Quality assurance of refuse derived fuel with machine vision

This thesis studies the use of machine vision in RDF quality assurance and manufacturing. Currently machine vision is used in recycling and material detection and some commer- cial products are available in the market. In this thesis an on-line machine vision system is proposed for characterizing particle size. The proposed machine vision system is based on the mapping between image segmenta- tion and the ground truth of the particle size. The results shows that the implementation of such machine vision system is feasible.

Feasibility of industrial implementation of laser cutting into paper making machine

Laser cutting implementation possibilities into paper making machine was studied as the main objective of the work. Laser cutting technology application was considered as a replacement tool for conventional cutting methods used in paper making machines for longitudinal cutting such as edge trimming at different paper making process and tambour roll slitting. Laser cutting of paper was tested in 70’s for the first time. Since then, laser cutting and processing has been applied for paper materials with different level of success in industry. Laser cutting can be employed for longitudinal cutting of paper web in machine direction. The most common conventional cutting methods include water jet cutting and rotating slitting blades applied in paper making machines. Cutting with CO2 laser fulfils basic requirements for cutting quality, applicability to material and cutting speeds in all locations where longitudinal cutting is needed. Literature review provided description of advantages, disadvantages and challenges of laser technology when it was applied for cutting of paper material with particular attention to cutting of moving paper web. Based on studied laser cutting capabilities and problem definition of conventional cutting technologies, preliminary selection of the most promising application area was carried out. Laser cutting (trimming) of paper web edges in wet end was estimated to be the most promising area where it can be implemented. This assumption was made on the basis of rate of web breaks occurrence. It was found that up to 64 % of total number of web breaks occurred in wet end, particularly in location of so called open draws where paper web was transferred unsupported by wire or felt. Distribution of web breaks in machine cross direction revealed that defects of paper web edge was the main reason of tearing initiation and consequent web break. The assumption was made that laser cutting was capable of improvement of laser cut edge tensile strength due to high cutting quality and sealing effect of the edge after laser cutting. Studies of laser ablation of cellulose supported this claim. Linear energy needed for cutting was calculated with regard to paper web properties in intended laser cutting location. Calculated linear cutting energy was verified with series of laser cutting. Practically obtained laser energy needed for cutting deviated from calculated values. This could be explained by difference in heat transfer via radiation in laser cutting and different absorption characteristics of dry and moist paper material. Laser cut samples (both dry and moist (dry matter content about 25-40%)) were tested for strength properties. It was shown that tensile strength and strain break of laser cut samples are similar to corresponding values of non-laser cut samples. Chosen method, however, did not address tensile strength of laser cut edge in particular. Thus, the assumption of improving strength properties with laser cutting was not fully proved. Laser cutting effect on possible pollution of mill broke (recycling of trimmed edge) was carried out. Laser cut samples (both dry and moist) were tested on the content of dirt particles. The tests revealed that accumulation of dust particles on the surface of moist samples can take place. This has to be taken into account to prevent contamination of pulp suspension when trim waste is recycled. Material loss due to evaporation during laser cutting and amount of solid residues after cutting were evaluated. Edge trimming with laser would result in 0.25 kg/h of solid residues and 2.5 kg/h of lost material due to evaporation. Schemes of laser cutting implementation and needed laser equipment were discussed. Generally, laser cutting system would require two laser sources (one laser source for each cutting zone), set of beam transfer and focusing optics and cutting heads. In order to increase reliability of system, it was suggested that each laser source would have double capacity. That would allow to perform cutting employing one laser source working at full capacity for both cutting zones. Laser technology is in required level at the moment and do not require additional development. Moreover, capacity of speed increase is high due to availability high power laser sources what can support the tendency of speed increase of paper making machines. Laser cutting system would require special roll to maintain cutting. The scheme of such roll was proposed as well as roll integration into paper making machine. Laser cutting can be done in location of central roll in press section, before so-called open draw where many web breaks occur, where it has potential to improve runability of a paper making machine. Economic performance of laser cutting was done as comparison of laser cutting system and water jet cutting working in the same conditions. It was revealed that laser cutting would still be about two times more expensive compared to water jet cutting. This is mainly due to high investment cost of laser equipment and poor energy efficiency of CO2 lasers. Another factor is that laser cutting causes material loss due to evaporation whereas water jet cutting almost does not cause material loss. Despite difficulties of laser cutting implementation in paper making machine, its implementation can be beneficial. The crucial role in that is possibility to improve cut edge strength properties and consequently reduce number of web breaks. Capacity of laser cutting to maintain cutting speeds which exceed current speeds of paper making machines what is another argument to consider laser cutting technology in design of new high speed paper making machines.

Sentence Compression with Supervised Machine Learning

The subject of the thesis is automatic sentence compression with machine learning, so that the compressed sentences remain both grammatical and retain their essential meaning. There are multiple possible uses for the compression of natural language sentences. In this thesis the focus is generation of television program subtitles, which often are compressed version of the original script of the program. The main part of the thesis consists of machine learning experiments for automatic sentence compression using different approaches to the problem. The machine learning methods used for this work are linear-chain conditional random fields and support vector machines. Also we take a look which automatic text analysis methods provide useful features for the task. The data used for machine learning is supplied by Lingsoft Inc. and consists of subtitles in both compressed an uncompressed form. The models are compared to a baseline system and comparisons are made both automatically and also using human evaluation, because of the potentially subjective nature of the output. The best result is achieved using a CRF - sequence classification using a rich feature set. All text analysis methods help classification and most useful method is morphological analysis. Tutkielman aihe on suomenkielisten lauseiden automaattinen tiivistäminen koneellisesti, niin että lyhennetyt lauseet säilyttävät olennaisen informaationsa ja pysyvät kieliopillisina. Luonnollisen kielen lauseiden tiivistämiselle on monta käyttötarkoitusta, mutta tässä tutkielmassa aihetta lähestytään television ohjelmien tekstittämisen kautta, johon käytännössä kuuluu alkuperäisen tekstin lyhentäminen televisioruudulle paremmin sopivaksi. Tutkielmassa kokeillaan erilaisia koneoppimismenetelmiä tekstin automaatiseen lyhentämiseen ja tarkastellaan miten hyvin erilaiset luonnollisen kielen analyysimenetelmät tuottavat informaatiota, joka auttaa näitä menetelmiä lyhentämään lauseita. Lisäksi tarkastellaan minkälainen lähestymistapa tuottaa parhaan lopputuloksen. Käytetyt koneoppimismenetelmät ovat tukivektorikone ja lineaarisen sekvenssin mallinen CRF. Koneoppimisen tukena käytetään tekstityksiä niiden eri käsittelyvaiheissa, jotka on saatu Lingsoft OY:ltä. Luotuja malleja vertaillaan Lopulta mallien lopputuloksia evaluoidaan automaattisesti ja koska teksti lopputuksena on jossain määrin subjektiivinen myös ihmisarviointiin perustuen. Vertailukohtana toimii kirjallisuudesta poimittu menetelmä. Tutkielman tuloksena paras lopputulos saadaan aikaan käyttäen CRF sekvenssi-luokittelijaa laajalla piirrejoukolla. Kaikki kokeillut teksin analyysimenetelmät auttavat luokittelussa, joista tärkeimmän panoksen antaa morfologinen analyysi.

Heat Demand Forecasting Models’ Development: Use of Data Mining Tools in SQL Server Analysis Services

This thesis introduces heat demand forecasting models which are generated by using data mining algorithms. The forecast spans one full day and this forecast can be used in regulating heat consumption of buildings. For training the data mining models, two years of heat consumption data from a case building and weather measurement data from Finnish Meteorological Institute are used. The thesis utilizes Microsoft SQL Server Analysis Services data mining tools in generating the data mining models and CRISP-DM process framework to implement the research. Results show that the built models can predict heat demand at best with mean average percentage errors of 3.8% for 24-h profile and 5.9% for full day. A deployment model for integrating the generated data mining models into an existing building energy management system is also discussed.

Telahiomon tuotannon läpimenoajan ja laadun optimointi

Tämän diplomityön tarkoituksena on tunnistaa UPM Kymin telahiomon tuotannon läpimenoaikaan sekä laatuun vaikuttavia tekijöitä ja löytää keinot niiden optimoimiseksi, jotta hiontatuotannon kustannustehokkuus parantuisi. Tutkimusmenetelminä työssä käytetään Kymin telahiomon tuotannon läpimenoaikojen telakohtaista mittaamista ja hionnasta tehtyjen mittausraporttien, pinnoituksista ja hionnoista tehtyjen ostotilauksien sekä SAP R/3-toiminnanohjausjärjestelmästä saatavan kunnossapitodatan tutkintaa. Tiedon lähteenä on käytetty myös kirjallisuutta ja UPM henkilöstön sekä toimittajien haastatteluita. Muiden telahiomojen aikaansaamaan laatuun ja tuotannon läpimenoaikaan verrattuna Kymin telahiomon keskimääräiset hiontatuotannon läpimenoajat ovat telasta riippuen kaksinkertaisia tai jopa lähes nelinkertaisia, vaikka pinnankarheus jää osassa teloista alle asetetun tavoitteen. Telahiomojen muototoleransseissa ei ole niin merkittäviä eroja, mitkä selittäisivät Kymin pidemmät hiontatuotannon läpimenoajat. Tämän takia muototoleransseja ei ole päädytty muuttamaan työn aikana, mutta käyttökokemusten mukaan pinnankarheusvaatimusta voidaan laskea. Telahiontaprosessin muotohiontavaihe on suurin hiontatuotannon läpimenoaikaan ja kustannuksiin vaikuttava tekijä. Hiontamenetelmien ja hionta-arvojen optimoimisella, hiontatyökalujen lastuamiskyvyn ylläpitämisellä, telahiontatuotannon yliprosessoinnin ehkäisyllä ja laatutoleransseihin tyytymisellä voidaan lyhentää kymmeniä tunteja telahiomon tuotannon läpimenoaikaa. Mittausraporttien mukaan merkittävin muutos telahiontaprosessin kustannuksiin ja hiontatuotannon läpimenoaikaan saadaan noudattamalla laatutoleransseja. Telojen kunnossapitoon liittyviä kustannuksia syntyy turhaan lisää, kun vaihdetaan ja hiotaan käyttökelpoisia teloja sekä uudelleen pinnoitetaan teloja, joiden pinnoitepaksuus on vielä riittävä. Pinnoitepaksuuden seurannalla voidaan minimoida telojen ennenaikaiset uudelleenpinnoitukset. Mittalaitteiden avulla pystyy optimoimaan telojen hiontavälit. Hiontavälien optimointi lyhentää myös hiontajonoa. Tällöin voidaan hyödyntää suunnitellun hiontajärjestyksen tuomia etuja tehokkaammin ja saavuttaa nopeampia tuotannon läpimenoaikoja.

Press forming of paperboard – advancement of converting tools and process control

Press forming is nowadays one of the most common industrial methods in use for producing deeper trays from paperboard. Demands for material properties like recyclability and sustainability have increased also in the packaging industry, but there are still limitations related to the formability of paperboard. A majority of recent studies have focused on material development, but the potential of the package manufacturing process can also be improved by the development of tooling and process control. In this study, advanced converting tools (die cutting tools and the press forming mould) are created for production scale paperboard tray manufacturing. Also monitoring methods that enable the production of paperboard trays with enhanced quality, and can be utilized in process control are developed. The principles for tray blank preparation, including creasing pattern and die cutting tool design are introduced. The mould heating arrangement and determination of mould clearance are investigated to improve the quality of the press formed trays. The effect of the spring back of the tray walls on the tray dimensions can be managed by adjusting the heat-related process parameters and estimating it at the mould design stage. This enables production speed optimization as the process parameters can be adjusted more freely. Real-time monitoring of pressing force by using multiple force sensors embedded in the mould structure can be utilized in the evaluation of material characteristics on a modified production machinery. Comprehensive process control can be achieved with a combination of measurement of the outer dimensions of the trays and pressing force monitoring. The control method enables detection of defects and tracking changes in the material properties. The optimized converting tools provide a basis for effective operation of the control system.

Data analysis tools and methods for DNA microarray and high-throughput sequencing data

The recent rapid development of biotechnological approaches has enabled the production of large whole genome level biological data sets. In order to handle thesedata sets, reliable and efficient automated tools and methods for data processingand result interpretation are required. Bioinformatics, as the field of studying andprocessing biological data, tries to answer this need by combining methods and approaches across computer science, statistics, mathematics and engineering to studyand process biological data. The need is also increasing for tools that can be used by the biological researchers themselves who may not have a strong statistical or computational background, which requires creating tools and pipelines with intuitive user interfaces, robust analysis workflows and strong emphasis on result reportingand visualization. Within this thesis, several data analysis tools and methods have been developed for analyzing high-throughput biological data sets. These approaches, coveringseveral aspects of high-throughput data analysis, are specifically aimed for gene expression and genotyping data although in principle they are suitable for analyzing other data types as well. Coherent handling of the data across the various data analysis steps is highly important in order to ensure robust and reliable results. Thus,robust data analysis workflows are also described, putting the developed tools andmethods into a wider context. The choice of the correct analysis method may also depend on the properties of the specific data setandthereforeguidelinesforchoosing an optimal method are given. The data analysis tools, methods and workflows developed within this thesis have been applied to several research studies, of which two representative examplesare included in the thesis. The first study focuses on spermatogenesis in murinetestis and the second one examines cell lineage specification in mouse embryonicstem cells.

Vaakatasossa toimivan modulaarisen pakkausyksikön prässin suunnittelu kartonkipakkauksille

Kartonkivuokien käyttö elintarviketeollisuudessa on kasvanut vuosi vuodelta ja kuluttajat ovat löytäneet kartonkipakkaukset niiden ekologisuuden, graafisen ulkoasun sekä turvallisuuden ansiosta. Vuokien valmistus mekaanisella prässäyksellä kehittyy jatkuvasti ja uusi teknologia mahdollistaa täysin uudentyyppisten prässien valmistuksen. Työn tavoitteena on tutkia voidaanko mekaaninen prässäys toteuttaa vaakatasossa uutta teknologiaa hyödyntämällä kustannustehokkaasti. Lisäksi tavoitteena on selvittää, millä voimantuottomenetelmällä prässiltä vaadittava voimantuotto on edullisinta toteuttaa. Suunnittelussa otetaan huomioon olemassa olevat työkalut, modulaarisuus, EU:n elintarvikelainsäädäntö sekä muut kriittiset tekijät. Työssä sovelletaan metodisen konstruoinnin mukaisesti systemaattista ongelmanratkaisua (VDI 2221). Lisäksi työssä käydään läpi kilpaileva menetelmä arvoanalyysi. Suunnittelua ja komponenttivalintoja analysoidaan SWOT- sekä pisteanalyysien avulla. Suunnittelussa syntyneiden ratkaisujen lujuusominaisuuksia tarkastellaan FEM-analyysillä. Tuloksista havaittiin, että vaakatasossa suoritettava prässäyksen voimantuotto on edullisinta ja yksinkertaisinta toteuttaa sähkömekaniikalla, että halutut ominaisuudet voidaan saavuttaa ja rakenne pitää mahdollisimman kompaktina. Kustannustehokkuuden saavuttamiseksi hankinnat on syytä kilpailuttaa huolellisesti. Työn lopussa esitetään mahdollisia jatkokehityskohteita, joita syntyi tämän diplomityön aikana.

Heat-transfer improvements in an axial-flux permanent-magnet synchronous machine

Axial-flux machines tend to have cooling difficulties since it is difficult to arrange continuous heat path between the stator stack and the frame. One important reason for this is that no shrink fitting of the stator is possible in an axial-flux machine. Using of liquid-cooled end shields does not alone solve this issue. Cooling of the rotor and the end windings may also be difficult at least in case of two-stator-single-rotor construction where air circulation in the rotor and in the end-winding areas may be difficult to arrange. If the rotor has significant losses air circulation via the rotor and behind the stator yokes should be arranged which, again, weakens the stator cooling. In this paper we study a novel way of using copper bars as extra heat transfer paths between the stator teeth and liquid cooling pools in the end shields. After this the end windings still suffer of low thermal conductivity and means for improving this by high-heat-conductance material was also studied. The design principle of each cooling system is presented in details. Thermal models based on Computational Fluid Dynamics (CFD) are used to analyse the temperature distribution in the machine. Measurement results are provided from different versions of the machine. The results show that significant improvements in the cooling can be gained by these steps.

Evaluation of Machine Learning Classifiers for Mobile Network Intrusion Detection Systems

Mobile malwares are increasing with the growing number of Mobile users. Mobile malwares can perform several operations which lead to cybersecurity threats such as, stealing financial or personal information, installing malicious applications, sending premium SMS, creating backdoors, keylogging and crypto-ransomware attacks. Knowing the fact that there are many illegitimate Applications available on the App stores, most of the mobile users remain careless about the security of their Mobile devices and become the potential victim of these threats. Previous studies have shown that not every antivirus is capable of detecting all the threats; due to the fact that Mobile malwares use advance techniques to avoid detection. A Network-based IDS at the operator side will bring an extra layer of security to the subscribers and can detect many advanced threats by analyzing their traffic patterns. Machine Learning(ML) will provide the ability to these systems to detect unknown threats for which signatures are not yet known. This research is focused on the evaluation of Machine Learning classifiers in Network-based Intrusion detection systems for Mobile Networks. In this study, different techniques of Network-based intrusion detection with their advantages, disadvantages and state of the art in Hybrid solutions are discussed. Finally, a ML based NIDS is proposed which will work as a subsystem, to Network-based IDS deployed by Mobile Operators, that can help in detecting unknown threats and reducing false positives. In this research, several ML classifiers were implemented and evaluated. This study is focused on Android-based malwares, as Android is the most popular OS among users, hence most targeted by cyber criminals. Supervised ML algorithms based classifiers were built using the dataset which contained the labeled instances of relevant features. These features were extracted from the traffic generated by samples of several malware families and benign applications. These classifiers were able to detect malicious traffic patterns with the TPR upto 99.6% during Cross-validation test. Also, several experiments were conducted to detect unknown malware traffic and to detect false positives. These classifiers were able to detect unknown threats with the Accuracy of 97.5%. These classifiers could be integrated with current NIDS', which use signatures, statistical or knowledge-based techniques to detect malicious traffic. Technique to integrate the output from ML classifier with traditional NIDS is discussed and proposed for future work.

Ympäristö- ja turvallisuustoiminnan kehittäminen kemikaaleja käyttävissä konepajoissa

Tämä diplomityö tehtiin Sampo-Rosenlewin Porin tehtaan toimeksiannosta. Työn tavoitteena oli kehittää ympäristö- ja turvallisuustoimintaa tehtaalla. Ympäristö- ja turvallisuustoimintaa kehitettiin luomalla toimintajärjestelmä sekä valitsemalla riskienhallintamenetelmä POA. Uusien työkalujen tuonti mukaan toimintakulttuuriin todettiin haastavaksi, sillä turvallisuus- ja ympäristökulttuuri on vielä matalalla tasolla. Ympäristö- ja turvallisuustoiminnan tasoa ja hallintakeinoja tutkittiin benchmarkkaamalla kolmea saman kokoluokan teollisuusyritystä ja keräämällä hyväksi todettuja metodeja toimintajärjestelmään. Sampo-Rosenlew on Porissa sijaitseva konepaja, joka valmistaa leikkuupuimureita ja metsäkoneita. Sampo-Rosenlew käyttää konepajana paljon kemikaaleja johtuen kolmesta maalaamostaan. Työn tavoitteena oli parantaa Sampo-Rosenlewin ympäristö- ja turvallisuusasioiden nykyistä tilaa erilaisten työkalujen avulla, joita yritykselle luotiin. Työssä kehitettiin Sampo-Rosenlewille toimintajärjestelmä ISO 14001 ympäristöjärjestelmästandardia ja OHSAS 18001 TTT- järjestelmästandardia mukaillen. Luotu toimintajärjestelmä on tulevaisuudessa tavoitteena sertifioida. Valittua riskianalyysimenetelmä POA:aa tullaan pilottivaiheessa testaamaan aluksi yrityksen maalaamoissa. Toimintajärjestelmä ja riskienhallintamenetelmä pyrittiin luomaan mahdollisimman yksinkertaiseksi, selkeäksi ja helpoksi kehittää. Näiden menetelmien käyttöönoton onnistumiseen vaikuttavat nykyinen toimintakulttuuri ja ylimmän johdon sitoutuminen asiaan. Järjestelmän käyttöönoton myötä on tavoitteena Sampo-Rosenlewin dokumentoinnin tason parantaminen ja kilpailukyvyn tehostaminen.

Design and implementation of machine vision system for the mobile assembly robot

The review of intelligent machines shows that the demand for new ways of helping people in perception of the real world is becoming higher and higher every year. This thesis provides information about design and implementation of machine vision for mobile assembly robot. The work has been done as a part of LUT project in Laboratory of Intelligent Machines. The aim of this work is to create a working vision system. The qualitative and quantitative research were done to complete this task. In the first part, the author presents the theoretical background of such things as digital camera work principles, wireless transmission basics, creation of live stream, methods used for pattern recognition. Formulas, dependencies and previous research related to the topic are shown. In the second part, the equipment used for the project is described. There is information about the brands, models, capabilities and also requirements needed for implementation. Although, the author gives a description of LabVIEW software, its add-ons and OpenCV which are used in the project. Furthermore, one can find results in further section of considered thesis. They mainly represented by screenshots from cameras, working station and photos of the system. The key result of this thesis is vision system created for the needs of mobile assembly robot. Therefore, it is possible to see graphically what was done on examples. Future research in this field includes optimization of the pattern recognition algorithm. This will give less response time for recognizing objects. Presented by author system can be used also for further activities which include artificial intelligence usage.