15 resultados para Consumption Predicting Model

em Doria (National Library of Finland DSpace Services) - National Library of Finland, Finland


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Kustannuslaskennan ala on muuttumassa. IT teknologian hämmästyttävän nopea kehitys viime vuosina on luonut kustannuslaskennalle uusia mahdollisuuksia. Toisaalta myös kustannuslaskennalle asetetut vaatimukset ovat muuttuneet. Nykyisin kustannustietoutta tarvitaan erityisesti päätöksenteon tueksi. Kaikesta huolimatta yleisesti käytetyt laskentamenetelmät eivät ole muuttuneet. Työn tavoite on tutkia mahdollisia tapoja tuotekohtaisen kustannuslaskennan toteuttamiseksi SAP toiminnanohjausjärjestelmän avulla. Erityisesti toiminnanohjausjärjestelmien nopea kehitys on mahdollistanut aikaisempaa nopeamman ja tarkemman kustannuslaskennan. On kuitenkin muistettava, että järjestelmät ovat vaintyökaluja. On siis erittäin tärkeää valita tarkoituksenmukainen laskentamenetelmä. Työn perimmäinen tarkoitus onkin valita kyseessä olevaan tilanteeseen sopivin menetelmä.Viime vuosien akateemisessa kirjoittelussa on esitelty useita uusia kustannuslaskentamenetelmiä. Toimintolaskennan uusi versio, Time-Driven Activity-Based Costing, on eräs varteenotettava vaihtoehto tuotekohtaisen kustannuslaskennan toteuttamiseksi SAP-ympäristössä. Toinen hyvin soveltuva menetelmä on Resource Consumption Accounting (RCA), joka soveltuu erityisen hyvin SAP-ympäristöön.Molemmilla menetelmillä on hyvät ja huonot puolet, mutta tässä tapauksessa RCA soveltuu tehtävään paremmin. RCA on joustava ja tarjoaa laaja-alaista tietoa. Tästä syystä Resource Consumption Accounting oli paras vaihtoehto.Työssä rakennettu RCA malli testattiin kolmen erilaisen tuotteen historiallisella datalla. RCA:ntuomia mahdollisuuksia pohdittiin ja ongelmia selvitettiin. RCA on hyvin saman tyyppinen yrityksessä jo käytettävän laskentamenetelmän kanssa. Implementointi ei siis olisi mahdoton tehtävä. RCA kuitenkin tarjoaa mahdollisuuksia, joita nykyisellä menetelmällä ei voida saavuttaa.

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Työn tavoitteena on selvittää voidaanko neuroverkkoa käyttää mallintamaan ja ennustamaan polttoaineen vaikutusta nykyaikaisen auton päästöihin. Näin pystyttäisiin vähentämään aikaa vievien ja kalliiden koeajojen tarvetta. Työ tehtiin Lappeenrannan teknillisen yliopiston ja Fortum Oy:n yhteistyöprojektissa. Työssä tehtiin kolme erilaista mallia. Ensimmäisenä tehtiin autokohtainen malli, jolla pyrittiin ennustamaan autokohtaista käyttäytymistä. Toiseksi kokeiltiin mallia, jossa automalli oli yhtenä syötteenä. Kolmantena yritettiin kiertää eräitä aineiston ongelmia käyttämällä "sumeutettuja" polttoaineiden koostumuksia. Työssä käytettiin MLP-neuroverkkoa, joka opetettiin backpropagation algoritmilla. Työssä havaittiin ettei käytettävissä olleella aineistolla ja käytetyillä malleilla pystytä riittävällä tarkkuudella mallintamaan polttoaineen vaikutusta päästöihin. Aineiston ongelmia olivat mm. suuret mittausvarianssit, aineiston pieni määrä sekä aineiston soveltumattomuus neuroverkolla mallintamiseen.

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Kilpailulliset tekijät ovat johtaneet paperin valmistajat miettimään keinoja valmistuskustannusten leikkaamiseksi. Yksi keino on optimoida raaka-aineiden käyttöä, jota on tehty tässä diplomityössä. Työn tarkoitus on selvittää koeajoin mahdollisuudet kalliimpien raaka-aineiden korvaamiseen edullisemmilla, säilyttäen kuitenkin pohjapaperin laadulliset ominaisuudet. Työ on toteutettu UPM Kymmene Oyj:n Jokilaakson tehtailla, Jämsänkosken paperitehtaan Tarrapaperit-osastolla. Työssä on käytetty apuna tietokoneohjelmia mallintamaan ja simuloimaan paperissa ja paperin kustannusrakenteessa tapahtuvia muutoksia, mutta merkittävimmässä asemassa ovat olleet koeajot ja erilaisten näytteiden käsittely. Raaka-aineina käytettävien massojen osuuksien optimoinnilla on saatu aikaiseksi merkittäviä kustannussäästöjä, mutta työn yhteydessä on löydetty myös keinoja säästöjen saavuttamiseksi energiankulutusta järkevöittämällä. Luotu malli auttaa jatkossa kustannusrakenteen seurannassa. Mäntysellun osuuden laskulla ja täyteaineen osuuden nostolla saavutetaan merkittävimmät kustannussäästöt, kemihierteellä vaikutus kustannuksiin on vähäisempi. Sähköenergiaa vievä kuitujen jauhatus on järjestetty paperikone 3:lla uudella tavalla, jolla on paitsi saavutettu säästöä energiassa, parannettu myös paperin lujuutta.

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The power is still today an issue in wearable computing applications. The aim of the present paper is to raise awareness of the power consumption of wearable computing devices in specific scenarios to be able in the future to design energy efficient wireless sensors for context recognition in wearable computing applications. The approach is based on a hardware study. The objective of this paper is to analyze and compare the total power consumption of three representative wearable computing devices in realistic scenarios such as Display, Speaker, Camera and microphone, Transfer by Wi-Fi, Monitoring outdoor physical activity and Pedometer. A scenario based energy model is also developed. The Samsung Galaxy Nexus I9250 smartphone, the Vuzix M100 Smart Glasses and the SimValley Smartwatch AW-420.RX are the three devices representative of their form factors. The power consumption is measured using PowerTutor, an android energy profiler application with logging option and using unknown parameters so it is adjusted with the USB meter. The result shows that the screen size is the main parameter influencing the power consumption. The power consumption for an identical scenario varies depending on the wearable devices meaning that others components, parameters or processes might impact on the power consumption and further study is needed to explain these variations. This paper also shows that different inputs (touchscreen is more efficient than buttons controls) and outputs (speaker sensor is more efficient than display sensor) impact the energy consumption in different way. This paper gives recommendations to reduce the energy consumption in healthcare wearable computing application using the energy model.

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As the development of integrated circuit technology continues to follow Moore’s law the complexity of circuits increases exponentially. Traditional hardware description languages such as VHDL and Verilog are no longer powerful enough to cope with this level of complexity and do not provide facilities for hardware/software codesign. Languages such as SystemC are intended to solve these problems by combining the powerful expression of high level programming languages and hardware oriented facilities of hardware description languages. To fully replace older languages in the desing flow of digital systems SystemC should also be synthesizable. The devices required by modern high speed networks often share the same tight constraints for e.g. size, power consumption and price with embedded systems but have also very demanding real time and quality of service requirements that are difficult to satisfy with general purpose processors. Dedicated hardware blocks of an application specific instruction set processor are one way to combine fast processing speed, energy efficiency, flexibility and relatively low time-to-market. Common features can be identified in the network processing domain making it possible to develop specialized but configurable processor architectures. One such architecture is the TACO which is based on transport triggered architecture. The architecture offers a high degree of parallelism and modularity and greatly simplified instruction decoding. For this M.Sc.(Tech) thesis, a simulation environment for the TACO architecture was developed with SystemC 2.2 using an old version written with SystemC 1.0 as a starting point. The environment enables rapid design space exploration by providing facilities for hw/sw codesign and simulation and an extendable library of automatically configured reusable hardware blocks. Other topics that are covered are the differences between SystemC 1.0 and 2.2 from the viewpoint of hardware modeling, and compilation of a SystemC model into synthesizable VHDL with Celoxica Agility SystemC Compiler. A simulation model for a processor for TCP/IP packet validation was designed and tested as a test case for the environment.

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COD discharges out of processes have increased in line with elevating brightness demands for mechanical pulp and papers. The share of lignin-like substances in COD discharges is on average 75%. In this thesis, a plant dynamic model was created and validated as a means to predict COD loading and discharges out of a mill. The assays were carried out in one paper mill integrate producing mechanical printing papers. The objective in the modeling of plant dynamics was to predict day averages of COD load and discharges out of mills. This means that online data, like 1) the level of large storage towers of pulp and white water 2) pulp dosages, 3) production rates and 4) internal white water flows and discharges were used to create transients into the balances of solids and white water, referred to as “plant dynamics”. A conversion coefficient was verified between TOC and COD. The conversion coefficient was used for predicting the flows from TOC to COD to the waste water treatment plant. The COD load was modeled with similar uncertainty as in reference TOC sampling. The water balance of waste water treatment was validated by the reference concentration of COD. The difference of COD predictions against references was within the same deviation of TOC-predictions. The modeled yield losses and retention values of TOC in pulping and bleaching processes and the modeled fixing of colloidal TOC to solids between the pulping plant and the aeration basin in the waste water treatment plant were similar to references presented in literature. The valid water balances of the waste water treatment plant and the reduction model of lignin-like substances produced a valid prediction of COD discharges out of the mill. A 30% increase in the release of lignin-like substances in the form of production problems was observed in pulping and bleaching processes. The same increase was observed in COD discharges out of waste water treatment. In the prediction of annual COD discharge, it was noticed that the reduction of lignin has a wide deviation from year to year and from one mill to another. This made it difficult to compare the parameters of COD discharges validated in plant dynamic simulation with another mill producing mechanical printing papers. However, a trend of moving from unbleached towards high-brightness TMP in COD discharges was valid.

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In this work a fuzzy linear system is used to solve Leontief input-output model with fuzzy entries. For solving this model, we assume that the consumption matrix from di erent sectors of the economy and demand are known. These assumptions heavily depend on the information obtained from the industries. Hence uncertainties are involved in this information. The aim of this work is to model these uncertainties and to address them by fuzzy entries such as fuzzy numbers and LR-type fuzzy numbers (triangular and trapezoidal). Fuzzy linear system has been developed using fuzzy data and it is solved using Gauss-Seidel algorithm. Numerical examples show the e ciency of this algorithm. The famous example from Prof. Leontief, where he solved the production levels for U.S. economy in 1958, is also further analyzed.

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Comprehensive understanding of the heat transfer processes that take place during circulating fluidized bed (CFB) combustion is one of the most important issues in CFB technology development. This leads to possibility of predicting, evaluation and proper design of combustion and heat transfer mechanisms. The aim of this thesis is to develop a model for circulating fluidized bed boiler operation. Empirical correlations are used for determining heat transfer coefficients in each part of the furnace. The proposed model is used both in design and offdesign conditions. During off-design simulations fuel moisture content and boiler load effects on boiler operation have been investigated. In theoretical part of the thesis, fuel properties of most typical classes of biomass are widely reviewed. Various schemes of biomass utilization are presented and, especially, concerning circulating fluidized bed boilers. In addition, possible negative effects of biomass usage in boilers are briefly discussed.

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This thesis presents a set of methods and models for estimation of iron and slag flows in the blast furnace hearth and taphole. The main focus was put on predicting taphole flow patterns and estimating the effects of various taphole conditions on the drainage behavior of the blast furnace hearth. All models were based on a general understanding of the typical tap cycle of an industrial blast furnace. Some of the models were evaluated on short-term process data from the reference furnace. A computational fluid dynamics (CFD) model was built and applied to simulate the complicated hearth flows and thus to predict the regions of the hearth exerted to erosion under various operating conditions. Key boundary variables of the CFD model were provided by a simplified drainage model based on the first principles. By examining the evolutions of liquid outflow rates measured from the furnace studied, the drainage model was improved to include the effects of taphole diameter and length. The estimated slag delays showed good agreement with the observed ones. The liquid flows in the taphole were further studied using two different models and the results of both models indicated that it is more likely that separated flow of iron and slag occurs in the taphole when the liquid outflow rates are comparable during tapping. The drainage process was simulated with an integrated model based on an overall balance analysis: The high in-furnace overpressure can compensate for the resistances induced by the liquid flows in the hearth and through the taphole. Finally, a recently developed multiphase CFD model including interfacial forces between immiscible liquids was developed and both the actual iron-slag system and a water-oil system in laboratory scale were simulated. The model was demonstrated to be a useful tool for simulating hearth flows for gaining understanding of the complex phenomena in the drainage of the blast furnace.

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This master’s thesis studies the probability of bankruptcy of Finnish limited liability companies as a part of credit risk assessment. The main idea of this thesis is to build and test bankruptcy prediction models for Finnish limited liability companies that can be utilized in credit decision making. The data used in this thesis consists of historical financial statements from 2112 Finnish limited liability companies, half of which have filed for bankruptcy. A total of four models are developed, two with logistic regression and two with multivariate discriminant analysis (MDA). The time horizon of the models varies from 1 to 2 years prior to the bankruptcy, and 14 different financial variables are used in the model formation. The results show that the prediction accuracy of the models ranges between 81.7% and 88.9%, and the best prediction accuracy is achieved with the one year prior the bankruptcy logistic regression model. However the difference between the best logistic model and the best MDA model is minimal. Overall based on the results of this thesis it can be concluded that predicting bankruptcy is possible to some extent, but naturally the results are not perfect.

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The energy consumption of IT equipments is becoming an issue of increasing importance. In particular, network equipments such as routers and switches are major contributors to the energy consumption of internet. Therefore it is important to understand how the relationship between input parameters such as bandwidth, number of active ports, traffic-load, hibernation-mode and their impact on energy consumption of a switch. In this paper, the energy consumption of a switch is analyzed in extensive experiments. A fuzzy rule-based model of energy consumption of a switch is proposed based on the result of experiments. The model can be used to predict the energy saving when deploying new switches by controlling the parameters to achieve desired energy consumption and subsequent performance. Furthermore, the model can also be used for further researches on energy saving techniques such as energy-efficient routing protocol, dynamic link shutdown, etc.

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At present, one of the main concerns of green network is to minimize the power consumption of network infrastructure. Surveys show that, the highest amount of power is consumed by the network devices during its runtime. However to control this power consumption it is important to know which factors has highest impact on this matter. This paper is focused on the measurement and modeling the power consumption of an Ethernet switch during its runtime considering various types of input parameters with all possible combinations. For the experiment, three input parameters are chosen. They are bandwidth, link load and number of connections. The output to be measured is the power consumption of the Ethernet switch. Due to the uncertain power consuming pattern of the Ethernet switch a fully-comprehensive experimental evaluation would require an unfeasible and cumbersome experimental phase. Because of that, design of experiment (DoE) method has been applied to obtain adequate information on the effects of each input parameters on the power consumption. The whole work consists of three parts. In the first part a test bed is planned with input parameters and the power consumption of the switch is measured. The second part is about generating a mathematical model with the help of design of experiment tools. This model can be used for measuring precise power consumption in different scenario and also pinpoint the parameters with higher influence in power consumption. And in the last part, the mathematical model is evaluated by comparing with the experimental values.

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Climate change is one of the biggest challenges faced by this generation. Despite being the single most important environmental challenge facing the planet and despite over two decades of international climate negotiations, global greenhouse gas (GHG) emissions continue to rise. By the middle of this century, GHGs must be reduced by as much as 40-70% if dangerous climate change is to be avoided. In the Kyoto Protocol no quantitative emission limitation and reduction commitments were placed on the developing countries. For the planning of the future commitments period and possible participation of developing countries, information of the functioning of the energy systems, CO2 emissions development in different sectors, energy use and technological development in developing countries is essential. In addition to the per capita emissions, the efficiency of the energy system in relation to GHG emissions is crucial for the decision of future long-term burden sharing between countries. Country’s future development of CO2 emissions can be defined by the estimated CO2 intensity of the future and the estimated GDP growth. The changes in CO2 intensity depend on several factors, but generally developed countries’ intensity has been increasing in the industrialization phase and decreasing when their economy shifts more towards the system dominated by the service sector. The level of the CO2 intensity depends by a large extent on the production structure and the energy sources that are used. Currently one of the most urgent issues regarding global climate change is to decide the future of the Kyoto Protocol. Negotiations on this topic have already been initiated, with the aim of being finalised by the 2015. This thesis provides insights into the various approaches that can be used to characterise the concept of comparable efforts for developing countries in a future international climate agreement. The thesis examines the post-Kyoto burden sharing questions for developing countries using the contraction and convergence model, which is one approach that has been proposed to allocate commitments regarding future GHG emissions mitigation. This new approach is a practical tool for the evaluation of the Kyoto climate policy process and global climate change negotiations from the perspective of the developing countries.

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In this thesis the consumers’ expected motives and barriers for engaging in collaborative consumption in Finland are studied. The phenomenon is observed through the lens of consumer theory and it is connected to the context using Hofstede’s 6-D model. The phenomenon is new and there are almost no recorded results in the background research, and when considering the limitations of this study, there are no results at all. Therefore, combining different kinds of literature, as well as taking along consumer theory and Hofstede’s model that explains cultural factors, it was possible to compile a comprehensive general view of the present state of the phenomenon. The actual study was conducted using qualitative methods and the solution was sought collecting data from six in-depth interviews with interviewees having experience from using, or offering resources, or both. According to the results, the primary motive in all modes of consumption was economic. Anti-materialism, anti-consumption, and expanding lifestyle were another a bit more general motives. Perceived barriers were, especially as a new result, the amount of trouble one has to see and in single modes, a lack of trust, the used platform and too expensive prices.