Spectrometrical Monitoring of Laser Sintering Process of Ceramic Material

This thesis is done as a part of project called FuncMama that is a project between Technical Research Centre of Finland (VTT), Oulu University (OY), Lappeenranta University of Technology (LUT) and Finnish industrial partners. Main goal of the project is to manufacture electric and mechanical components from mixed materials using laser sintering. Aim of this study was to create laser sintered pieces from ceramic material and monitor the sintering event by using spectrometer. Spectrometer is a device which is capable to record intensity of different wavelengths in relation with time. In this study the monitoring of laser sintering was captured with the equipment which consists of Ocean Optics spectrometer, optical fiber and optical lens (detector head). Light from the sintering process hit first to the lens system which guides the light in to the optical fibre. Optical fibre transmits the light from the sintering process to the spectrometer where wavelengths intensity level information is detected. The optical lens of the spectrometer was rigidly set and did not move along with the laser beam. Data which was collected with spectrometer from the laser sintering process was converted with Excel spreadsheet program for result’s evaluation. Laser equipment used was IPG Photonics pulse fibre laser. Laser parameters were kept mainly constant during experimental part and only sintering speed was changed. That way it was possible to find differences in the monitoring results without fear of too many parameters mixing together and affecting to the conclusions. Parts which were sintered had one layer and size of 5 x 5 mm. Material was CT2000 – tape manufactured by Heraeus which was later on post processed to powder. Monitoring of different sintering speeds was tested by using CT2000 reference powder. Moreover tests how different materials effect to the process monitoring were done by adding foreign powder Du Pont 951 which had suffered in re-grinding and which was more reactive than CT2000. By adding foreign material it simulates situation where two materials are accidently mixed together and it was studied if that can be seen with the spectrometer. It was concluded in this study that with the spectrometer it is possible to detect changes between different laser sintering speeds. When the sintering speed is lowered the intensity level of light is higher from the process. This is a result of higher temperature at the sintering spot and that can be noticed with the spectrometer. That indicates it could be possible to use spectrometer as a tool for process observation and support the idea of having system that can help setting up the process parameter window. Also important conclusion was how well the adding of foreign material could be seen with the spectrometer. When second material was added a significant intensity level raise could be noticed in that part where foreign material was mixed. That indicates it is possible to see if there are any variations in the material or if there are more materials mixed together. Spectrometric monitoring of laser sintering could be useful tool for process window observation and temperature controlling of the sintering process. For example if the process window for specific material is experimentally determined to get wanted properties and satisfying sintering speed. It is possible if the data is constantly recorded that the results can show faults in the part texture between layers. Changes between the monitoring data and the experimentally determined values can then indicate changes in the material being generated by material faults or by wrong process parameters. The results of this study show that spectrometer could be one possible tool for monitoring. But to get in that point where this all can be made possible much more researching is needed.

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Sottiisi.

Bayesian methods for estimation, optimization and experimental design

Mathematical models often contain parameters that need to be calibrated from measured data. The emergence of efficient Markov Chain Monte Carlo (MCMC) methods has made the Bayesian approach a standard tool in quantifying the uncertainty in the parameters. With MCMC, the parameter estimation problem can be solved in a fully statistical manner, and the whole distribution of the parameters can be explored, instead of obtaining point estimates and using, e.g., Gaussian approximations. In this thesis, MCMC methods are applied to parameter estimation problems in chemical reaction engineering, population ecology, and climate modeling. Motivated by the climate model experiments, the methods are developed further to make them more suitable for problems where the model is computationally intensive. After the parameters are estimated, one can start to use the model for various tasks. Two such tasks are studied in this thesis: optimal design of experiments, where the task is to design the next measurements so that the parameter uncertainty is minimized, and model-based optimization, where a model-based quantity, such as the product yield in a chemical reaction model, is optimized. In this thesis, novel ways to perform these tasks are developed, based on the output of MCMC parameter estimation. A separate topic is dynamical state estimation, where the task is to estimate the dynamically changing model state, instead of static parameters. For example, in numerical weather prediction, an estimate of the state of the atmosphere must constantly be updated based on the recently obtained measurements. In this thesis, a novel hybrid state estimation method is developed, which combines elements from deterministic and random sampling methods.

Improvement of Surface Strength of Paper

Offset printing is a popular printing method that is especially suitable for large and fast print jobs. Newspapers, magazines and books are typical examples of products printed with offset method. In high volume printing production high efficiency is essential. Offset printing uses tacky inks that cause serious stress to the paper surface. Dusting and linting are terms that describe how loose and weakly bonded particles are removed from the paper surface in the printing process. The removed particles accumulate in the process causing deteriorating print quality. This forces the printing operators to stop production for washing and cleaning. Time and money are lost. Dusting and linting tendency of paper can be decreased by improving the surface strength of paper. In the present work a method to increase the surface strength of paper was studied. In the literature part offset printing method and challenges related to offset printing are presented. A review of new methods for surface sizing of paper is also presented. The experimental part presents trials where an apparatus for improving paper surface strength was tested and developed in mill scale. Laboratory work supporting the actual mill scale operations is also presented. The acquired results provide a solid base of information to make decisions on how to proceed with research in the present field of study.

Cargo Traffic on the Helsinki-Tallinn Route

The twin-city model has found to increase economical activity and well-being. The similar economical, social and cultural background of Finland and Estonia as well as the EU integration give good preconditions to create a twin-city of Helsinki and Tallinn. The relatively long distance between Helsinki and Tallinn is challenging. Therefore, good transport infrastructure and functioning connections are required to form a twin-city of Helsinki and Tallinn. The connections between these cities can be considered also in broader perspective than only from the viewpoint of the twin-city concept. New markets areas have been emerged in Europe due to collapse of planned economy and integration of Europe. Also the transport routes to the markets are changing. The Hel-sinki-Tallinn sea route can be considered as a fast route to the new markets in the Cen-tral and Eastern Europe. The Helsinki-Tallinn sea route is also a potential route to the Western European markets. This study provides an analysis of transport and cargo flows between Finland and Esto-nia for regional and local planners. The main purpose of the study is to clarify the pre-sent situation of the seaborne cargo flows on the Helsinki-Tallinn route and how the cargo flows will develop in the future. The study focuses on the following thematic enti-ties: the Finnish and Estonian seaborne transport system and cargo flows, the structure and volume of the cargo flows on the Helsinki-Tallinn route, the hinterland cargo flows on the Helsinki-Tallinn route and the transport methods used on the Helsinki-Tallinn route. The study was carried out as a desk research, a statistical analysis and an inter-view study during the spring–autumn 2011. The study reveals that during the period 2002–2010 the volume of the seaborne cargo traffic between Finland and Estonia has increased significantly while the trend of the trade volume between Finland and Estonia has remained nearly constant. This indicates that the route via Estonia is increasingly used in the Finnish foreign trade. Because the ports of Helsinki and Tallinn are the main ports in the cargo traffic between Finland and Estonia, the role of the Helsinki-Tallinn route as a sea leg in the hinterland connections of Finland has increased. The growth of the cargo volume on the Helsinki-Tallinn route was estimated to continue on the annual level of 10 % during the next couple of years. In the long run the growth of the cargo volumes depends on the economical and indus-trial development of the former Eastern European countries. If the IMO’s sulphur regu-lations will come in force, the Helsinki-Tallinn route will become one of the main routes also to the Western European markets, besides of the route via Sweden. The study also shows that the fast and reliable connections year round on the Helsinki-Tallinn route have made it possible for service and logistics companies to reconsider their logistics strategies in a new way in the both side of the Gulf of Finland. Anyway, the ropax concept is seen as the only economical profitable solution on the Helsinki-Tallinn route because cargo and passenger traffic are supporting each other. The trucks (vehicle combinations) will remain the main mode of transport on the Helsinki-Tallinn route because general cargo is the main commodity on the route. IMO’s sulphur regula-tions and the changes in the structure of the Finnish industry may create prerequisites for rail road transport in the hinterland connections of Finland. The twin-city model has found to increase economical activity and well-being. The similar economical, social and cultural background of Finland and Estonia as well as the EU integration give good preconditions to create a twin-city of Helsinki and Tallinn. The relatively long distance between Helsinki and Tallinn is challenging. Therefore, good transport infrastructure and functioning connections are required to form a twin-city of Helsinki and Tallinn. The connections between these cities can be considered also in broader perspective than only from the viewpoint of the twin-city concept. New markets areas have been emerged in Europe due to collapse of planned economy and integration of Europe. Also the transport routes to the markets are changing. The Hel-sinki-Tallinn sea route can be considered as a fast route to the new markets in the Cen-tral and Eastern Europe. The Helsinki-Tallinn sea route is also a potential route to the Western European markets. This study provides an analysis of transport and cargo flows between Finland and Esto-nia for regional and local planners. The main purpose of the study is to clarify the pre-sent situation of the seaborne cargo flows on the Helsinki-Tallinn route and how the cargo flows will develop in the future. The study focuses on the following thematic enti-ties: the Finnish and Estonian seaborne transport system and cargo flows, the structure and volume of the cargo flows on the Helsinki-Tallinn route, the hinterland cargo flows on the Helsinki-Tallinn route and the transport methods used on the Helsinki-Tallinn route. The study was carried out as a desk research, a statistical analysis and an inter-view study during the spring–autumn 2011. The study reveals that during the period 2002–2010 the volume of the seaborne cargo traffic between Finland and Estonia has increased significantly while the trend of the trade volume between Finland and Estonia has remained nearly constant. This indicates that the route via Estonia is increasingly used in the Finnish foreign trade. Because the ports of Helsinki and Tallinn are the main ports in the cargo traffic between Finland and Estonia, the role of the Helsinki-Tallinn route as a sea leg in the hinterland connections of Finland has increased. The growth of the cargo volume on the Helsinki-Tallinn route was estimated to continue on the annual level of 10 % during the next couple of years. In the long run the growth of the cargo volumes depends on the economical and indus-trial development of the former Eastern European countries. If the IMO’s sulphur regu-lations will come in force, the Helsinki-Tallinn route will become one of the main routes also to the Western European markets, besides of the route via Sweden. The study also shows that the fast and reliable connections year round on the Helsinki-Tallinn route have made it possible for service and logistics companies to reconsider their logistics strategies in a new way in the both side of the Gulf of Finland. Anyway, the ropax concept is seen as the only economical profitable solution on the Helsinki-Tallinn route because cargo and passenger traffic are supporting each other. The trucks (vehicle combinations) will remain the main mode of transport on the Helsinki-Tallinn route because general cargo is the main commodity on the route. IMO’s sulphur regula-tions and the changes in the structure of the Finnish industry may create prerequisites for rail road transport in the hinterland connections of Finland.

Sataman informaatiokeskuksen mahdollisuudet ympäristövaikutusten vähentämisessä

Logistiikka ja etenkin kuljetukset aiheuttavat suuren määrän suoria päästöjä ilmaan sekä muita ympäristövaikutuksia ihmisille ja luonnolle. Suomessa ja muissa EU-maissa kuljetusten tuottamat päästöt muodostavat yli viidenneksen kaikista päästöistä, joten puhutaan merkittävästä päästöjen vähentämistarpeesta. Tietoteknisten ratkaisujen nopea kehittyminen on mahdollistanut tietotekniikan hyödyntämisen myös logistiikassa ja logistiikan tuottamien päästöjen vähentämisessä. Tietotekniset ratkaisut ovat mahdollistaneet muun muassa sähköisten kartta- ja paikannusohjelmistojen käytön, kuljetusreittien optimoinnin, lastien ja kuljetusten seurannan, sähköisten dokumenttien hyödyntämisen sekä päästöjen laskemisen erilaisten tietoteknisten sovellusten avulla. Tämän tutkimuksen tarkoituksena on selvittää Port Community System (PCS) -järjestelmän eli satamayhteisön informaatiokeskuksen mahdollisuuksia vähentää ympäristövaikutuksia Suomessa ja erityisesti Kymenlaaksossa. Tutkimuksessa on selvitetty yleisesti logistiikan ympäristövaikutuksia ja tutkittu EU:n ohjauskeinoja logistiikan ympäristökuormitusten vähentämiseksi. Kymenlaakson alueelta on kartoitettu tavaraliikenteen päästömäärien nykytilaa ja kehitystä laskemalla auto-, juna- ja laivaliikenteen ympäristövaikutuksia vuosilta 2001–2009. Lisäksi tutkimuksessa on selvitetty, millaisia logistiikkaan liittyviä älyliikenne- ja tietotekniikkahankkeita ja -visioita EU:n tasolla on vireillä sekä tutkittu ICT-ratkaisujen mahdollisuuksia ympäristöhaittojen vähentämisessä. Kirjallisuustutkimukseen perustuen on arvioitu ja pohdittu Suomeen soveltuvan PCS-järjestelmän ympäristöhyötyjä ja ympäristötyökaluja. Lisäksi tutkimuksessa on tarkasteltu kahden case-esimerkin avulla, minkälaisia logistisia toimintoja helpottavia ja ympäristöasioita parantavia tietojärjestelmiä logistiikkayrityksillä on käytössä. Tutkimuksen perusteella tavaraliikenteen päästöt Kymenlaakson alueella ovat vuosien 2001–2007 aikana kasvaneet merkittävästi, mutta talouden taantuman ja tavarakuljetusten vähenemisen seurauksena päästömäärät ovat olleet jyrkässä laskussa vuosina 2008 ja 2009. Merkittävin päästökomponentti on ollut hiilidioksidi ja eniten päästöjä on aiheutunut maantieliikenteestä. EU:n tasolla on vireillä useita erilaisia hankkeita ja visioita logistiikan päästöjen vähentämiseksi, mutta monessa tapauksessa niiden täytäntöönpano vaatii vielä vuosien työn. Kirjallisuustutkimuksen perusteella ICT-ratkaisujen avulla saavutettavissa olevat ympäristöhyödyt vaihtelevat pienistä parannuksista (esim. päästöjen simulointimallit) suuriin maailmanlaajuisiin ratkaisuihin (esim. kuljetusreittien optimointi ja rahdin seuranta globaaleissa toimitusketjuissa). Merkittävimmät PCS-järjestelmällä saavutettavissa olevat ympäristöhyödyt ovat kuljetusten ja logististen toimintojen yleinen tehostuminen ja sen myötä päästöjen vähentyminen sekä paperisten asiakirjojen ja tulostettavan paperimäärän väheneminen PCS-järjestelmän mahdollistaman sähköisiin dokumentteihin siirtymisen myötä. PCS-järjestelmän avulla voidaan vaikuttaa ympäristöasioihin myös epäsuorasti muun muassa reittien ja lastikapasiteetin optimoinnin, lastin seurannan, älykkään valaistuksen ja palvelinkeskusten kautta. Mahdollisista ympäristöhyödyistä huolimatta taloudellisen hyödyn tavoittelu ja palveluiden toiminnallinen parantaminen menevät valitettavan usein ympäristöasioiden edelle. Vihreiden arvojen korostaminen järjestelmiä suunniteltaessa voi kuitenkin tuoda suurta kilpailuetua ja edistää ympäristön suojelua laajemminkin.

Kernel-Based Ranking. Methods for Learning and Performance Estimation

Machine learning provides tools for automated construction of predictive models in data intensive areas of engineering and science. The family of regularized kernel methods have in the recent years become one of the mainstream approaches to machine learning, due to a number of advantages the methods share. The approach provides theoretically well-founded solutions to the problems of under- and overfitting, allows learning from structured data, and has been empirically demonstrated to yield high predictive performance on a wide range of application domains. Historically, the problems of classification and regression have gained the majority of attention in the field. In this thesis we focus on another type of learning problem, that of learning to rank. In learning to rank, the aim is from a set of past observations to learn a ranking function that can order new objects according to how well they match some underlying criterion of goodness. As an important special case of the setting, we can recover the bipartite ranking problem, corresponding to maximizing the area under the ROC curve (AUC) in binary classification. Ranking applications appear in a large variety of settings, examples encountered in this thesis include document retrieval in web search, recommender systems, information extraction and automated parsing of natural language. We consider the pairwise approach to learning to rank, where ranking models are learned by minimizing the expected probability of ranking any two randomly drawn test examples incorrectly. The development of computationally efficient kernel methods, based on this approach, has in the past proven to be challenging. Moreover, it is not clear what techniques for estimating the predictive performance of learned models are the most reliable in the ranking setting, and how the techniques can be implemented efficiently. The contributions of this thesis are as follows. First, we develop RankRLS, a computationally efficient kernel method for learning to rank, that is based on minimizing a regularized pairwise least-squares loss. In addition to training methods, we introduce a variety of algorithms for tasks such as model selection, multi-output learning, and cross-validation, based on computational shortcuts from matrix algebra. Second, we improve the fastest known training method for the linear version of the RankSVM algorithm, which is one of the most well established methods for learning to rank. Third, we study the combination of the empirical kernel map and reduced set approximation, which allows the large-scale training of kernel machines using linear solvers, and propose computationally efficient solutions to cross-validation when using the approach. Next, we explore the problem of reliable cross-validation when using AUC as a performance criterion, through an extensive simulation study. We demonstrate that the proposed leave-pair-out cross-validation approach leads to more reliable performance estimation than commonly used alternative approaches. Finally, we present a case study on applying machine learning to information extraction from biomedical literature, which combines several of the approaches considered in the thesis. The thesis is divided into two parts. Part I provides the background for the research work and summarizes the most central results, Part II consists of the five original research articles that are the main contribution of this thesis.

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