114 resultados para Climate Engineering


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Systems suppliers are focal actors in mechanical engineering supply chains, in between general contractors and component suppliers. This research concentrates on the systems suppliers’ competitive flexibility, as a competitive advantage that the systems supplier gains from independence from the competitive forces of the market. The aim is to study the roles that power, dependence relations, social capital, and interorganizational learning have on the competitive flexibility. Research on this particular theme is scarce thus far. The research method applied here is the inductive multiple case study. Interviews from four case companies were used as main source of the qualitative data. The literature review presents previous literature on subcontracting, supply chain flexibility, supply chain relationships, social capital and interorganizational learning. The result of this study are seven propositions and consequently a model on the effects that the dominance of sales of few customers, power of competitors, significance of the manufactured system in the end product, professionalism in procurement and the significance of brand products in the business have on the competitive flexibility. These relationships are moderated by either social capital or interorganizational learning. The main results obtained from this study revolve around social capital and interorganizational learning, which have beneficial effects on systems suppliers’ competitive flexibility, by moderating the effects of other constructs of the model. Further research on this topic should include quantitative research to provide the extent to which the results can be reliably generalized. Also each construct of the model gives possible focus for more thorough research.

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Aiheen laajempi artikkeli on julkaistu konferenssi-CD:llä.

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Climate innovations, that cover both technological applications and process and service innovations, play a key role in climate change mitigation. The purpose of this study was to examine how the Finnish innovation system could be enhanced with governmental measures so that the diffusion of climate innovations could be speeded up. During the study, it became evident that the governmental measures need to support the whole innovation chain, which comprises of research, development, demonstration and deployment. Only this can lead to the successful birth and diffusion of low carbon innovations. The study found that the strengths of the Finnish innovation system are research and development, and the current national innovation policies strongly support these activities. However, these have been emphasised at the expense of the demonstration and deployment. Consequently, the biggest bottlenecks in the Finnish innovation landscape are the lack of pilot and demonstration projects and slow commercialisation, thus the high price of the innovation. To meet with the challenge, the government should firstly promote strict greenhouse gas emission reduction targets. This would boost up the innovation activities, which would also lower the prices of the innovations. To speed up the commercialisation process, measures that stimulate the domestic market, such as feed-in-tariffs and public procurements, are needed. Special attention should also be paid to the measures that could shift the traditional closed innovation chain towards open innovation. This means that the product development should involve experts from several fields such as the user and marketing experts to speed up the commercialisation. In addition, efficient innovation co-operation between both private and public sector is essential. Finally, as the domestic resources are not adequate for producing all the innovations needed, the domestic innovation activities should be focused on a few sectors, and at the same time promote efficient import policies.

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The purpose of this study was to investigate the nature of co-operation between a project owner and an outside engineering consultant in combined heat and power plant implementation projects. Moreover, as another focal subject of the study was to familiarize the purchasing behavior of the energy producer and how an outside engineering consultant participated into different stages of the purchasing process. The study was carried out as a multiple case study including altogether six Finnish power plant implementation projects that had been taken into commercial use during 1995 – 2015. By adjusting the findings of empirical interview data and comparing those to the theoretical framework concerning, among others, Finnish energy production, engineering consulting businesses, delivery methods of construction project and finally the purchasing process, it can be concluded that especially in the power plant implementation projects in the past have a great influence to decisions made during the project. The role of the main engineering consultant is to act as an assistant, who helps to achieve the project goals successfully rather than an advisor who only knows how the project should be conducted. At least in these five project cases this was the case, meaning that the final decision power always remaining with project owner.

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Research focus of this thesis is to explore options for building systems for business critical web applications. Business criticality here includes requirements for data protection and system availability. The focus is on open source software. Goals are to identify robust technologies and engineering practices to implement such systems. Research methods include experiments made with sample systems built around chosen software packages that represent certain technologies. The main research focused on finding a good method for database data replication, a key functionality for high-availability, database-driven web applications. Research included also finding engineering best practices from books written by administrators of high traffic web applications. Experiment with database replication showed, that block level synchronous replication offered by DRBD replication software offered considerably more robust data protection and high-availability functionality compared to leading open source database product MySQL, and its built-in asynchronous replication. For master-master database setups, block level replication is more recommended way to build high-availability into the system. Based on thesis research, building high-availability web applications is possible using a combination of open source software and engineering best practices for data protection, availability planning and scaling.

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Segmentointi on perinteisesti ollut erityisesti kuluttajamarkkinoinnin työkalu, mutta siirtymä tuotteista palveluihin on lisännyt segmentointitarvetta myös teollisilla markkinoilla. Tämän tutkimuksen tavoite on löytää selkeästi toisistaan erottuvia asiakasryhmiä suomalaisen liikkeenjohdon konsultointiyritys Synocus Groupin tarjoaman case-materiaalin pohjalta. K-means-klusteroinnin avulla löydetään kolme potentiaalista markkinasegmenttiä perustuen siihen, mitkä tarjoamaelementit 105 valikoitua suomalaisen kone- ja metallituoteteollisuuden asiakasta ovat maininneet tärkeimmiksi. Ensimmäinen klusteri on hintatietoiset asiakkaat, jotka laskevat yksikkökohtaisia hintoja. Toinen klusteri koostuu huolto-orientoituneista asiakkaista, jotka laskevat tuntikustannuksia ja maksimoivat konekannan käyttötunteja. Tälle kohderyhmälle kannattaisi ehkä markkinoida teknisiä palveluja ja huoltosopimuksia. Kolmas klusteri on tuottavuussuuntautuneet asiakkaat, jotka ovat kiinnostuneita suorituskyvyn kehittämisestä ja laskevat tonnikohtaisia kustannuksia. He tavoittelevat alempia kokonaiskustannuksia lisääntyneen suorituskyvyn, pidemmän käyttöiän ja alempien huoltokustannusten kautta.

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Työssä tutkitaan Etelä-Karjalan alueella olevien uusiutuvien energiavarojen lisäämisen mahdollisuuksia sekä energian kulutuksen vähennysmahdollisuuksia energiatehokkuuden avulla pienissä ja keskisuurissa konepaja- ja kunnossapitoyrityksissä. Energiaohjelman pohjalla on EU:n halu jalkauttaa energia- ja ilmastotavoitteensa pieniin ja keskisuuriin yrityksiin. Ohjelma on muodostettu yritysryhmän mielipiteet ja tarpeet, sekä Etelä-Karjalan alueen ominaispiirteet huomioon ottaen. Energiaohjelmaa muodostettaessa perehdyttiin sekä EU:n että Suomen energiapolitiikkaan ja Etelä-Karjalan alueellisiin ominaisuuksiin ja energiantuotantotapoihin. Lisäksi yrityksiä haastateltiin energia-asioista ja niihin liittyvistä asenteista sekä perehdyttiin yritysten energiatehokkuuteen. Haastattelujen ja alueellisen energiarakenteen pohjalta päädyttiin muodostamaan energiaohjelma energiatehokkuuteen painottuen, koska alueen uusiutuvia luonnonvaroja on jo hyödynnetty melko tehokkaasti. Energiaohjelmaa testattiin pilottiprojektissa, joka toteutettiin työssä teoreettisena laskentana. Pilottiprojektin laskennasta saatiin lupaavia tuloksia. Laskennassa käytettävistä arvoista suurin osa saatiin pilottiprojektin yritykseltä tai muista lähteistä, mutta osa arvioitiin itse. Pilottiprojektista saatujen tietojen perusteella voidaan energiaohjelman väittää toimivan ainakin tarkastelussa mukana olleessa yritysryhmässä Etelä-Karjalan alueella. Energiaohjelma voi edistää yritysryhmän energiatehokkuutta vain jos se otetaan yrityksissä käyttöön. Ohjelmaa on mahdollista kehittää lisää muun muassa yksinkertaistamalla laskentaa. Jatkokehittelyllä on mahdollista luoda EU:n alueelle sopiva energiantehokkuustarkasteluun käytettävä ohjelma.

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Työn tarkoituksena on selvittää miten sähköistä kysynnän herättämistä voidaan hyödyntää Mantsinen Group Ltd Oy:ssä siten, että sillä pystytään tukemaan myyntiä. Lisäksi sähköisen kysynnän herättämisen tehokkuutta tutkitaan, jotta saadaan selville onko se kannattavaa ja kuinka hyvin se sopii yritykselle. Kysynnän herättämisjärjestelmän käyttö on määritelty kirjallisuuteen perustuen ja sen jälkeen järjestelmän käyttö on aloitettu. Sähköisen kysynnän herättämisen tehokkuus mitataan kolmen kuukauden tarkastelujakson todellisella datalla. Sähköisen kysynnän herättämisen sopivuutta arvioidaan perustuen sen kustannustehokkuuteen ja tuloksiin. Työn tulokset osoittavat, että sähköinen kysynnän herättäminen on kannattavaa ja se sopii yritykselle. Sillä voidaan parhaiten tukea myyntiä järjestelmän tuottaessa laadukkaita myyntimahdollisuuksia tasaisena virtana myynnille. Myös aiemmin manuaalisesti tehtyjä työtehtäviä voidaan automatisoida ja näin vähentää myyjien työtaakkaa.

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The goal of the master‘s thesis is to determine and estimate ice accretion influence on the wind turbine blade performance. The thesis describes the technique of ice accretion calculation on the wind turbine blade and determination characteristics of the turbine with ice accreted. The methodology of the classic Blade Element Moment Theory was used. Iced blade experimental data was investigated in order to calculate blade with ice characteristics. The obtained results shows that iced blade power coefficient is lower than clean blade one. The heating system implementation shows that in the particular site in the Lapland region it is efficient.

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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.