The improvement of enclosure protection class of power electronics device

Tässä diplomityössä tutkittiin vaihtoehtoja tehoelektroniikkalaitteiden kotelointiluokan kehittämiseksi. Haasteena paremman suojauksen suunnittelussa on laitteiden tuottama suuri määrä lämpöä, joka vaatii tehokkaan jäähdytyksen. Työn tuloksena saatu prototyyppi IP33 luokkaa varten täyttää standardissa SFS-EN 60529+A1 asetetut vaatimukset kyseiselle kotelointiluokalle. Rakenteessa ja valmistettavuudessa havaittiin muutama ongelma, jotka ovat korjattavissa pienillä muutoksilla. Korkeampia suojausluokkia varten testattiin IP54-luokiteltujen filtterituulettimien vaikutusta laitteen jäähdytykseen. Testien perusteella jäähdytysteho on riittävä ja filtterituulettimet todettiin toimivaksi ratkaisuksi korkeammille suojausluokille. Työn perusteella voidaan todeta, että nykyiset laitteet voidaan muokata vastaamaan IP33 luokan vaatimuksia kohtuullisen pienillä muutoksilla. Tätä korkeammat suojausluokat vaatisivat niin suuria muutoksia designiin, että todennäköisesti täysin uuden laitteen suunnittelu olis kannattavin vaihtoehto.

Lean Six Sigma in a Manufacturing Lead Time Improvement Project

The objective of this research is to demonstrate the use of Lean Six Sigma methodology in a manufacturing lead time improvement project. Moreover, the goal is to develop working solutions for the target company to improve its manufacturing lead time. The theoretical background is achieved through exploring the literature of Six Sigma, Lean and Lean Six Sigma. The development will be done in collaboration with the related stakeholders, by following the Lean Six Sigma improvement process DMAIC and by analyzing the process data from the target company. The focus of this research is in demonstrating how to use Lean Six Sigma improvement process DMAIC in practice, rather than in comparing Lean Six Sigma to other improvement methodologies. In order to validate the manufacturing system’s current state, improvement potential and solutions, statistical tools such as linear regression analysis were used. This ensured that all the decisions were as heavily based on actual data as possible. As a result of this research, a set of solutions were developed and implemented in the target company. These solutions included batch size reduction, bottleneck shift, first-in first-out queuing and shifting a data entry task from production planners to line workers. With the use of these solutions, the target company was able to reduce its manufacturing lead time by over one third.

Linking supplier delivery risk to outbound delivery service performance improvement

Customer satisfaction should be the main focus for all of the parts of the business. Usually supply chain behind the business is in a key role when this focus is pursued especially in repair service business. When focusing on the materials that are needed to make repairs to equipment under service contracts, the time aspect of quality is critical. Do late deliveries from supplier have an effect on the service performance of repairs when distribution center of a centralized purchasing unit is acting as a buffer between suppliers and repair service business? And if so, how should the improvement efforts be prioritized? These are the two main questions that this thesis focuses on. Correlation and linear regression was tested between service levels of supplier and distribution center. Percentage of on-time deliveries were compared to outbound delivery service level. It was found that there is statistically significant correlation between inbound and outbound operations success. The other main question of the thesis, improvement prioritization, was answered by creating material availability based supplier classification and additional to that, by developing the decision process for the analysis of most critical suppliers. This was built on a basis of previous supplier and material classification methods.

Accuracy improvement of a demand forecasting model

This research concerns different statistical methods that assist to increase the demand forecasting accuracy of company X’s forecasting model. Current forecasting process was analyzed in details. As a result, graphical scheme of logical algorithm was developed. Based on the analysis of the algorithm and forecasting errors, all the potential directions for model future improvements in context of its accuracy were gathered into the complete list. Three improvement directions were chosen for further practical research, on their basis, three test models were created and verified. Novelty of this work lies in the methodological approach of the original analysis of the model, which identified its critical points, as well as the uniqueness of the developed test models. Results of the study formed the basis of the grant of the Government of St. Petersburg.

Att använda Choice Reaction Time (CRT) paradigmet för att differentiera mellan sexualförbrytare med barnoffer, sexualförbrytare med vuxna offer, förbrytare skyldiga till andra brott än sexualbrott, samt kontroller från normalpopulationen

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Quantitative refinement of reaction-based biomodels

In the field of molecular biology, scientists adopted for decades a reductionist perspective in their inquiries, being predominantly concerned with the intricate mechanistic details of subcellular regulatory systems. However, integrative thinking was still applied at a smaller scale in molecular biology to understand the underlying processes of cellular behaviour for at least half a century. It was not until the genomic revolution at the end of the previous century that we required model building to account for systemic properties of cellular activity. Our system-level understanding of cellular function is to this day hindered by drastic limitations in our capability of predicting cellular behaviour to reflect system dynamics and system structures. To this end, systems biology aims for a system-level understanding of functional intraand inter-cellular activity. Modern biology brings about a high volume of data, whose comprehension we cannot even aim for in the absence of computational support. Computational modelling, hence, bridges modern biology to computer science, enabling a number of assets, which prove to be invaluable in the analysis of complex biological systems, such as: a rigorous characterization of the system structure, simulation techniques, perturbations analysis, etc. Computational biomodels augmented in size considerably in the past years, major contributions being made towards the simulation and analysis of large-scale models, starting with signalling pathways and culminating with whole-cell models, tissue-level models, organ models and full-scale patient models. The simulation and analysis of models of such complexity very often requires, in fact, the integration of various sub-models, entwined at different levels of resolution and whose organization spans over several levels of hierarchy. This thesis revolves around the concept of quantitative model refinement in relation to the process of model building in computational systems biology. The thesis proposes a sound computational framework for the stepwise augmentation of a biomodel. One starts with an abstract, high-level representation of a biological phenomenon, which is materialised into an initial model that is validated against a set of existing data. Consequently, the model is refined to include more details regarding its species and/or reactions. The framework is employed in the development of two models, one for the heat shock response in eukaryotes and the second for the ErbB signalling pathway. The thesis spans over several formalisms used in computational systems biology, inherently quantitative: reaction-network models, rule-based models and Petri net models, as well as a recent formalism intrinsically qualitative: reaction systems. The choice of modelling formalism is, however, determined by the nature of the question the modeler aims to answer. Quantitative model refinement turns out to be not only essential in the model development cycle, but also beneficial for the compilation of large-scale models, whose development requires the integration of several sub-models across various levels of resolution and underlying formal representations.

Improving the fire retardancy of extruded/coextruded wood-plastic composites

The main objective of this thesis is to study the impact of different mineral fillers and fire retardants on the reaction-to-fire properties of extruded/coextruded wood-plastic composites (WPCs). The impact of additives on the flammability properties of WPCs is studied by cone calorimetry. The studied properties are ignition time, peak heat release rate, total heat release, total smoke production, and mass loss rate. The effects of mineral fillers and fire retardants were found to vary with the type of additive, the type of additive combinations, the amount of additives, as well as the production method of the WPCs. The study shows that talc can be used to improve the properties of extruded WPCs. Especially ignition time, peak heat release rate and mass loss rate were found to be improved significantly by talc. The most significant improvement in the fire retardancy of coextruded WPCs was achieved in combinations of natural graphite and melamine. Ignition time, peak heat release rate and total smoke production were improved essentially. High increase in smoke production was found in samples where the amount of ammonium polyphosphate was 10% or higher. Coextrusion as a structural modification was found as a promising way to improve the flammability properties of composite materials in a cost-effective way.

Bio and chemocatalysis for stereo and regioselective one-pot reaction applications

The development of cost efficient, selective and sustainable chemical processes for production of chiral building blocks is of great importance in synthetic and industrial organic chemistry. One way to reach these objectives is to carry out several reactions steps in one vessel at one time. Furthermore, when this kind of one-pot multi step reactions are catalyzed by heterogeneous chemo- and bio-catalysts, which can be separated from the reaction products by filtration, practical access to chiral small molecules for further utilization can be obtained. The initial reactions studied in this thesis are the two step dynamic kinetic resolution of rac-2-hydroxy-1-indanone and the regioselective hydrogenation of 1,2-indanedione. These reactions are then combined in a new heterogeneously catalyzed one-pot reaction sequence enabling simple recovery of the catalysts by filtration, facilitating simple reaction product isolation. Conclusively, the readily available 1,2-indanedione is by the presented one-pot sequence, utilizing heterogeneous enzyme and transition metal based catalysts, transferred with high regio- and stereoselectivity to a useful chiral vicinal hydroxyl ketone structure. Additional and complementary investigation of homogeneous half-sandwich ruthenium complexes for catalyzing the epimerization of chiral secondary alcohols of five natural products containing additional non-functionalized stereocenters was conducted. In principle, this kind of epimerization reactions of single stereocenters could be utilized for converting inexpensive starting materials, containing other stereogenic centers, into diastereomeric mixtures from which more valuable compounds can be isolated by traditional isolation techniques.

Implementation of Quantitative Reaction-based Model Refinement

Building a computational model for complex biological systems is an iterative process. It starts from an abstraction of the process and then incorporates more details regarding the specific biochemical reactions which results in the change of the model fit. Meanwhile, the model’s numerical properties such as its numerical fit and validation should be preserved. However, refitting the model after each refinement iteration is computationally expensive resource-wise. There is an alternative approach which ensures the model fit preservation without the need to refit the model after each refinement iteration. And this approach is known as quantitative model refinement. The aim of this thesis is to develop and implement a tool called ModelRef which does the quantitative model refinement automatically. It is both implemented as a stand-alone Java application and as one of Anduril framework components. ModelRef performs data refinement of a model and generates the results in two different well known formats (SBML and CPS formats). The development of this tool successfully reduces the time and resource needed and the errors generated as well by traditional reiteration of the whole model to perform the fitting procedure.

Computational models for and from biology : simple gene assembly and reaction systems

The advancement of science and technology makes it clear that no single perspective is any longer sufficient to describe the true nature of any phenomenon. That is why the interdisciplinary research is gaining more attention overtime. An excellent example of this type of research is natural computing which stands on the borderline between biology and computer science. The contribution of research done in natural computing is twofold: on one hand, it sheds light into how nature works and how it processes information and, on the other hand, it provides some guidelines on how to design bio-inspired technologies. The first direction in this thesis focuses on a nature-inspired process called gene assembly in ciliates. The second one studies reaction systems, as a modeling framework with its rationale built upon the biochemical interactions happening within a cell. The process of gene assembly in ciliates has attracted a lot of attention as a research topic in the past 15 years. Two main modelling frameworks have been initially proposed in the end of 1990s to capture ciliates’ gene assembly process, namely the intermolecular model and the intramolecular model. They were followed by other model proposals such as templatebased assembly and DNA rearrangement pathways recombination models. In this thesis we are interested in a variation of the intramolecular model called simple gene assembly model, which focuses on the simplest possible folds in the assembly process. We propose a new framework called directed overlap-inclusion (DOI) graphs to overcome the limitations that previously introduced models faced in capturing all the combinatorial details of the simple gene assembly process. We investigate a number of combinatorial properties of these graphs, including a necessary property in terms of forbidden induced subgraphs. We also introduce DOI graph-based rewriting rules that capture all the operations of the simple gene assembly model and prove that they are equivalent to the string-based formalization of the model. Reaction systems (RS) is another nature-inspired modeling framework that is studied in this thesis. Reaction systems’ rationale is based upon two main regulation mechanisms, facilitation and inhibition, which control the interactions between biochemical reactions. Reaction systems is a complementary modeling framework to traditional quantitative frameworks, focusing on explicit cause-effect relationships between reactions. The explicit formulation of facilitation and inhibition mechanisms behind reactions, as well as the focus on interactions between reactions (rather than dynamics of concentrations) makes their applicability potentially wide and useful beyond biological case studies. In this thesis, we construct a reaction system model corresponding to the heat shock response mechanism based on a novel concept of dominance graph that captures the competition on resources in the ODE model. We also introduce for RS various concepts inspired by biology, e.g., mass conservation, steady state, periodicity, etc., to do model checking of the reaction systems based models. We prove that the complexity of the decision problems related to these properties varies from P to NP- and coNP-complete to PSPACE-complete. We further focus on the mass conservation relation in an RS and introduce the conservation dependency graph to capture the relation between the species and also propose an algorithm to list the conserved sets of a given reaction system.

Performance improvement in mediterranean operations using risk management analysis : Case study of Containerships Group Ltd

Emerging markets of Northern Africa and Turkey provide growth opportunities for logistics service companies in the middle of low growth environment of European Union. The purpose of this research is to explore and analyze the risk factors in container shipping industry and third party logistics (3PL) services. The research empirically examined the risk factors, which are related within the interaction between these two parties in emerging markets of Mediterranean area. The previous studies have provided a valuable insight into the operational risks faced by container shipping industries. However, most of these studies have focused on one or several operational risk factors from a single point of view, and no studies have inclusively examined the possible operational risks faced in the container shipping industry from dual perspective of 3PL provider and its customers. A questionnaire has been deployed to collect related data; and the impacts of the risks were then be assessed and ranked using the method of risk mapping. Respondents were located in Turkey, Algeria, Tunisia, and Libya. Research presents the most important risk factors identified, and compares them between 3PL provider and its customers. The research also provide some risk mitigation strategies for the key risk factors, and tried to figure out a common risk picture, which guides the managers in both sides to have a better decisions and as a result, improve the performance of the container shipping operations. Challenge during project execution time was that customers identified vast amount of more risks than what was the case with logistics service operator.

Improvement of Energy Efficiency in a Gold Mining Industry: Case Study of a Russian Gold Mining Company

The issue of energy efficiency is attracting more and more attention of academia, business and policy makers worldwide due to increasing environmental concerns, depletion of non-renewable energy resources and unstable energy prices. The significant importance of energy efficiency within gold mining industry is justified by considerable energy intensity of this industry as well as by the high share of energy costs in the total operational costs. In the context of increasing industrial energy consumption energy efficiency improvement may provide significant energy savings and reduction of CO2 emission that is highly important in order to contribute to the global goal of sustainability. The purpose of this research is to identify the ways of energy efficiency improvement relevant for a gold mining company. The study implements single holistic case study research strategy focused on a Russian gold mining company. The research involves comprehensive analysis of company’s energy performance including analysis of energy efficiency and energy management practices. This study provides following theoretical and managerial contributions. Firstly, it proposes a methodology for comparative analysis of energy performance of Russian and foreign gold mining companies. Secondly, this study provides comprehensive analysis of main energy efficiency challenges relevant for a Russian gold mining company. Finally, in order to overcome identified challenges this research conceives a guidance for a gold mining company for implementation of energy management system based on the ISO standard.

Mass transfer and reaction kinetics in single droplet systems

As reactive extraction grown more and more popular in a variety of technological applications, optimizing its performance becomes more and more important. The process of complex formation is affected by a great number of both physical and chemical properties of all the components involved, and sometimes their interference with one another makes improving the effectiveness of such processes very difficult. In this Master’s Theses, the processes of complex formation between the aqueous phase - represented by copper sulfate water solution, and organic phase – represented by Acorga M5640 solvent extractor, were studied in order to establish the effect these components have on reactive extraction performance and to determine which step is bottlenecking the process the most.