for automated drilling, especially when the drill wears rapidly at the end of its life. No advanced signal processing is required for the proposed technique, as satisfactory results are obtained using common time domain signal processing methods. The recommended monitoring choice will definitely depend on the sensor that is practical and reliable in industry. / Dissertation (MEng)--University of Pretoria, 2012. / gm2013 / Mechanical and Aeronautical Engineering / MEng / Unrestricted

This thesis is focus on monitoring state of machine parts that are under the most stress. Type of artificial intelligence used in this work is recurrent neural network and its modifications. Chosen type of neural network was used because of the sequential character of used data. This thesis is solving three problems. In first problem algorithm is trying to determine state of mill tool wear using recurrent neural network. Used method for monitoring state is indirect. Second Problem was focused on detecting fault of a bearing and classifying it to specific category. In third problem RNN is used to predict RUL of monitored bearing.

In this diploma thesis is elaborated design of diagnostic system for small jet engines. The aim is to describe the types of possible failures of jet engines, to determine important parameters characterizing the immediate state of engine and define methods for measurement of selected parameters. The first part is devoted to a description of selected types of small turbojet engines, followed by a summary of the most widely used diagnostic methods for assessing the health condition of the engine during operation. The next chapter contains calculation of the engine thermal cycle with characteristics of construction components. Then there is analysis of small jet engine failures with a description of their causes and possibilities of identification by diagnostic system. Thesis continues with a description of measurement methods and selection of the required sensors. Next chapter is focused on the proposed diagnostic system for condition monitoring of the engine. The last part is devoted to an excursion in laboratory for jet engine testing at the Technical University in Košice.

Machine tool components are widely used in many industrial applications. In accordance with their usage, a reliable health monitoring system is necessary to detect defects in these components in order monitor machinery performance and avoid malfunction. Even though several techniques have been reported for fault detection and diagnosis, it is a challenging task to implement a condition monitoring system in real world applications due to their complexity in structure and noisy operating environment. The primary objective of this thesis is to develop novel intelligent algorithms for a reliable fault diagnosis of machine tool components. Another objective is to use Micro Electro Mechanical System (MEMS) sensor and interface it with Raspberry pi hardware for the real time condition monitoring. Primarily knowledge based approach with morphological operators and Fuzzy Inference System is proposed, the e˙ectiveness of this approach lies in the selection of structuring elements(SEs). When this is evaluated with di˙erent classes of bearing fault signals, it is able to detect the fault frequencies e˙ectively. Secondarily, An analytical approach with multi class support machine is proposed, this method has uniqueness of learning on its own with out any prior knowledge, the e˙ectiveness of this method lies on selected features and used kernel for converging. Results have shown that RBF (Radial Bias Function) kernel, which is commonly known as gauss kernel has good performance in identifying faults with less computation time. An idea of prototyping these methods has triggered in using Micro Electro Mechanical System (MEMS) sensor for data acquisition and real time Condition Monitoring. LIS3DH accelerometer sensor is used for the data acquisition of spindle for capturing high frequency fault signals. The measured data is analyzed and compared with the industrial sensor k-shear accelerometer type 8792A.

Many dams existing today were constructed around fifty years ago. Condition monitoring is essential for maintaining high safety and determining the current level of safety and stability for these dams. There is a need for new monitoring techniques and finite element coupled monitoring could be one of these techniques. A concrete arch dam located in Sweden is modelled and calibrated with respect to concrete temperature measurements. The temperature distribution is then defined as a prescribed strain in a structural mechanical model in which a parametric study is performed. The results from the parametric study are compared to measurements of the crest deformation and a combination of parameters is found giving the lowest difference between measurements and model results for the mid-section. The results show that the finite element model can be used to predict the behavior of the dam with acceptable deviation. The parametric study indicates that the reference temperature of the concrete has little effect on the amplitude of the deformation and that the governing factor is the coefficient of thermal expansion. / Många av de dammar som finns idag byggdes för omkring femtio år sedan. Tillståndsövervakning är avgörande för att kunna bestämma nivån av säkerhet och stabilitet för dessa dammar. Det finns ett behov av ny övervakningsteknik och finita element-kopplad övervakning kan vara en av dessa tekniker. En betongvalvdamm modelleras och kalibreras med avseende på uppmätt betongtemperatur. Den beräknade temperaturfördelningen definieras sedan som en föreskriven töjning en strukturmekanisk modell i vilken en parametrisk studie utförs. Resultaten från parameterstudien jämförs med mätningar av kröndeformation och en kombination av parametrar identifieras som ger lägsta skillnad mellan mätningar och modellresultat för mittsektionen. Resultaten visar att modellen kan användas för att förutsäga dammens beteende med acceptabel avvikelse. Parameterstudien indikerar att referenstemperaturen för betongen har liten inverkan på amplituden för deformationen och att den styrande faktorn är längdutvidgningskoefficienten.

The choice of the topic addressed in this thesis aims to improve the service and maintenance on ceramic ball bearings in a specific test dynamometer and through an engineering approach develop tools for condition monitoring. The company connected to this thesis, AVL, is the world's largest privately owned company for development, simulation and testing technology of powertrains for passenger cars, trucks and large engines. Engine testing is a critical part of the business at AVL Sweden and unexpected bearing failure can result in long repair times and great economic losses due to loss of the testing time. In short terms, the methodological approach followed the following steps; first a thorough information retrieval regarding bearings and analysis was conducted. The search was deepened around areas such as hybrid ball bearings, bearing failure mechanisms, bearing defect frequencies, signal analysis and condition monitoring. After this a table for bearing damage detection was developed and a “step by step” guidance for condition monitoring. The tools where afterwards verified by simple testing to detect complications within the chosen system. The existing condition monitoring system that is used today revealed weaknesses as it lacked the feature of taking preventive measures. The system that is based on temperature measurements isn’t satisfactory enough, especially when it’s missing visual clarity. Service and maintenance according to specifications from the manufacturer should be scheduled to ensure operational and guarantees. Currently mounted accelerometers on the housing of the Dynas3 engine should be connected for collecting data and the total sum of energy should be calculated for simple monitoring of historical progression. This should be done by following the guidance in order to ensure proper data acquisition. The best way to implement condition monitoring showed to be by performing multi-parameter monitoring. The design of the condition monitoring system is highly connected to what to monitor and at what stage. One main consideration to keep in mind is that it’s very rare that manufacturing defects are the reason for bearing failure. Instead it derives from improper storage, transport, handling or dimensional errors and even in some cases by improperly implemented force analysis prior to bearing selection. / Huvudämnet som behandlas i detta examensarbete syftar till att förbättra service och underhåll på keramiska kullager i en viss testdynamometer och genom ett ingenjörsmässigt tillvägagångsätt utveckla verktyg för tillståndsövervakning. Företaget som är ansluten till detta examensarbete är AVL som är världens största privatägda företag för utveckling, simulering och testteknik för drivlinor för personbilar, lastbilar och stora motorer. Motorprovning är en viktig del av verksamheten vid AVL Sverige, och ett oväntat lagerhaveri kan leda till långa reparationstider och stora ekonomiska förluster på grund av utebliven test tid. I korta termer följde den metod som använts följande steg, först genomfördes en grundlig informationssökning om lager och tillhörande analyser. Efter det fördjupades sökande kring områden som hybrida kullager, lagerskademekanismer, frekvenser kopplade till lagerskador, signalanalys och tillståndsövervakning. Efter detta framställdes en tabell för detektering av lagerskador, samt en ”steg för steg” guide för tillståndsövervakning. Verktygen för tillståndsövervakning kontrolleras efteråt, genom att enkla tester genomfördes för att upptäcka komplikationer inom det valda systemet. Det övervakningssystem som används idag avslöjade svagheter genom att sakna funktionen att vidta förebyggande åtgärder. System som är baserat på temperaturmätningar är inte tillräckligt tillfredsställande, speciellt när det saknar en visuell tydlighet. Den service och underhåll som enligt tillverkarens föreskrifter påvisas bör planeras för att säkerställa drift och garantier. Nuvarande monterade accelerometrar fästa vid motorhöljet bör anslutas för att insamla data, och den totala summan av energin bör beräknas för en enkel övervakning av det historiska utvecklingsförloppet. Detta bör göras genom att följa de riktlinjer som framställts för att säkerställa korrekt datainsamling. Det bäst passande sättet att genomföra tillståndsövervakning på i detta fall visade sig vara att utföra multiparameterövervakning. Framställningen av tillståndsövervakningssystemet är starkt förknippat med vad som skall övervakas och i vilket skede. En huvudsaklig bidragande faktor att komma ihåg är att det är mycket ovanligt att fabrikationsfel är orsaken till lagerhaveri. Istället härstammar haveriet från felaktig förvaring, transportering, hantering eller dimensioneringsfel och i vissa fall av felaktigt genomförd kraftanalys inför lagerval.