Vesivoiman ajosuunnittelu

Diplomityön tavoitteena oli tutkia UPM-Kymmene Oyj:n keskusvalvomossa tapahtuvaa vesivoiman ajosuunnittelua. Pääkohdat tarkastelussa olivat vesistöjen säännöstely, erilaiset vesivuodet ja sähkömarkkinatilanteet. Vesivoiman ajosuunnittelua tarkasteltiin pääasiassa erilaisten vesivuosien ja sähkömarkkinatilanteiden näkökulmasta. Lähtötietoina käytettiin Suomen ympäristökeskuksen vesistömallijärjestelmän ja UPM-Kymmene Oyj:n energianhallintajärjestelmän numeerisia historia-arvoja. Työssäselvitettiin UPM-Kymmene Oyj:n vesivarannoista hyödynnettävissä olevat energiamäärät. Energiamäärien avulla määritettiin skenaario UPM-Kymmene Oyj:n vesivoimantuotannon vaihtelusta. Lisäksi tarkasteltiin vesivoimaa sähkötaseen säätövoimana. Teoreettisessa osassa perehdyttiin Suomen sähköntuotantorakenteeseen, vesivoiman asemaan sähköntuotannossa ja vesivoiman ohjausmekanismeihin. Lisäksi tarkasteltiin UPM-Kymmene Oyj:n sähkön käyttöä ja vesivarantoja. Soveltavassa osassa tarkasteltiin, miten vesivoiman ohjausmekanismit toimivat käytännössä. Lisäksi analysoitiin sähkömarkkinatilanteiden vaikutuksia ja vesivoimalaitosten ajon tehostamismahdollisuuksia. Työn tuloksena laadittiin ennuste-simulaattori, jolla voidaan optimoida vesivoimanja lauhdevoiman ajoa. Tulevaisuudessa simulaattorin avulla voidaan ennustaa poikkeuksellisia sähkömarkkinatilanteita.

Estimating the Price and Demand Development of Some Paperboard Grades

Työn tavoitteena oli luoda malli, jonka avulla voitaisiin ennustaa kartonkituotteiden hinnan ja kysynnän kehitystä. Työssä kerättiin aluksi tietoa kartonkimarkkinoista haastattelujen ja tilastotietojen avulla. Näiden perusteella luotiin malli, joka kuvaa kartonkimarkkinoiden ja -teollisuuden rakennetta. Erityisesti kiinnitettiin huomiota asiakkaiden tilauskäyttäytymiseen, tuotannonohjaukseen sekä hinnan muodostumiseen. Työssä käytettiin ennustemenetelmänä systeemidynamiikkaa. Oleellista oli löytää systeemissä esiintyvät tärkeimmät takaisinkytkennät ja systeemin avainmuuttujat. Kun kaikille mallin muuttujille oli määritetty yhtälöt ja vakioille annettu arvot, voitiin mallia simuloida, ja saada ennusteet halutuille muuttujille. Työssä esitettiin ennusteet kartonkimarkkinoiden tärkeimmille parametreille kahden vuoden päähän. Työssä tarkasteltiin myös, miten muutokset mallin käyttäytymistä säätelevissä muuttujissa vaikuttavat tuloksiin. Jotta pystyttäisiin paremmin selvittämään koko kartonkiteollisuuden dynamiikka, lisätutkimusta tarvittaisiin vielä eri kartonkilajien substituutiomahdollisuuksista ja hintojen riippuvuuksista. Mielenkiintoista olisi myös tietää, miten tuotannon käyttöasteiden muutokset ja hinnan vaihtelut vaikuttavat liiketoiminnan kannattavuuteen valmistajien näkökulmasta.

Heikkojen signaalien hyödyntäminen PK-yrityksissä, tapaustutkimus osaamiskeskuksen toimintamalli

Diplomityössä tutkitaan heikkojen signaalien hyödyntämistä pienissä ja keskisuurissa yrityksissä (pk-yritykset). Tutkimuksen pääkysymys on, miten pk-yritykset voivat hyödyntää kansallisten toimijoiden, kuten FinNode Venäjän ja Finpron, tuottamia heikkoja signaaleita päätöksenteossaan. Tutkimuksessa käsitellään heikkoja signaaleja ja ulkoista liiketoimintatietoa. Käsittely pohjautuu kirjallisuudessa esitettyihin keinoihin ja menetelmiin, jotka liittyvät heikkojen signaalien havainnointiin, lähteisiin, keräämiseen ja hyödyntämiseen. Ulkoisen liiketoimintatiedon perustana on informaatioketju ja uuden tiedon luomisen yhteys ulkoisen liiketoimintatiedon hyödyntämiseen. Kirjallisuusmallien avulla on käsitelty myös haasteita, jotka ilmenevät heikkojen signaalien hyödyntämisessä, ja miten ulkoisen liiketoimintatiedon hankinnassa käytettävää prosessia pystytään hyödyntämään osana heikkojen signaalien seulontaa ja analysointia. Diplomityön tutkimusosassa kerättiin teemahaastatteluilla pk-yrityksiltä ja kansallisilta innovaatiojärjestelmän toimijoilta tietoa. Yrityksiltä saatiin tietoa ulkoisen liiketoimintatiedon ja heikkojen signaalien keräämisestä ja hyödyntämisestä. Kansallisilta innovaatiojärjestelmän toimijoilta kerättiin tietoa rakennetusta ennakointijärjestelmästä ja sen hyödynnettävyydestä pk-yrityksissä sekä osaamiskeskusohjelman roolista tiedon välittäjänä. Kirjallisuus ja haastattelut yhdistämällä tutkimuksessa syntyi toimintamalli Kaakkois-Suomen osaamiskeskukselle. Toimintamallin avulla pk-yritykset voivat hyödyntää kansallisen innovaatiojärjestelmän toimijoiden keräämää, liiketoiminnalleen tärkeää signaalitietoa strategiaprosessissaan. Suomen innovaatiojärjestelmä on toimiva ennakoinnin osalta, kun taas pk-yrityksissä ei useinkaan suunnata resursseja ennakointiin ja heikkojen signaalien keräämiseen. Ajankohta toimintamallin käyttöönotolle vaikuttaa tutkimuksen pohjalta sopivalta, sillä järjestelmää on rakennettu ja testattu jo muutamien vuosien ajan.

Combining Advanced Forecasting Methods with System Dynamics - the Case of Finnish Seaports

Seaports play an important part in the wellbeing of a nation. Many nations are highly dependent on foreign trade and most trade is done using sea vessels. This study is part of a larger research project, where a simulation model is required in order to create further analyses on Finnish macro logistical networks. The objective of this study is to create a system dynamic simulation model, which gives an accurate forecast for the development of demand of Finnish seaports up to 2030. The emphasis on this study is to show how it is possible to create a detailed harbor demand System Dynamic model with the help of statistical methods. The used forecasting methods were ARIMA (autoregressive integrated moving average) and regression models. The created simulation model gives a forecast with confidence intervals and allows studying different scenarios. The building process was found to be a useful one and the built model can be expanded to be more detailed. Required capacity for other parts of the Finnish logistical system could easily be included in the model.

A Bayesian Approach for Forecasting Heat Load in a District Heating System

The growing population in cities increases the energy demand and affects the environment by increasing carbon emissions. Information and communications technology solutions which enable energy optimization are needed to address this growing energy demand in cities and to reduce carbon emissions. District heating systems optimize the energy production by reusing waste energy with combined heat and power plants. Forecasting the heat load demand in residential buildings assists in optimizing energy production and consumption in a district heating system. However, the presence of a large number of factors such as weather forecast, district heating operational parameters and user behavioural parameters, make heat load forecasting a challenging task. This thesis proposes a probabilistic machine learning model using a Naive Bayes classifier, to forecast the hourly heat load demand for three residential buildings in the city of Skellefteå, Sweden over a period of winter and spring seasons. The district heating data collected from the sensors equipped at the residential buildings in Skellefteå, is utilized to build the Bayesian network to forecast the heat load demand for horizons of 1, 2, 3, 6 and 24 hours. The proposed model is validated by using four cases to study the influence of various parameters on the heat load forecast by carrying out trace driven analysis in Weka and GeNIe. Results show that current heat load consumption and outdoor temperature forecast are the two parameters with most influence on the heat load forecast. The proposed model achieves average accuracies of 81.23 % and 76.74 % for a forecast horizon of 1 hour in the three buildings for winter and spring seasons respectively. The model also achieves an average accuracy of 77.97 % for three buildings across both seasons for the forecast horizon of 1 hour by utilizing only 10 % of the training data. The results indicate that even a simple model like Naive Bayes classifier can forecast the heat load demand by utilizing less training data.

Mobile Communications within the European Union: The Role of Location in the Evolution and Forecasting of the Diffusion Process

In the European Union, the importance of mobile communications was realized early on. The process of mobile communications becoming ubiquitous has taken time, as the innovation of mobile communications diffused into the society. The aim of this study is to find out how the evolution and spatial patterns of the diffusion of mobile communications within the European Union could be taken into account in forecasting the diffusion process. There is relatively lot of research of innovation diffusion on the individual (micro) andthe country (macro) level, if compared to the territorial level. Territorial orspatial diffusion refers either to the intra-country or inter-country diffusionof an innovation. In both settings, the dif- fusion of a technological innovation has gained scarce attention. This study adds knowledge of the diffusion between countries, focusing especially on the role of location in this process. The main findings of the study are the following: The penetration rates of the European Union member countries have become more even in the period of observation, from the year 1981 to 2000. The common digital GSM system seems to have hastened this process. As to the role of location in the diffusion process, neighboring countries have had similar diffusion processes. They can be grouped into three, the Nordic countries, the central and southern European countries, and the remote southern European countries. The neighborhood effect is also domi- nating in thegravity model which is used for modeling the adoption timing of the countries. The subsequent diffusion within a country, measured by the logistic model in Finland, is af- fected positively by its economic situation, and it seems to level off at some 92 %. Considering the launch of future mobile communications systemsusing a common standard should implicate an equal development between the countries. The launching time should be carefully selected as the diffusion is probably delayed in economic downturns. The location of a country, measured by distance, can be used in forecasting the adoption and diffusion. Fi- nally, the result of penetration rates becoming more even implies that in a relatively homoge- nous set of countries, such as the European Union member countries, the estimated final pene- tration of a single country can be used for approximating the penetration of the others. The estimated eventual penetration of Finland, some 92 %, should thus also be the eventual level for all the European Union countries and for the European Union as a whole.

CREATING A MODEL FOR INVENTORY MANAGEMENT SYSTEM

Tutkielman tarkoituksena oli mallintaa varastonhallintajärjestelmä, joka olisi sopiva case yritykselle. Tutkimus aloitettiin case yrityksen varastonhallinan nykytilan kartoituksella, jonka jälkeen tutkittiin varastonhallinnan eri osa-alueisiin. Varastonhallinnan osa-alueista käsiteltiin varastotyyppejä, motiiveja, tavoitteita, kysynnän ennustamista sekä erilaisia varastonhallinnan työkaluja. Sen lisäksi tutkittiin erilaisia varaston täydennysmalleja. Teoriaosuudessa käsiteltiin lisäksi kolmea erilaista tietojärjestelmätyyppiä: toiminnanohjausjärjestelmää, sähköisen kaupankäynnin järjestelmää sekä räätälöityä järjestelmää. Tutkimussuunnitelmassa nämä kolme järjestelmää rajattiin vaihtoehdoiksi, joista jokin valittaisiin case yrityksen varastonhallintajärjestelmäksi. Teorian ja nykytilan pohjalta tehtiin viitekehys, jossa esiteltiin varastonhallintajärjestelmän tieto- ja toiminnallisuusominaisuuksia. Nämä ominaisuudet priorisoitiin neljään eri luokkaan ominaisuuden kriittisyyden mukaan. Järjestelmävaihtoehdot arvioitiin viitekehyksen kriteerien mukaisesti, miten helposti ominaisuudet olisivat toteutettavissa eri vaihtoehdoissa. Tulokset laskettiin näiden arviointien perusteella, jonka jälkeen tulosten analysoinnissa huomattiin, että toiminnanohjausjärjestelmä sopisi parhaiten case yrityksen varastonhallintajärjestelmäksi.

Researching Manufacturing Planning and Control system and Master Scheduling in a manufacturing firm.

The objective of this thesis is to research Manufacturing Planning and Control (MPC) system and Master Scheduling (MS) in a manufacturing firm. The study is conducted at Ensto Finland Corporation, which operates on a field of electrical systems and supplies. The paper consists of theoretical and empirical parts. The empirical part is based on weekly operating at Ensto and includes inter-firm material analysis, learning and meetings. Master Scheduling is an important module of an MPC system, since it is beneficial on transforming strategic production plans based on demand forecasting into operational schedules. Furthermore, capacity planning tools can remarkably contribute to production planning: by Rough-Cut Capacity Planning (RCCP) tool, a MS plan can be critically analyzed in terms of available key resources in real manufacturing environment. Currently, there are remarkable inefficiencies when it comes to Ensto’s practices: the system is not able to take into consideration seasonal demand and react on market changes on time; This can cause significant lost sales. However, these inefficiencies could be eliminated through the appropriate utilization of MS and RCCP tools. To utilize MS and RCCP tools in Ensto’s production environment, further testing in real production environment is required. Moreover, data accuracy, appropriate commitment to adapting and learning the new tools, and continuous developing of functions closely related to MS, such as sales forecasting, need to be ensured.

Rural Food System Change in Tanzania during the Post-Ujamaa Era. A Case Study from Western Bagamoyo District

Food systems in Sub-Saharan Africa have been rapidly transforming during the recent decades with diverse outcomes on human development and environment. This study explores the food system change in rural villages in eastern Tanzania where subsistence agriculture has traditionally been the main source of livelihood. The focus is on the salient changes in the spatial dimensions and structural composition of the food system in the context of economic liberalization that has taken place after the end of the socialist ujamaa era in the mid-1980s. In addition, the linkages of the changes are examined in relation to food security, socio-economic situation, livelihoods, and local environment. The approach of the study is geographical, but also involves various multi-disciplinary elements, particularly from development studies. The research methods included thematic and questionnaire interviews, participatory tools, and the analysis of land use/ cover data and official documents. Several earlier studies that were made in the area during the late 1970s and 1980s provided an important reference base. The study shows that subsistence farming has lost its dominant role in food provisioning due to the declining productivity of land, livestock losses, and the increasing shift of labour to non-farm sectors. Also rapid population growth has added to the pressure on land and other natural resources. Despite the increasing need for money for buying marketed foods and other necessities, the nutritional situation shows improvement and severe malnutrition has diminished. However, the long-term sustainability of this transformation raises concerns. Firstly, the food security situation continues to be fragile and prone to shocks such as adverse climatic conditions, crop failures and price hikes. Secondly, the commodification of the food system and livelihoods in general is linked to rapid environmental degradation in the area, particularly the loss of soil fertility and deforestation. The situation calls for efforts that take more determined and holistic approaches towards sustainable development of the rural food system with particular focus on the role and viability of small-scale farming.

Development of a measuring-control system for energy monitoring in low power

In this thesis a control system for an intelligent low voltage energy grid is presented, focusing on the control system created by using a multi-agent approach which makes it versatile and easy to expand according to the future needs. The control system is capable of forecasting the future energy consumption and decisions making on its own without human interaction when countering problems. The control system is a part of the St. Petersburg State Polytechnic University’s smart grid project that aims to create a smart grid for the university’s own use. The concept of the smart grid is interesting also for the consumers as it brings new possibilities to control own energy consumption and to save money. Smart grids makes it possible to monitor the energy consumption in real-time and to change own habits to save money. The intelligent grid also brings possibilities to integrate the renewable energy sources to the global or the local energy production much better than the current systems. Consumers can also sell their extra power to the global grid if they want.

Forecasting financial weather - can we foresee market sentiment? Spectrum of stock price behavior - NYSE case study

The desire to create a statistical or mathematical model, which would allow predicting the future changes in stock prices, was born many years ago. Economists and mathematicians are trying to solve this task by applying statistical analysis and physical laws, but there are still no satisfactory results. The main reason for this is that a stock exchange is a non-stationary, unstable and complex system, which is influenced by many factors. In this thesis the New York Stock Exchange was considered as the system to be explored. A topological analysis, basic statistical tools and singular value decomposition were conducted for understanding the behavior of the market. Two methods for normalization of initial daily closure prices by Dow Jones and S&P500 were introduced and applied for further analysis. As a result, some unexpected features were identified, such as a shape of distribution of correlation matrix, a bulk of which is shifted to the right hand side with respect to zero. Also non-ergodicity of NYSE was confirmed graphically. It was shown, that singular vectors differ from each other by a constant factor. There are for certain results no clear conclusions from this work, but it creates a good basis for the further analysis of market topology.

Development of project cash flow forecasting process

Process management refers to improving the key functions of a company. The main functions of the case company - project management, procurement, finance, and human resource - use their own separate systems. The case company is in the process of changing its software. Different functions will use the same system in the future. This software change causes changes in some of the company’s processes. Project cash flow forecasting process is one of the changing processes. Cash flow forecasting ensures the sufficiency of money and prepares for possible changes in the future. This will help to ensure the company’s viability. The purpose of the research is to describe a new project cash flow forecasting process. In addition, the aim is to analyze the impacts of the process change, with regard to the project control department’s workload and resources through the process measurement, and how the impacts take the department’s future operations into account. The research is based on process management. Processes, their descriptions, and the way the process management uses the information, are discussed in the theory part of this research. The theory part is based on literature and articles. Project cash flow and forecasting-related benefits are also discussed. After this, the project cash flow forecasting as-is and to-be processes are described by utilizing information, obtained from the theoretical part, as well as the know-how of the project control department’s personnel. Written descriptions and cross-functional flowcharts are used for descriptions. Process measurement is based on interviews with the personnel – mainly cost controllers and department managers. The process change and the integration of two processes will allow work time for other things, for example, analysis of costs. In addition to the quality of the cash flow information will improve compared to the as-is process. Analyzing the department’s other main processes, department’s roles, and their responsibilities should be checked and redesigned. This way, there will be an opportunity to achieve the best possible efficiency and cost savings.

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.