M. Tech. (Mechanical Engineering) Vaal University of Technology / Monitoring the condition of equipment in industry is very important to prevent unplanned breakdowns and to prolong their life. This is necessary, since it is not always economically viable to stop equipment at regular intervals to do maintenance. Failure on machines can lead to high repair costs and production losses. It is thus of paramount importance that early failure symptoms be identified by means of condition monitoring. This study in the field of condition monitoring is performed to determine if the mechanical shock values induced in defect bearings could be used to measure the condition of a bearing while operating under variable speed and variable load. Variable speed and variable load is becoming more popular in industry because variable speed drives applications ensure effective process control. Variable speed application, cause fault frequencies to fluctuate and therefore vibration applications for constant speed applications, which are speed-dependent, can no longer apply. Vibration-monitoring techniques that have applied for many years have now become obsolete in these variable speed applications. Methods such as Short Time Fourier Transformation (STFT), time scale like wavelet transform, and Order tracking has been applied in variable speed applications with some success. These methods analyses the vibration phases on the signal buy compensating for the speed changes. In this thesis, the Shock pulse method is selected as the analyses tool to measure the mechanical shock. Shock pulse monitoring does not focus on the vibration phases but measures in a small-time window when mechanical shocks are induced in the bearing material before the vibration phase. There is very little documented research in the field of mechanical shock pulse monitoring for conditions of variable speed and variable loads, and therefore this research focuses on recording these mechanical shock values by empirical tests. The tests were performed on a bearing with an induced defect on the outer race. The rolling element of the bearing strikes the defect and the mechanical shock value (dBsv) is measured. The mechanical shock is measured with the Shock pulse method in a small-time window before vibration occurs. In this time window, the dBsv is recorded over time to provide diagnostic information of the bearing during acceleration, deceleration and various loading conditions. These mechanical shocks are elastic waves that mirror the impact-contact-force's time function and the Shock pulse monitoring accelerometer, which is tuned to 32 kHz, will respond to the elastic wave fronts with transient amplitudes proportional to the square of the impact velocities. The mechanical shock values were analysed and reoccurring fault levels were identified on each empirical test. These recurring events from the empirical tests were used as primary data for analysis in this research. These tests were performed on a bearing with an induced failure and it was found that the dBsv measured over time could not be used to monitor the condition of the bearing under variable speed applications. This was because the dBsv changed as the speed increased. To overcome this problem Sohoel’s theory was applied and the initial mechanical shock value (dBi) was calculated for the bearing. The dbi value was subtracted from the dBsv and a value called the maximum mechanical shock value (dBm) was obtained. The dBm values stayed constant for the duration of the test and this allowed the condition of the bearing to be measured under variable speed and variable load conditions with some exception. The exception to the findings was that the dBm values stayed constant during acceleration phases, but during the deceleration phases the values were erratic and scattered. At speed below 200rpm the dBm values did not stay constant and therefore it was concluded that the dBm value recorded the best results only when thrust on the bearing was maximum. The other exception was under no-load conditions. The values were erratic and scattered, and therefore the results were not a true reflection of the bearing condition. The third exception was that the results on bearings with various loads remained constant during increased load changes unless the loading was erratic. During erratic load changes, the results were affected. The results also indicated that the larger the defect on the bearing raceway, the higher the dBm values were. Multipil defects on the bearing race ways were not part of this thesis and this gives an opertunity for futher research. The Shock pulse monitoring technique was 100% successful in monitoring the bearing condition only while the speed of the bearing was increasing. The results obtained in this work demonstrated that the condition of bearings can be monitored in applications of variable speed and variable load if the exception are eliminated and to obtain conclusive results the mechanical shock pulses should be measured over time and not be used as once-off value.

<p>Denna rapport är en beskrivning av ett examensarbete utfört vid SPM Instrument AB i Strängnäs. SPM Instrument utvecklar och tillverkar produkter för konditionsmätning av maskiner. </p><p>Målet var att skapa en cd-presentation i redigeringsprogrammet Macromedia Flash 5.0, som på ett enkelt sätt med rörliga bilder förklarar en konditionsmätningsmetod som kallas för Stöt Puls Metoden.</p><p>Uppgiften löstes genom att först inhämta information om Stöt Puls Metoden, sedan utformades Flash-filmen och slutligen testades och utvecklades filmen tills dess att jag och SPM Instrument var nöjda. </p> / <p>This report describes a final-year project performed at SPM Instrument AB in Strängnäs. The company develop and manufacture products for condition monitoring of machinery equipment. </p><p>The goal was to create a cd-presentation in the computer software Macromedia Flash 5.0, with moving pictures which explains a condition monitoring method that is called the Shoke Pulse Method. </p><p>The task was solved by first finding out information about the Shoke Pulse Method, then the Flash-movie was created and finally the movie was tested and developed until both I and SPM Instrument was satisfied.</p>

Denna rapport är en beskrivning av ett examensarbete utfört vid SPM Instrument AB i Strängnäs. SPM Instrument utvecklar och tillverkar produkter för konditionsmätning av maskiner. Målet var att skapa en cd-presentation i redigeringsprogrammet Macromedia Flash 5.0, som på ett enkelt sätt med rörliga bilder förklarar en konditionsmätningsmetod som kallas för Stöt Puls Metoden. Uppgiften löstes genom att först inhämta information om Stöt Puls Metoden, sedan utformades Flash-filmen och slutligen testades och utvecklades filmen tills dess att jag och SPM Instrument var nöjda. / This report describes a final-year project performed at SPM Instrument AB in Strängnäs. The company develop and manufacture products for condition monitoring of machinery equipment. The goal was to create a cd-presentation in the computer software Macromedia Flash 5.0, with moving pictures which explains a condition monitoring method that is called the Shoke Pulse Method. The task was solved by first finding out information about the Shoke Pulse Method, then the Flash-movie was created and finally the movie was tested and developed until both I and SPM Instrument was satisfied.

<div>This body of work examines analytical and numerical models to simulate the response of structures in shock absorption applications. Specifically, the work examines the prediction of cushion curves of polymer foams, and a topological examination of a $\chi$ shape unit cell found in architected mechanical elastomeric metamaterials. The $\chi$ unit cell exhibits the same effective stress-strain relationship as a closed cell polymer foam. Polymer foams are commonly used in the protective packaging of fragile products. Cushion curves are used within the packaging industry to characterize a foam's impact performance. These curves are two-dimensional representations of the deceleration of an impacting mass versus static stress. The main drawback with cushion curves is that they are currently generated from an exhaustive set of experimental test data. This work examines modeling the shock response using a continuous rod approximation with a given impact velocity in order to generate cushion curves without the need of extensive testing. In examining the $\chi$ unit cell, this work focuses on the effects of topological changes on constitutive behavior and shock absorbing performance. Particular emphasis is placed on developing models to predict the onset of regions of quasi-zero-modulus (QZM), the length of the QZM region and the cushion curve produced by impacting the unit cell. The unit cell's topology is reduced to examining a characteristic angle, defining the internal geometry with the cell, and examining the effects of changing this angle.</div><div>However, the characteristic angle cannot be increased without tradeoffs; the cell's effective constitutive behavior evolves from long regions to shortened regions of quasi-zero modulus. Finally, this work shows that the basic $\chi$ unit cell can be tessellated to produce a nearly equivalent force deflection relationship in two directions. The analysis and results in this work can be viewed as new framework in analyzing programmable elastomeric metamaterials that exhibit this type of nonlinear behavior for shock absorption.</div>

Underhåll är en aktivitet som varje produktion vill undvika så mycket som möjligt på grund av kostnaderna och tiden som anknyts till den. Trots detta så är en väl fungerande underhållsverksamhet väsentlig för att främja produktionens funktionssäkerhet och tillgänglighet att tillverka. En effektiv underhållsorganisation går däremot inte ut på att genomföra mer underhåll än vad som egentligen är nödvändigt utan att genomföra underhåll i rätt tid. På traditionellt sätt så genomförs detta genom att ersätta slitage delar och serva utrustningen med fastställda mellanrum för att förebygga att haveri, vilket kallas för förebyggande underhåll. De tidsintervaller som angivits för service bestäms av leverantörerna och grundar sig i en generell uppskattning av slitagedelarnas livslängd utifrån tester och analys. Till skillnad från att köra utrustningen till den går sönder som kallas för Avhjälpande underhåll så kan underhåll genomföras vid lämpliga tider så att det inte påverkar produktion och tillgänglighet. Men de tidsintervall som leverantörerna rekommenderar till företagen garanterar inte att slitage delen håller sig till det intervallet, delarna kan exempelvis rasa tidigare än angivet eller till och med hålla längre. Av denna anledning är det naturliga steget i underhållets utveckling att kunna övervaka utrustningens hälsa i hopp om att kunna förutspå när och varför ett haveri ska uppstå. Den här typen av underhåll kallas för tillståndsbaserat och prediktivt underhåll och medför ultimat tillgänglighet av utrustning och den mest kostnadseffektiva underhållsorganisationen, då god framförhållning och översikt uppnås för att enbart genomföra underhåll när det behövs. Det som gör tillståndsbaserat och prediktivt underhåll möjligt är den fjärde industriella revolutionen “Industri 4.0” och teknologierna som associeras med den som går ut på absolut digitalisering av produktionen och smarta fabriker. Teknologier som IoT, Big Dataanalys och Artificiell Intelligens används för att koppla upp utrustning till nätet med hjälp av givare för att samla in och lagra data som ska användas i analyser för att prognosera dess livslängd. Uppdragsgivaren AstraZeneca i Södertälje tillverkar olika typer av läkemedel som många är livsviktiga för de patienter som tar dessa mediciner. Om AstraZenecas produktion står still på grund av fel i utrustningen kommer det inte enbart medföra stora ekonomiska konsekvenser utan även påverka de människor som med livet förlitar sig på den medicin som levereras. För att försäkra produktionens tillgänglighet har AstraZeneca gjort försök att tillämpa tillståndsbaserat och prediktivt underhåll men det är fortfarande enbart i startgroparna. Eftersom ventilation är kritisk del av AstraZeneca produktion då ett fel i ventilationssystemet resulterar i totalt produktionsstopp i byggnaden förens problemet åtgärdas och anläggningen sanerats blev det även rapportens fokusområde. Arbetets uppgift går därför ut på att undersöka möjligheter för AstraZeneca att utveckla deras prediktiva och tillståndsbaserat underhåll på deras ventilationssystem, för att sedan kunna identifiera och presentera förslag på åtgärder. Dessa förslag analyserades sedan med hjälp av verktygen QFD-Matris och Pugh-Matris för att kunna uppskatta vilket förslag som är mest kostnadseffektivt, funktions effektivt samt vilket förslag som kommer tillföra mest nytta för underhållet på AstraZeneca. / Maintenance is an activity that every production wants to avoid as much as possible due to the costs and the time associated with it. Despite this, a well-functioning maintenance operation is essential to promote the production's availability to manufacture and operational reliability. Running an efficient maintenance operation is not about carrying out more maintenance than is necessary but carrying out the right amount of maintenance at the right time. Traditionally speaking this is done by replacing worn parts and servicing the equipment at set intervals to prevent breakdowns, this method is called preventive maintenance. The intervals specified for service are determined by the suppliers and are based on general estimates of the service life for the spare parts from test and analytics. Preventive maintenance allows for maintenance to be carried out at appropriate time to not affect production and availability unlike running the equipment until breakdown, which is called reactive maintenance. However, these intervals that the suppliers recommend do not guarantee that the parts adhere to the given interval, the part can for example break down earlier than expected or even outlast its prescribed lifetime. Because of this, the natural step in the development of maintenance is giving companies the ability to monitor the health of the equipment in hope of being able to predict potential breakdowns. This is what Condition-Based and predictive maintenance is and it provides the ultimate availability of equipment and the most cost-effective maintenance organization, because the good foresight and overview allows maintenance to be carried out only when needed. The fourth industrial revolution “Industry 4.0”, absolute digitalization of production, smart factories and all the technologies associated with this is what makes this type of maintenance possible. Technologies such as IoT, Big Data Analytics and Artificial Intelligence are used to connect equipment to the network using sensors so that data can be stored and collected to be analyzed to forecast the lifespan of parts and equipment. AstraZeneca in Södertälje manufactures different types of medicine, many of which are vital for the patients who take them. If their production comes to a standstill due to equipment failure, it will not only have major financial consequences but also greatly affect the people who rely on the medicine offered with their lives. To ensure the availability of production, AstraZeneca has made attempts to apply condition-based and predictive maintenance, but it is still only in its infancy. Since ventilation is a critical part of AstraZeneca's production, as a failure here will result in a total production stoppage for the building affected and will not resume before the problem is remedied and the plant is decontaminated, it also became the report's focus area. The task at hand is therefore to investigate the opportunities AstraZeneca must develop their predictive and condition-based maintenance for their ventilation systems, in order to be able to present proposals for measures. The proposals will then be analyzed using tools like the QFD-Matrix and the Pugh-Matrix in order to estimate which is more cost effective, function effective and which one will bring the most benefit to AstraZeneca.