Production planning and optimization of a pulp mill: introduction of the optimisation based scheduling software for pulp industry

The objective of this project was to introduce a new software product to pulp industry, a new market for case company. An optimization based scheduling tool has been developed to allow pulp operations to better control their production processes and improve both production efficiency and stability. Both the work here and earlier research indicates that there is a potential for savings around 1-5%. All the supporting data is available today coming from distributed control systems, data historians and other existing sources. The pulp mill model together with the scheduler, allows what-if analyses of the impacts and timely feasibility of various external actions such as planned maintenance of any particular mill operation. The visibility gained from the model proves also to be a real benefit. The aim is to satisfy demand and gain extra profit, while achieving the required customer service level. Research effort has been put both in understanding the minimum features needed to satisfy the scheduling requirements in the industry and the overall existence of the market. A qualitative study was constructed to both identify competitive situation and the requirements vs. gaps on the market. It becomes clear that there is no such system on the marketplace today and also that there is room to improve target market overall process efficiency through such planning tool. This thesis also provides better overall understanding of the different processes in this particular industry for the case company.

Cost-efficient virtual machine management : provisioning, admission control, and consolidation

One of the main challenges in Software Engineering is to cope with the transition from an industry based on software as a product to software as a service. The field of Software Engineering should provide the necessary methods and tools to develop and deploy new cost-efficient and scalable digital services. In this thesis, we focus on deployment platforms to ensure cost-efficient scalability of multi-tier web applications and on-demand video transcoding service for different types of load conditions. Infrastructure as a Service (IaaS) clouds provide Virtual Machines (VMs) under the pay-per-use business model. Dynamically provisioning VMs on demand allows service providers to cope with fluctuations on the number of service users. However, VM provisioning must be done carefully, because over-provisioning results in an increased operational cost, while underprovisioning leads to a subpar service. Therefore, our main focus in this thesis is on cost-efficient VM provisioning for multi-tier web applications and on-demand video transcoding. Moreover, to prevent provisioned VMs from becoming overloaded, we augment VM provisioning with an admission control mechanism. Similarly, to ensure efficient use of provisioned VMs, web applications on the under-utilized VMs are consolidated periodically. Thus, the main problem that we address is cost-efficient VM provisioning augmented with server consolidation and admission control on the provisioned VMs. We seek solutions for two types of applications: multi-tier web applications that follow the request-response paradigm and on-demand video transcoding that is based on video streams with soft realtime constraints. Our first contribution is a cost-efficient VM provisioning approach for multi-tier web applications. The proposed approach comprises two subapproaches: a reactive VM provisioning approach called ARVUE and a hybrid reactive-proactive VM provisioning approach called Cost-efficient Resource Allocation for Multiple web applications with Proactive scaling. Our second contribution is a prediction-based VM provisioning approach for on-demand video transcoding in the cloud. Moreover, to prevent virtualized servers from becoming overloaded, the proposed VM provisioning approaches are augmented with admission control approaches. Therefore, our third contribution is a session-based admission control approach for multi-tier web applications called adaptive Admission Control for Virtualized Application Servers. Similarly, the fourth contribution in this thesis is a stream-based admission control and scheduling approach for on-demand video transcoding called Stream-Based Admission Control and Scheduling. Our fifth contribution is a computation and storage trade-o strategy for cost-efficient video transcoding in cloud computing. Finally, the sixth and the last contribution is a web application consolidation approach, which uses Ant Colony System to minimize the under-utilization of the virtualized application servers.

Production Cycle Optimization: Defining the Market Potential for a New Planning Tool

An optimization tool has been developed to help companies to optimize their production cycles and thus improve their overall supply chain management processes. The application combines the functionality that traditional APS (Advanced Planning System) and ARP (Automatic Replenishment Program) systems provide into one optimization run. A qualitative study was organized to investigate opportunities to expand the product’s market base. Twelve personal interviews were conducted and the results were collected in industry specific production planning analyses. Five process industries were analyzed to identify the product’s suitability to each industry sector and the most important product development areas. Based on the research the paper and the plastic film industries remain the most potential industry sectors at this point. To be successful in other industry sectors some product enhancements would be required, including capabilities to optimize multiple sequential and parallel production cycles, handle sequencing of complex finishing operations and to include master planning capabilities to support overall supply chain optimization. In product sales and marketing processes the key to success is to find and reach the people who are involved directly with the problems that the optimization tool can help to solve.

Railway Wagon Market Analysis and New Multi-Purpose Wagon Solution for Freight Transports - Finnish Manufacturing Perspective

Rautateillä käytettävät tavaravaunut ovat vanhenemassa hyvin nopeasti; tämä koskee niin Venäjää, Suomea, Ruotsia kuin laajemminkin Eurooppaa. Venäjällä ja Euroopassa on käytössä runsaasti vaunuja, jotka ovat jo ylittäneet niille suositeltavan käyttöiän. Silti niitä käytetään kuljetuksissa, kun näitä korvaavia uusia vaunuja ei ole tarpeeksi saatavilla. Uusimmat vaunut ovat yleensä vaunuja vuokraavien yritysten tai uusien rautatieoperaattorien hankkimia - tämä koskee erityisesti Venäjää, jossa vaunuvuokraus on noussut erittäin suosituksi vaihtoehdoksi. Ennusteissa kerrotaan vaunupulan kasvavan ainakin vuoteen 2010 saakka. Jos rautateiden suosio rahtikuljetusmuotona kasvaa, niin voimistuva vaunukysyntä jatkuu huomattavan paljon pidemmän aikaa. Euroopan ja Venäjän vaunukannan tilanne näkyy myös sitä palvelevan konepajateollisuuden ongelmina - yleisesti ottaen alan eurooppalaiset yritykset ovat heikosti kannattavia ja niiden liikevaihto ei juuri kasva, venäläiset ja ukrainalaiset yritykset ovat olleet samassa tilanteessa, joskin aivan viime vuosina tilanne on osassa kääntynyt paremmaksi. Kun näiden maanosien yritysten liikevaihtoa, voittoa ja omistaja-arvoa verrataan yhdysvaltalaisiin kilpailijoihin, huomataan että jälkimmäisten suoriutuminen on huomattavan paljon parempaa, ja näillä yrityksillä on myös kyky maksaa osinkoja omistajilleen. Tutkimuksen tarkoituksena oli kehittää uuden tyyppinen kuljetusvaunu Suomen, Venäjän sekä mahdollisesti myös Kiinan väliseen liikenteeseen. Vaunutyypin tarkoituksena olisi kyetä toimimaan monikäyttöisenä, niin raaka-aineiden kuin konttienkin kuljetuksessa, tasapainottaen kuljetusmuotojen aiheuttamaa kuljetuspaino-ongelmaa. Kehitystyön pohjana käytimme yli 1000 venäläisen vaunutyypin tietokantaa, josta valitsimme Data Envelopment Analysis -menetelmällä soveliaimmat vaunut kontinkuljetukseen (lähemmin tarkastelimme n. 40 vaunutyyppiä), jättäen mahdollisimman vähän tyhjää tilaa junaan, mutta silti kyeten kantamaan valitun konttilastin. Kun kantokykyongelmia venäläisissä vaunuissa ei useinkaan ole, on vertailu tehtävissä tavarajunan pituuden ja kokonaispainon perusteella. Simuloituamme yhdistettyihin kuljetuksiin soveliasta vaunutyyppiä käytännössä löytyvässä kuljetusverkostossa (esim. raakapuuta Suomeen tai Kiinaan ja kontteja takaisin Venäjän suuntaan), huomasimme lyhemmän vaunupituuden sisältävän kustannusetua, erityisesti raakaainekuljetuksissa, mutta myös rajanylityspaikkojen mahdollisesti vähentyessä. Lyhempi vaunutyyppi on myös joustavampi erilaisten konttipituuksien suhteen (40 jalan kontin käyttö on yleistynyt viime vuosina). Työn lopuksi ehdotamme uuden vaunutyypin tuotantotavaksi verkostomaista lähestymistapaa, jossa osa vaunusta tehtäisiin Suomessa ja osa Venäjällä ja/tai Ukrainassa. Vaunutyypin tulisi olla rekisteröity Venäjälle, sillä silloin sitä voi käyttää Suomen ja Venäjän, kuten myös soveltuvin osin Venäjän ja Kiinan välisessä liikenteessä.

Optimization of short term power trading between Russia, Finland and Baltic countries

Russian and Baltic electricity markets are in the process of reformation and development on the way for competitive and transparent market. Nordic market also undergoes some changes on the way to market integration. Old structure and practices have been expired whereas new laws and rules come into force. The master thesis describes structure and functioning of wholesale electricity markets, cross-border connections between different countries. Additionally methods of cross-border trading using different methods of capacity allocation are disclosed. The main goal of present thesis is to study current situation at different electricity markets and observe changes coming into force as well as the capacity and electricity balances forecast in order to optimize short term power trading between countries and estimate the possible profit for the company.

Essays on pricing of risk and international linkage of Russian stock market

Last two decades have seen a rapid change in the global economic and financial situation; the economic conditions in many small and large underdeveloped countries started to improve and they became recognized as emerging markets. This led to growth in the amounts of global investments in these countries, partly spurred by expectations of higher returns, favorable risk-return opportunities, and better diversification alternatives to global investors. This process, however, has not been without problems and it has emphasized the need for more information on these markets. In particular, the liberalization of financial markets around the world, globalization of trade and companies, recent formation of economic and regional blocks, and the rapid development of underdeveloped countries during the last two decades have brought a major challenge to the financial world and researchers alike. This doctoral dissertation studies one of the largest emerging markets, namely Russia. The motivation why the Russian equity market is worth investigating includes, among other factors, its sheer size, rapid and robust economic growth since the turn of the millennium, future prospect for international investors, and a number of important major financial reforms implemented since the early 1990s. Another interesting feature of the Russian economy, which gives motivation to study Russian market, is Russia’s 1998 financial crisis, considered as one of the worst crisis in recent times, affecting both developed and developing economies. Therefore, special attention has been paid to Russia’s 1998 financial crisis throughout this dissertation. This thesis covers the period from the birth of the modern Russian financial markets to the present day, Special attention is given to the international linkage and the 1998 financial crisis. This study first identifies the risks associated with Russian market and then deals with their pricing issues. Finally some insights about portfolio construction within Russian market are presented. The first research paper of this dissertation considers the linkage of the Russian equity market to the world equity market by examining the international transmission of the Russia’s 1998 financial crisis utilizing the GARCH-BEKK model proposed by Engle and Kroner. Empirical results shows evidence of direct linkage between the Russian equity market and the world market both in regards of returns and volatility. However, the weakness of the linkage suggests that the Russian equity market was only partially integrated into the world market, even though the contagion can be clearly seen during the time of the crisis period. The second and the third paper, co-authored with Mika Vaihekoski, investigate whether global, local and currency risks are priced in the Russian stock market from a US investors’ point of view. Furthermore, the dynamics of these sources of risk are studied, i.e., whether the prices of the global and local risk factors are constant or time-varying over time. We utilize the multivariate GARCH-M framework of De Santis and Gérard (1998). Similar to them we find price of global market risk to be time-varying. Currency risk also found to be priced and highly time varying in the Russian market. Moreover, our results suggest that the Russian market is partially segmented and local risk is also priced in the market. The model also implies that the biggest impact on the US market risk premium is coming from the world risk component whereas the Russian risk premium is on average caused mostly by the local and currency components. The purpose of the fourth paper is to look at the relationship between the stock and the bond market of Russia. The objective is to examine whether the correlations between two classes of assets are time varying by using multivariate conditional volatility models. The Constant Conditional Correlation model by Bollerslev (1990), the Dynamic Conditional Correlation model by Engle (2002), and an asymmetric version of the Dynamic Conditional Correlation model by Cappiello et al. (2006) are used in the analysis. The empirical results do not support the assumption of constant conditional correlation and there was clear evidence of time varying correlations between the Russian stocks and bond market and both asset markets exhibit positive asymmetries. The implications of the results in this dissertation are useful for both companies and international investors who are interested in investing in Russia. Our results give useful insights to those involved in minimising or managing financial risk exposures, such as, portfolio managers, international investors, risk analysts and financial researchers. When portfolio managers aim to optimize the risk-return relationship, the results indicate that at least in the case of Russia, one should account for the local market as well as currency risk when calculating the key inputs for the optimization. In addition, the pricing of exchange rate risk implies that exchange rate exposure is partly non-diversifiable and investors are compensated for bearing the risk. Likewise, international transmission of stock market volatility can profoundly influence corporate capital budgeting decisions, investors’ investment decisions, and other business cycle variables. Finally, the weak integration of the Russian market and low correlations between Russian stock and bond market offers good opportunities to the international investors to diversify their portfolios.

Regime Switching Models for Electricity Time Series that Capture Fat Tailed Distributions

In the power market, electricity prices play an important role at the economic level. The behavior of a price trend usually known as a structural break may change over time in terms of its mean value, its volatility, or it may change for a period of time before reverting back to its original behavior or switching to another style of behavior, and the latter is typically termed a regime shift or regime switch. Our task in this thesis is to develop an electricity price time series model that captures fat tailed distributions which can explain this behavior and analyze it for better understanding. For NordPool data used, the obtained Markov Regime-Switching model operates on two regimes: regular and non-regular. Three criteria have been considered price difference criterion, capacity/flow difference criterion and spikes in Finland criterion. The suitability of GARCH modeling to simulate multi-regime modeling is also studied.

Complexity Optimization in Product Development with Modularization

A company’s competence to manage its product portfolio complexity is becoming critically important in the rapidly changing business environment. The continuous evolvement of customer needs, the competitive market environment and internal product development lead to increasing complexity in product portfolios. The companies that manage the complexity in product development are more profitable in the long run. The complexity derives from product development and management processes where the new product variant development is not managed efficiently. Complexity is managed with modularization which is a method that divides the product structure into modules. In modularization, it is essential to take into account the trade-off between the perceived customer value and the module or component commonality across the products. Another goal is to enable the product configuration to be more flexible. The benefits are achieved through optimizing complexity in module offering and deriving the new product variants more flexibly and accurately. The developed modularization process includes the process steps for preparation, mapping the current situation, the creation of a modular strategy and implementing the strategy. Also the organization and support systems have to be adapted to follow-up targets and to execute modularization in practice.

Optimization as a method of search engine marketing

This study is dedicated to search engine marketing (SEM). It aims for developing a business model of SEM firms and to provide explicit research of trustworthy practices of virtual marketing companies. Optimization is a general term that represents a variety of techniques and methods of the web pages promotion. The research addresses optimization as a business activity, and it explains its role for the online marketing. Additionally, it highlights issues of unethical techniques utilization by marketers which created relatively negative attitude to them on the Internet environment. Literature insight combines in the one place both technical and economical scientific findings in order to highlight technological and business attributes incorporated in SEM activities. Empirical data regarding search marketers was collected via e-mail questionnaires. 4 representatives of SEM companies were engaged in this study to accomplish the business model design. Additionally, the fifth respondent was a representative of the search engine portal, who provided insight on relations between search engines and marketers. Obtained information of the respondents was processed qualitatively. Movement of commercial organizations to the online market increases demand on promotional programs. SEM is the largest part of online marketing, and it is a prerogative of search engines portals. However, skilled users, or marketers, are able to implement long-term marketing programs by utilizing web page optimization techniques, key word consultancy or content optimization to increase web site visibility to search engines and, therefore, user’s attention to the customer pages. SEM firms are related to small knowledge-intensive businesses. On the basis of data analysis the business model was constructed. The SEM model includes generalized constructs, although they represent a wider amount of operational aspects. Constructing blocks of the model includes fundamental parts of SEM commercial activity: value creation, customer, infrastructure and financial segments. Also, approaches were provided on company’s differentiation and competitive advantages evaluation. It is assumed that search marketers should apply further attempts to differentiate own business out of the large number of similar service providing companies. Findings indicate that SEM companies are interested in the increasing their trustworthiness and the reputation building. Future of the search marketing is directly depending on search engines development.

The Evolution of Securities Lending and Risk Mitigation: A Finnish Market Case Study

Although securities lending is an important function of the financial markets, it has not received that much academic attention. This study examines the evolution of European securities lending and risk management with an emphasis on the development of collateral management, the function responsible for reducing credit risk. The effects of the recent financial instabilities are also considered. The evolution of the Finnish securities lending market is examined in more detail through a case-study. This study can be classified as a constructive qualitative case study. The initial practical knowledge comes from the author's own experience and additional insight and theoretical background is acquired through a literature review. The case study is based on research, semi-structured interviews and a brief analysis of numerical data. The main observation of this study was that securities lending is now recognized as more of an investment management discipline than an operational support function. The recent financial instabilities have resulted in an increased focus on risk and transparency. In securities lending this is directly reflected in collateral management guidelines and procedures. Collateral management has become increasingly technologically developed and automated. Collateral optimization initiatives have been started to make the process more efficient, liquid, and cost effective. Although securities lending is generally an OTC-market with no standard market place, centralized exchange-like models have been introduced. Finnish securities lending has now shifted towards the more common global OTC model. Although the Finnish securities lending industry has developed, and the main laws governing it (tax legislation) have changed, there is still need for development. There are still not many Finnish participants involved and due to legal issues most securities loans are collateralized with cash and not securities (e.g. government bonds).

Methodology for wind turbine blade geometry optimization

Nowadays, the upwind three bladed horizontal axis wind turbine is the leading player on the market. It has been found to be the best industrial compromise in the range of different turbine constructions. The current wind industry innovation is conducted in the development of individual turbine components. The blade constitutes 20-25% of the overall turbine budget. Its optimal operation in particular local economic and wind conditions is worth investigating. The blade geometry, namely the chord, twist and airfoil type distributions along the span, responds to the output measures of the blade performance. Therefore, the optimal wind blade geometry can improve the overall turbine performance. The objectives of the dissertation are focused on the development of a methodology and specific tool for the investigation of possible existing wind blade geometry adjustments. The novelty of the methodology presented in the thesis is the multiobjective perspective on wind blade geometry optimization, particularly taking simultaneously into account the local wind conditions and the issue of aerodynamic noise emissions. The presented optimization objective approach has not been investigated previously for the implementation in wind blade design. The possibilities to use different theories for the analysis and search procedures are investigated and sufficient arguments derived for the usage of proposed theories. The tool is used for the test optimization of a particular wind turbine blade. The sensitivity analysis shows the dependence of the outputs on the provided inputs, as well as its relative and absolute divergences and instabilities. The pros and cons of the proposed technique are seen from the practical implementation, which is documented in the results, analysis and conclusion sections.

Price spike forecasting in a competitive day-ahead energy market

Electricity price forecasting has become an important area of research in the aftermath of the worldwide deregulation of the power industry that launched competitive electricity markets now embracing all market participants including generation and retail companies, transmission network providers, and market managers. Based on the needs of the market, a variety of approaches forecasting day-ahead electricity prices have been proposed over the last decades. However, most of the existing approaches are reasonably effective for normal range prices but disregard price spike events, which are caused by a number of complex factors and occur during periods of market stress. In the early research, price spikes were truncated before application of the forecasting model to reduce the influence of such observations on the estimation of the model parameters; otherwise, a very large forecast error would be generated on price spike occasions. Electricity price spikes, however, are significant for energy market participants to stay competitive in a market. Accurate price spike forecasting is important for generation companies to strategically bid into the market and to optimally manage their assets; for retailer companies, since they cannot pass the spikes onto final customers, and finally, for market managers to provide better management and planning for the energy market. This doctoral thesis aims at deriving a methodology able to accurately predict not only the day-ahead electricity prices within the normal range but also the price spikes. The Finnish day-ahead energy market of Nord Pool Spot is selected as the case market, and its structure is studied in detail. It is almost universally agreed in the forecasting literature that no single method is best in every situation. Since the real-world problems are often complex in nature, no single model is able to capture different patterns equally well. Therefore, a hybrid methodology that enhances the modeling capabilities appears to be a possibly productive strategy for practical use when electricity prices are predicted. The price forecasting methodology is proposed through a hybrid model applied to the price forecasting in the Finnish day-ahead energy market. The iterative search procedure employed within the methodology is developed to tune the model parameters and select the optimal input set of the explanatory variables. The numerical studies show that the proposed methodology has more accurate behavior than all other examined methods most recently applied to case studies of energy markets in different countries. The obtained results can be considered as providing extensive and useful information for participants of the day-ahead energy market, who have limited and uncertain information for price prediction to set up an optimal short-term operation portfolio. Although the focus of this work is primarily on the Finnish price area of Nord Pool Spot, given the result of this work, it is very likely that the same methodology will give good results when forecasting the prices on energy markets of other countries.

Towards sustainable Iron- and steelmaking with economic optimization

The iron and steelmaking industry is among the major contributors to the anthropogenic emissions of carbon dioxide in the world. The rising levels of CO2 in the atmosphere and the global concern about the greenhouse effect and climate change have brought about considerable investigations on how to reduce the energy intensity and CO2 emissions of this industrial sector. In this thesis the problem is tackled by mathematical modeling and optimization using three different approaches. The possibility to use biomass in the integrated steel plant, particularly as an auxiliary reductant in the blast furnace, is investigated. By pre-processing the biomass its heating value and carbon content can be increased at the same time as the oxygen content is decreased. As the compression strength of the preprocessed biomass is lower than that of coke, it is not suitable for replacing a major part of the coke in the blast furnace burden. Therefore the biomass is assumed to be injected at the tuyere level of the blast furnace. Carbon capture and storage is, nowadays, mostly associated with power plants but it can also be used to reduce the CO2 emissions of an integrated steel plant. In the case of a blast furnace, the effect of CCS can be further increased by recycling the carbon dioxide stripped top gas back into the process. However, this affects the economy of the integrated steel plant, as the amount of top gases available, e.g., for power and heat production is decreased. High quality raw materials are a prerequisite for smooth blast furnace operation. High quality coal is especially needed to produce coke with sufficient properties to ensure proper gas permeability and smooth burden descent. Lower quality coals as well as natural gas, which some countries have in great volumes, can be utilized with various direct and smelting reduction processes. The DRI produced with a direct reduction process can be utilized as a feed material for blast furnace, basic oxygen furnace or electric arc furnace. The liquid hot metal from a smelting reduction process can in turn be used in basic oxygen furnace or electric arc furnace. The unit sizes and investment costs of an alternative ironmaking process are also lower than those of a blast furnace. In this study, the economy of an integrated steel plant is investigated by simulation and optimization. The studied system consists of linearly described unit processes from coke plant to steel making units, with a more detailed thermodynamical model of the blast furnace. The results from the blast furnace operation with biomass injection revealed the importance of proper pre-processing of the raw biomass as the composition of the biomass as well as the heating value and the yield are all affected by the pyrolysis temperature. As for recycling of CO2 stripped blast furnace top gas, substantial reductions in the emission rates are achieved if the stripped CO2 can be stored. However, the optimal recycling degree together with other operation conditions is heavily dependent on the cost structure of CO2 emissions and stripping/storage. The economical feasibility related to the use of DRI in the blast furnace depends on the price ratio between the DRI pellets and the BF pellets. The high amount of energy needed in the rotary hearth furnace to reduce the iron ore leads to increased CO2 emissions.

Simulating the dynamics of silver market using computational market dynamics

Traditional econometric approaches in modeling the dynamics of equity and commodity markets, have, made great progress in the past decades. However, they assume rationality among the economic agents and and do not capture the dynamics that produce extreme events (black swans), due to deviation from the rationality assumption. The purpose of this study is to simulate the dynamics of silver markets by using the novel computational market dynamics approach. To this end, the daily data from the period of 1st March 2000 to 1st March 2013 of closing prices of spot silver prices has been simulated with the Jabłonska-Capasso-Morale(JCM) model. The Maximum Likelihood approach has been employed to calibrate the acquired data with JCM. Statistical analysis of the simulated series with respect to the actual one has been conducted to evaluate model performance. The model captures the animal spirits dynamics present in the data under evaluation well.