Hybridikomposiittien hyödyntäminen tuulivoimalan rakenteissa

Diplomityön tarkoituksena oli tutkia hybridikomposiittien soveltuvuutta tuulivoimalan osien tai osakokonaisuuksien rakennemateriaaliksi. Lähtökohtana oli selvittää erityisesti luonnonkuitukomposiitin materiaaliteknisten ominaisuuksien, etenkin lujuusominaisuuksi-en soveltuminen tuulivoiman rakenteisiin. Työn johdanto-osuudessa esitellään tuulivoiman rooli tämän päivän energiantuotannossa, yksittäisen tuulivoimalalaitoksen rakenne, rakenteiden suunnittelussa huomioitavat seikat, voimalan eri osien kuten tornin, lapojen ja nasellin yleisimmät valmistusmenetelmät, sekä muovien ja eri lujitteiden ohella puumuovikomposiitin materiaaliominaisuudet, valmistus-menetelmät ja yleisimmät käyttökohteet. Hybridikomposiittien lujuusominaisuuksia tutkittiin Lappeenrannan teknillisen yliopiston puutekniikan laboratoriossa suoritetuissa mittauksissa. Saatuja tuloksia verrattiin referens-situlosten ohella myös tällä hetkellä tuulivoimalan rakenteissa yleisesti käytettävien lasi- ja hiilikuidun, sekä teräksen ominaisuuksiin. Mittaustulosten perusteella bambu- ja lasikuitu-lujitteiset puumuovikomposiitit soveltuvat parhaiten tuulivoimalarakenteisiin, mutta niiden valmistaminen ekstruusiomenetelmällä on melko haasteellista.

Feasibility study of metal to polymer hybrid joining

The increasing demand for lightweight components has led to a huge exploitation of non-metallic materials such as polymers, fibers and elastomers in industrial and manufacturing processes. Recent trends towards cost effectiveness, weight reduction and production flexibility in industrial production and manufacturing processes has led to a growing interest in hybrid components where two or more dissimilar materials coexist to achieving specifically optimized characteristics. The importance of this research is to serve as a bridge to understanding the theories behind various joining techniques and the adaptation of the process for metal to polymer hybrid joints. Moreso, it helps companies to select the most productive and yet economical joining process for realization of lightweight metal to polymer hybrid components. This thesis is a literature review analyzing various materials that has been published on various joining methods for metal to polymer hybrid joints on the feasibility and eventual realization of the joint between these dissimilar materials. This study is aimed at theoretically evaluating the feasibility of joining processes between metal and plastic components by exploiting exhaustively joining and welding sources.

Biomass fractionation

The objective of this master's thesis was to develop a process to increase the value of residual fungal biomass as an animal feed. The increase in value is achieved by enriching the protein content in the biomass and potentially isolating other valuable fractions for productisation. In the literature part of this thesis the composition of fungal biomass and fungal cell wall and the factors affecting them during cultivation are presented. The possible processing options are also presented and evaluated. The soy protein and single cell protein product manufacturing processes are used as examples due to the lack of fungal biomass fractionation processes found in published literature. The second part of this thesis was performed by making laboratory experiments on the developed process, which consisted of acid hydrolysis with subsequent ethanol extraction. Chitin was precipitated from the acid hydrolysate filtrate. The experiments were conducted with three different hydrolysis temperatures and three different acid concentrations. The optimal hydrolysis conditions were 60 °C with 10 %-vol acid concentration. Optimal conditions in hydrolysis resulted in 30 % increase in protein content in the final biomass. The conceptual process was modelled to scale of 10 000 t/a biomass feed. The mass and energy balances were based on the laboratory experiments. Economic calculations were performed to determine the maximal capital expense while achieving 10 % internal rate of return for the investment. For the basic case the capital expense threshold was 25.8 M€. Four optional cases and parameter sensitivity analysis were performed to determine the effects of changes in the process. The chitin sales had the greatest impact of the individual parameters.

Kestävä liiketoiminta kansainvälisessä sopimusvalmistuksessa: Case Nike

Tässä kandidaatintyössä esitellään kestävään kehitykseen, yritysten sosiaaliseen vastuuseen sekä sopimusvalmistukseen liittyvää teoriaa ja sovelletaan sitä tämän jälkeen case -yritys Niken toiminnan tutkimiseen ja arviointiin. Työn tavoitteena on muodostaa selkeä kuva Niken toiminnasta yritysvastuullisuuden sekä kestävän kehityksen hyväksi ja esitellä aihealueeseen liittyvä teoria sekä käsitteet. Työn avulla pyritään tekemään myös jonkinasteisia yleistyksiä suuryritysten vaikutuksista kohdealueisiin sopimusvalmistuksen yhteydessä. Työ on toteutettu osittain kirjallisuuskatsauksena ja osittain tapaustutkimuksena hyödyntäen pääasiallisesti elektronista tiedonhakua. Tutkimuksen tuloksena voidaan todeta, että Niken tämänhetkinen tilanne yritysvastuullisuuden saralla on erinomainen ja se on kestävän kehityksen alalla edelläkävijä. Nike on säilyttänyt toiminnassaan ja koko tuotantoketjussaan kestävät periaatteet sopimusvalmistuksen tuomista laajoista verkostoista ja sidosryhmäsuhteista huolimatta. Yritysten sosiaalinen vastuu sekä sopimusvalmistus ovat tuoneet Niken brändille laajamittaista arvostusta ja tätä kautta välillisesti taloudellista menestystä. Uhratuista resursseista huolimatta Nike pärjää tällä hetkellä taloudellisesti paremmin, kuin ennen vastuullisuuden sekä kestävien toimintamallien laajempaa implementaatiota. Myös tulevaisuus näyttää Niken kohdalla valoisalta.

Utilization of Statistical Methods for Management in the Forest Industry

The strongest wish of the customer concerning chemical pulp features is consistent, uniform quality. Variation may be controlled and reduced by using statistical methods. However, studies addressing the application and benefits of statistical methods in forest product sector are scarce. Thus, the customer wish is the root cause of the motivation behind this dissertation. The research problem addressed by this dissertation is that companies in the chemical forest product sector require new knowledge for improving their utilization of statistical methods. To gain this new knowledge, the research problem is studied from five complementary viewpoints – challenges and success factors, organizational learning, problem solving, economic benefit, and statistical methods as management tools. The five research questions generated on the basis of these viewpoints are answered in four research papers, which are case studies based on empirical data collection. This research as a whole complements the literature dealing with the use of statistical methods in the forest products industry. Practical examples of the application of statistical process control, case-based reasoning, the cross-industry standard process for data mining, and performance measurement methods in the context of chemical forest products manufacturing are brought to the public knowledge of the scientific community. The benefit of the application of these methods is estimated or demonstrated. The purpose of this dissertation is to find pragmatic ideas for companies in the chemical forest product sector in order for them to improve their utilization of statistical methods. The main practical implications of this doctoral dissertation can be summarized in four points: 1. It is beneficial to reduce variation in chemical forest product manufacturing processes 2. Statistical tools can be used to reduce this variation 3. Problem-solving in chemical forest product manufacturing processes can be intensified through the use of statistical methods 4. There are certain success factors and challenges that need to be addressed when implementing statistical methods

Analysis and Optimization of Machining Process Using Evolutionary Algorithms

To ensure quality of machined products at minimum machining costs and maximum machining effectiveness, it is very important to select optimum parameters when metal cutting machine tools are employed. Traditionally, the experience of the operator plays a major role in the selection of optimum metal cutting conditions. However, attaining optimum values each time by even a skilled operator is difficult. The non-linear nature of the machining process has compelled engineers to search for more effective methods to attain optimization. The design objective preceding most engineering design activities is simply to minimize the cost of production or to maximize the production efficiency. The main aim of research work reported here is to build robust optimization algorithms by exploiting ideas that nature has to offer from its backyard and using it to solve real world optimization problems in manufacturing processes.In this thesis, after conducting an exhaustive literature review, several optimization techniques used in various manufacturing processes have been identified. The selection of optimal cutting parameters, like depth of cut, feed and speed is a very important issue for every machining process. Experiments have been designed using Taguchi technique and dry turning of SS420 has been performed on Kirlosker turn master 35 lathe. Analysis using S/N and ANOVA were performed to find the optimum level and percentage of contribution of each parameter. By using S/N analysis the optimum machining parameters from the experimentation is obtained.Optimization algorithms begin with one or more design solutions supplied by the user and then iteratively check new design solutions, relative search spaces in order to achieve the true optimum solution. A mathematical model has been developed using response surface analysis for surface roughness and the model was validated using published results from literature.Methodologies in optimization such as Simulated annealing (SA), Particle Swarm Optimization (PSO), Conventional Genetic Algorithm (CGA) and Improved Genetic Algorithm (IGA) are applied to optimize machining parameters while dry turning of SS420 material. All the above algorithms were tested for their efficiency, robustness and accuracy and observe how they often outperform conventional optimization method applied to difficult real world problems. The SA, PSO, CGA and IGA codes were developed using MATLAB. For each evolutionary algorithmic method, optimum cutting conditions are provided to achieve better surface finish.The computational results using SA clearly demonstrated that the proposed solution procedure is quite capable in solving such complicated problems effectively and efficiently. Particle Swarm Optimization (PSO) is a relatively recent heuristic search method whose mechanics are inspired by the swarming or collaborative behavior of biological populations. From the results it has been observed that PSO provides better results and also more computationally efficient.Based on the results obtained using CGA and IGA for the optimization of machining process, the proposed IGA provides better results than the conventional GA. The improved genetic algorithm incorporating a stochastic crossover technique and an artificial initial population scheme is developed to provide a faster search mechanism. Finally, a comparison among these algorithms were made for the specific example of dry turning of SS 420 material and arriving at optimum machining parameters of feed, cutting speed, depth of cut and tool nose radius for minimum surface roughness as the criterion. To summarize, the research work fills in conspicuous gaps between research prototypes and industry requirements, by simulating evolutionary procedures seen in nature that optimize its own systems.

Randzonenveränderung beim Bohren und ihre Auswirkung auf Folgebearbeitungsverfahren

In der Praxis kommt es bei der spanenden Bearbeitung immer wieder zu großen Standwegunterschieden identischer Werkzeuge bei vordergründig identischen Bearbeitungsrandbedingungen. Insbesondere bei Fertigungsschritten, die das Bohren als Vorbearbeitung erfordern, kommt es gelegentlich zu atypischen Verschleißerscheinungen, die auf das Entstehen einer Neuhärtezone an der Werkstückoberfläche beim Bohren zurückgeführt werden. Grundsätzlich sind Randzonenveränderungen eine Folge der mechanischen und thermischen Beanspruchung bei der Bearbeitung. Beim Eindringen des Schneidkeils kommt es zu Kornverzerrungen, welche die Werkstückhärte bis in eine Tiefe von 40 bis 80 µm erhöhen können. Überdies wird die Randzone des Werkstücks durch den Bearbeitungsvorgang und den Spantransport erhitzt und durch den Kühlschmierstoff bzw. die so genannte Selbstabschreckung im Anschluss sehr schnell abgekühlt. So kann es in Abhängigkeit der Randbedingungen zu Gefügeänderungen mit härtesteigernder (Sekundärabschreckung) oder härtemindernder (Anlasseffekte) Wirkung kommen. Nicht zuletzt beeinflussen beide Beanspruchungsarten auch das Ausmaß der Eigenspannungen in der Werkstückoberfläche. In dieser Arbeit werden die beim Kernlochbohren erzeugten Randzonenveränderungen sowie die Standzeit von Folgebearbeitungswerkzeugen, wie Gewindebohrern und Gewindeformern, und deren Abhängigkeit vom Verschleißzustand des Kernlochbohrers untersucht. Weiterhin werden mit Hilfe einer Energiebilanz die Anteile herausgefiltert, die primär die Eigenschaften der Bohrungsrandzone beeinflussen. Dies geschieht mit Hilfe einer mathematischen Modellierung des Bohrprozesses, in der die Einflüsse der Schneidkantengeometrie, der Schneidkantenverrundung, der Schneidkantenfase sowie des Freiflächenverschleißes berücksichtigt werden.

Millora d’un prototipus de control de qualitat de producció de paper pintat basat en visió per computador

L’objectiu d’aquest projecte és realitzar l’anàlisi, disseny i implementació d’una nova eina per analitzar les diferencies entre el paper que s’està produint i les mostres de referència, que millori els resultats obtinguts pel prototipus anterior i faciliti la interpretació dels resultats obtinguts, per part dels operaris de l’empresa. Partint de dos imatges escannejades que anomenem patró i mostra, que corresponen respectivament a les imatges de referència i de la mostra de producció

Automatització d’una màquina de tall rotatiu

Molt sovint, a l’indústria de l’alimentació o de la cosmètica, hi ha promocions on s’afegeixen productes de regal; aquests els embalen amb un sleever (tipus de plàstic força rígid) que després retractilen. Aquestes promocions solen ser esporàdiques i canviants i això fa que no sigui factible la modificació de la línia de producció general per a realitzar-les. Per aquest motiu, moltes empreses disposen d’una petita màquina de tall rotatiu per a poder tallar els sleevers ells mateixos, i així tallar a molta velocitat i precisió aquestes petites produccions. Així doncs, esdevé molt interessant l’adquisició d’aquest tipus de maquinària. L’objectiu del projecte és fer l’automatització d’una màquina que pugui tallar aquest tipus de material ràpidament per fer-lo rentable

SQualTrack: A Tool for Robust Fault Detection

One of the techniques used to detect faults in dynamic systems is analytical redundancy. An important difficulty in applying this technique to real systems is dealing with the uncertainties associated with the system itself and with the measurements. In this paper, this uncertainty is taken into account by the use of intervals for the parameters of the model and for the measurements. The method that is proposed in this paper checks the consistency between the system's behavior, obtained from the measurements, and the model's behavior; if they are inconsistent, then there is a fault. The problem of detecting faults is stated as a quantified real constraint satisfaction problem, which can be solved using the modal interval analysis (MIA). MIA is used because it provides powerful tools to extend the calculations over real functions to intervals. To improve the results of the detection of the faults, the simultaneous use of several sliding time windows is proposed. The result of implementing this method is semiqualitative tracking (SQualTrack), a fault-detection tool that is robust in the sense that it does not generate false alarms, i.e., if there are false alarms, they indicate either that the interval model does not represent the system adequately or that the interval measurements do not represent the true values of the variables adequately. SQualTrack is currently being used to detect faults in real processes. Some of these applications using real data have been developed within the European project advanced decision support system for chemical/petrochemical manufacturing processes and are also described in this paper

Contribución metodológica en técnicas de diseñar para fabricación

En el proceso de diseño se toman decisiones que pueden afectar a la fabricabilidad del producto. Cuando el diseñador es experto, considera las limitaciones, las propiedades y el coste de fabricación en la fase de materialización o de detalle. El problema surge cuando el diseñador no es experto o cuando no hay suficiente información y conocimiento de fabricación disponible. Tomando como referencia la teoría de Diseño Axiomático y las técnicas de DFM, se propone una metodología para identificar, definir y formalizar la información de fabricación que debería estar disponible en el diseño para diseñar para fabricar (DFM). También se propone un prototipo de modelo de información para desarrollar una futura herramienta informática que facilitaría la aplicación de esta metodología y que permitiría guiar al diseñador durante el diseño. La metodología ha sido aplicada a una biela de un motor de combustión interna alternativo (MCIA), y a los procesos que se están usando actualmente para fabricarla: forja en matriz cerrada y forja de polvo de metal.

Multivariable cluster analysis for high-speed industrial machinery

The overall operation and internal complexity of a particular production machinery can be depicted in terms of clusters of multidimensional points which describe the process states, the value in each point dimension representing a measured variable from the machinery. The paper describes a new cluster analysis technique for use with manufacturing processes, to illustrate how machine behaviour can be categorised and how regions of good and poor machine behaviour can be identified. The cluster algorithm presented is the novel mean-tracking algorithm, capable of locating N-dimensional clusters in a large data space in which a considerable amount of noise is present. Implementation of the algorithm on a real-world high-speed machinery application is described, with clusters being formed from machinery data to indicate machinery error regions and error-free regions. This analysis is seen to provide a promising step ahead in the field of multivariable control of manufacturing systems.

On instabilities in data assimilation algorithms

Data assimilation algorithms are a crucial part of operational systems in numerical weather prediction, hydrology and climate science, but are also important for dynamical reconstruction in medical applications and quality control for manufacturing processes. Usually, a variety of diverse measurement data are employed to determine the state of the atmosphere or to a wider system including land and oceans. Modern data assimilation systems use more and more remote sensing data, in particular radiances measured by satellites, radar data and integrated water vapor measurements via GPS/GNSS signals. The inversion of some of these measurements are ill-posed in the classical sense, i.e. the inverse of the operator H which maps the state onto the data is unbounded. In this case, the use of such data can lead to significant instabilities of data assimilation algorithms. The goal of this work is to provide a rigorous mathematical analysis of the instability of well-known data assimilation methods. Here, we will restrict our attention to particular linear systems, in which the instability can be explicitly analyzed. We investigate the three-dimensional variational assimilation and four-dimensional variational assimilation. A theory for the instability is developed using the classical theory of ill-posed problems in a Banach space framework. Further, we demonstrate by numerical examples that instabilities can and will occur, including an example from dynamic magnetic tomography.

A normative method to analyse workarounds in a healthcare environment: motivations, consequences, and constraints

Healthcare information systems have the potential to enhance productivity, lower costs, and reduce medication errors by automating business processes. However, various issues such as system complexity and system abilities in a relation to user requirements as well as rapid changes in business needs have an impact on the use of these systems. In many cases failure of a system to meet business process needs has pushed users to develop alternative work processes (workarounds) to fill this gap. Some research has been undertaken on why users are motivated to perform and create workarounds. However, very little research has assessed the consequences on patient safety. Moreover, the impact of performing these workarounds on the organisation and how to quantify risks and benefits is not well analysed. Generally, there is a lack of rigorous understanding and qualitative and quantitative studies on healthcare IS workarounds and their outcomes. This project applies A Normative Approach for Modelling Workarounds to develop A Model of Motivation, Constraints, and Consequences. It aims to understand the phenomenon in-depth and provide guidelines to organisations on how to deal with workarounds. Finally the method is demonstrated on a case study example and its relative merits discussed.