932 resultados para Product Launch. Industrial Markets. Segmentation. Conjoint Analysis. Technology Push


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The objective of this paper is to examine whether informal labor markets affect the flows of Foreign Direct Investment (FDI), and also whether this effect is similar in developed and developing countries. With this aim, different public data sources, such as the World Bank (WB), and the United Nations Conference on Trade and Development (UNCTAD) are used, and panel econometric models are estimated for a sample of 65 countries over a 14 year period (1996-2009). In addition, this paper uses a dynamic model as an extension of the analysis to establish whether such an effect exists and what its indicators and significance may be.

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Recent years have produced great advances in the instrumentation technology. The amount of available data has been increasing due to the simplicity, speed and accuracy of current spectroscopic instruments. Most of these data are, however, meaningless without a proper analysis. This has been one of the reasons for the overgrowing success of multivariate handling of such data. Industrial data is commonly not designed data; in other words, there is no exact experimental design, but rather the data have been collected as a routine procedure during an industrial process. This makes certain demands on the multivariate modeling, as the selection of samples and variables can have an enormous effect. Common approaches in the modeling of industrial data are PCA (principal component analysis) and PLS (projection to latent structures or partial least squares) but there are also other methods that should be considered. The more advanced methods include multi block modeling and nonlinear modeling. In this thesis it is shown that the results of data analysis vary according to the modeling approach used, thus making the selection of the modeling approach dependent on the purpose of the model. If the model is intended to provide accurate predictions, the approach should be different than in the case where the purpose of modeling is mostly to obtain information about the variables and the process. For industrial applicability it is essential that the methods are robust and sufficiently simple to apply. In this way the methods and the results can be compared and an approach selected that is suitable for the intended purpose. Differences in data analysis methods are compared with data from different fields of industry in this thesis. In the first two papers, the multi block method is considered for data originating from the oil and fertilizer industries. The results are compared to those from PLS and priority PLS. The third paper considers applicability of multivariate models to process control for a reactive crystallization process. In the fourth paper, nonlinear modeling is examined with a data set from the oil industry. The response has a nonlinear relation to the descriptor matrix, and the results are compared between linear modeling, polynomial PLS and nonlinear modeling using nonlinear score vectors.

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The uncertainty of any analytical determination depends on analysis and sampling. Uncertainty arising from sampling is usually not controlled and methods for its evaluation are still little known. Pierre Gy’s sampling theory is currently the most complete theory about samplingwhich also takes the design of the sampling equipment into account. Guides dealing with the practical issues of sampling also exist, published by international organizations such as EURACHEM, IUPAC (International Union of Pure and Applied Chemistry) and ISO (International Organization for Standardization). In this work Gy’s sampling theory was applied to several cases, including the analysis of chromite concentration estimated on SEM (Scanning Electron Microscope) images and estimation of the total uncertainty of a drug dissolution procedure. The results clearly show that Gy’s sampling theory can be utilized in both of the above-mentioned cases and that the uncertainties achieved are reliable. Variographic experiments introduced in Gy’s sampling theory are beneficially applied in analyzing the uncertainty of auto-correlated data sets such as industrial process data and environmental discharges. The periodic behaviour of these kinds of processes can be observed by variographic analysis as well as with fast Fourier transformation and auto-correlation functions. With variographic analysis, the uncertainties are estimated as a function of the sampling interval. This is advantageous when environmental data or process data are analyzed as it can be easily estimated how the sampling interval is affecting the overall uncertainty. If the sampling frequency is too high, unnecessary resources will be used. On the other hand, if a frequency is too low, the uncertainty of the determination may be unacceptably high. Variographic methods can also be utilized to estimate the uncertainty of spectral data produced by modern instruments. Since spectral data are multivariate, methods such as Principal Component Analysis (PCA) are needed when the data are analyzed. Optimization of a sampling plan increases the reliability of the analytical process which might at the end have beneficial effects on the economics of chemical analysis,

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Raw measurement data does not always immediately convey useful information, but applying mathematical statistical analysis tools into measurement data can improve the situation. Data analysis can offer benefits like acquiring meaningful insight from the dataset, basing critical decisions on the findings, and ruling out human bias through proper statistical treatment. In this thesis we analyze data from an industrial mineral processing plant with the aim of studying the possibility of forecasting the quality of the final product, given by one variable, with a model based on the other variables. For the study mathematical tools like Qlucore Omics Explorer (QOE) and Sparse Bayesian regression (SB) are used. Later on, linear regression is used to build a model based on a subset of variables that seem to have most significant weights in the SB model. The results obtained from QOE show that the variable representing the desired final product does not correlate with other variables. For SB and linear regression, the results show that both SB and linear regression models built on 1-day averaged data seriously underestimate the variance of true data, whereas the two models built on 1-month averaged data are reliable and able to explain a larger proportion of variability in the available data, making them suitable for prediction purposes. However, it is concluded that no single model can fit well the whole available dataset and therefore, it is proposed for future work to make piecewise non linear regression models if the same available dataset is used, or the plant to provide another dataset that should be collected in a more systematic fashion than the present data for further analysis.

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Demand forecasting is one of the fundamental managerial tasks. Most companies do not know their future demands, so they have to make plans based on demand forecasts. The literature offers many methods and approaches for producing forecasts. When selecting the forecasting approach, companies need to estimate the benefits provided by particular methods, as well as the resources that applying the methods call for. Former literature points out that even though many forecasting methods are available, selecting a suitable approach and implementing and managing it is a complex cross-functional matter. However, research that focuses on the managerial side of forecasting is relatively rare. This thesis explores the managerial problems that are involved when demand forecasting methods are applied in a context where a company produces products for other manufacturing companies. Industrial companies have some characteristics that differ from consumer companies, e.g. typically a lower number of customers and closer relationships with customers than in consumer companies. The research questions of this thesis are: 1. What kind of challenges are there in organizing an adequate forecasting process in the industrial context? 2. What kind of tools of analysis can be utilized to support the improvement of the forecasting process? The main methodological approach in this study is design science, where the main objective is to develop tentative solutions to real-life problems. The research data has been collected from two organizations. Managerial problems in organizing demand forecasting can be found in four interlinked areas: 1. defining the operational environment for forecasting, 2. defining the forecasting methods, 3. defining the organizational responsibilities, and 4. defining the forecasting performance measurement process. In all these areas, examples of managerial problems are described, and approaches for mitigating these problems are outlined.

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Tämän diplomityön tavoite on kartoittaa maalien ja lakkojen valmistuksessa syntyvien sivuvirtojen hyötykäyttöä ja hyötykäyttöpotentiaalia nykyisellään. Työn tarkoitus on toimia esiselvityksenä pinnoiteteollisuuden sivuvirtojen hyötykäyttöön liittyvien liiketoimintamahdollisuuksien syvemmälle analyysille. Teollisuuden sivuvirtoihin liittyvää tietoa kerätään tilastoista ja olemassa olevista raporteista sekä haastattelemalla teollisuus- ja palveluyritysten edustajia sekä alan asiantuntijoita. Sivuvirtojen teknisten hyötykäyttömahdollisuuksien ja liiketoiminnallisten mahdollisuuksien tarkastelua varten järjestetään työpajoja asiantuntijoille Apila Group Oy Ab:n asiantuntijaverkostossa. Neljässä haastatellussa tuotantolaitoksissa syntyi vuonna 2008 yhteensä 6 662 tonnia kiinteää jätettä ja lietteitä. 68 % näistä sivuvirroista hyötykäytettiin energiana tai polttoaineen valmistuksessa. Materiaalina sivuvirtoja hyötykäytettiin 16 % sivuvirroista, pääasiassa pahvia, paperia, metalleja sekä tynnyreitä ja kontteja. Myös merkittävä osa liuottimista otettiin talteen uudelleenhyödyntämistä varten. Tässä diplomityössä hyötykäyttömahdollisuuksien tarkempaa tarkastelua varten valittiin tavanomaisiksi jätteiksi luokiteltuja maalisivuvirtoja, joita haastatelluissa tuotantolaitoksissa syntyi noin 1 500 tonnia. Maalisivuvirtojen tärkeimmät materiaaliominaisuudet liittyvät niiden sisältämiin täyte- ja sideaineisiin, jotka muodostavat merkittävän osan maalien koostumuksesta. Selvityksen mukaan nämä ominaisuudet voidaan ottaa hyötykäyttöön erilaisissa yhdistelmämateriaaleissa, esimerkiksi ekstruusiopuristetuissa tai ahtopuristetuissa muovikuitukomposiiteissa. Komposiittien raaka-aineena käytetään jo erilaisia sivuvirtoja ja lisäksi erilaisten komposiittien markkinoiden ennustetaan kasvavan. Tämä voi tarjota mahdollisuuksia uusille palvelu-, t&k- tai tuotteistusliiketoiminnoille. Kuivilla maalijätteillä on myös hyvä lämpöarvo, jolloin energiahyötykäytön ja palamisjäännöksen materiaalihyötykäytön yhdistäminen mm. keramiikka- tai sementtiteollisuudessa voi tarjota mahdollisuuksia uusille liiketoiminnoille.

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The objective of this thesis is to examine the market reaction around earnings announcements in Finnish stock markets. The aim is to find out whether the extreme market conditions during the financial crisis are reflected in stock prices as a stronger reaction. In addition to this, the purpose is to investigate how extensively Finnish listed companies report the country segmentation of revenues in their interim reports and whether the country risk is having a significant impact on perceived market reaction. The sample covers all companies listed in Helsinki stock exchange at 1.1.2010 and these companies’ interim reports from the first quarter of 2008 to last quarter of 2009. Final sample consists of 81 companies and 630 firm-quarter observations. The data sample has been divided in two parts, of which country risk sample contains 17 companies and 127 observations and comparison sample covers 66 companies and 503 observations. Research methodologies applied in this thesis are event study and cross-sectional regression analysis. Empirical results indicate that the market reaction occurs mainly during the announcement day and is slightly stronger in case of positive earnings surprises than the reactions observed in previous studies. In case of negative earnings surprises no significant differences can be observed. In case of country risk sample and negative earnings surprise market reaction is negative already in advance of the disclosure contrary to comparison sample. In case of positive surprise no differences can be observed. Country risk variable developed during this study seems to explain only minor part of the market reaction.

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This thesis is a preliminary study targeting South-Eastern Finland. The objective was to find out the financial and functional readiness and willingness of the small and medium-sized enterprises of the region to manufacture and sell distributed bioenergy solutions collaboratively as a business network. In this case these solutions mean small-scale (0.5 - 3 MW) woodchips-operated combined heat and power (CHP) plants. South-Eastern Finland has suffered from a decline in the recent years, mostly due to the problems of the traditionally strong industrial know-how area of the region, the paper industry. Local small and medium-sized companies will have to find new ways to survive the toughening competition. A group of 40 companies from suitable industries were selected and financial and comparative analysis was performed on them. Additionally 19 managing directors of the companies were selected for an interview to find out their views on networking, its requirements, advantages and the general interest in it. The studied companies were found to be generally in fairly good financial condition and in that sense, fit for networking activities. The interviews revealed that the companies were capable of producing all the needed elements for the plants in question, and the managers appeared to be very interested in and have a positive attitude towards such business networks. Thus it can be said that the small and medium-sized companies of the region are capable of and interested in manufacturing small bio-CHP plants as a production network.

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A coupled system simulator, based on analytical circuit equations and a finite element method (FEM) model of the motor has been developed and it is used to analyse a frequency-converterfed industrial squirrel-cage induction motor. Two control systems that emulate the behaviour of commercial direct-torque-controlled (DTC) and vector-controlled industrial frequency converters have been studied, implemented in the simulation software and verified by extensive laboratory tests. Numerous factors that affect the operation of a variable speed drive (VSD) and its energy efficiency have been investigated, and their significance in the simulation of the VSD results has been studied. The dependency of the frequency converter, induction motor and system losses on the switching frequency is investigated by simulations and measurements at different speeds for both the vector control and the DTC. Intensive laboratory measurements have been carried out to verify the simulation results.

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Cutin and suberin are structural and protective polymers of plant surfaces. The epidermal cells of the aerial parts of plants are covered with an extracellular cuticular layer, which consists of polyester cutin, highly resistant cutan, cuticular waxes and polysaccharides which link the layer to the epidermal cells. A similar protective layer is formed by a polyaromatic-polyaliphatic biopolymer suberin, which is present particularly in the cell walls of the phellem layer of periderm of the underground parts of plants (e.g. roots and tubers) and the bark of trees. In addition, suberization is also a major factor in wound healing and wound periderm formation regardless of the plants’ tissue. Knowledge of the composition and functions of cuticular and suberin polymers is important for understanding the physiological properties for the plants and for nutritional quality when these plants are consumed as foods. The aims of the practical work were to assess the chemical composition of cuticular polymers of several northern berries and seeds and suberin of two varieties of potatoes. Cutin and suberin were studied as isolated polymers and further after depolymerization as soluble monomers and solid residues. Chemical and enzymatic depolymerization techniques were compared and a new chemical depolymerization method was developed. Gas chromatographic analysis with mass spectrometric detection (GC-MS) was used to assess the monomer compositions. Polymer investigations were conducted with solid state carbon-13 cross polarization magic angle spinning nuclear magnetic resonance spectroscopy (13C CP-MAS NMR), Fourier transform infrared spectroscopy (FTIR) and microscopic analysis. Furthermore, the development of suberin over one year of post-harvest storage was investigated and the cuticular layers from berries grown in the North and South of Finland were compared. The results show that the amounts of isolated cuticular layers and cutin monomers, as well as monomeric compositions vary greatly between the berries. The monomer composition of seeds was found to differ from the corresponding berry peel monomers. The berry cutin monomers were composed mostly of long-chain aliphatic ω-hydroxy acids, with various mid-chain functionalities (double-bonds, epoxy, hydroxy and keto groups). Substituted α,ω-diacids predominated over ω-hydroxy acids in potato suberin monomers and slight differences were found between the varieties. The newly-developed closed tube chemical method was found to be suitable for cutin and suberin analysis and preferred over the solvent-consuming and laborious reflux method. Enzymatic hydrolysis with cutinase was less effective than chemical methanolysis and showed specificity towards α,ω-diacid bonds. According to 13C CP-MAS NMR and FTIR, the depolymerization residues contained significant amounts of aromatic structures, polysaccharides and possible cutan-type aliphatic moieties. Cultivation location seems to have effect on cuticular composition. The materials studied contained significant amounts of different types of biopolymers that could be utilized for several purposes with or without further processing. The importance of the so-called waste material from industrial processes of berries and potatoes as a source of either dietary fiber or specialty chemicals should be further investigated in detail. The evident impact of cuticular and suberin polymers, among other fiber components, on human health should be investigated in clinical trials. These by-product materials may be used as value-added fiber fractions in the food industry and as raw materials for specialty chemicals such as lubricants and emulsifiers, or as building blocks for novel polymers.

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The purpose of this thesis was to determine, what kind of service offering the case company should provide to its customers in the Australian market. For this, a model for analysing the competitive environment was developed. In the model, three players were considered: customers, competitors and the case company. Benchmarking was used in identifying competitors’ offerings currently available in the market. Experts inside the case company were consulted for determining the customer need. The competitors’ offerings were analysed on the basis of Pekkarinen et al.’s (2009) framework, dividing the offerings to services supporting the supplier’s product (SSP), supporting the client (SSC), supporting the client’s network (SSN), supporting mutual actions (SSM) and benefit and risk sharing elements. After this, they were compared to the competitive environment in order to identify areas where the case company can differentiate itself from its competitors in the Australian market. On the basis of the company’s key success factors, and the Finnish service concept currently in use, some additional offerings were suggested for the case company in order to further outperform its competitors in the market. Finally, on the basis of the suggested offerings and competitors’ offerings, a service concept was suggested for the case company to introduce in the Australian market.

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Electricity distribution network operation (NO) models are challenged as they are expected to continue to undergo changes during the coming decades in the fairly developed and regulated Nordic electricity market. Network asset managers are to adapt to competitive technoeconomical business models regarding the operation of increasingly intelligent distribution networks. Factors driving the changes for new business models within network operation include: increased investments in distributed automation (DA), regulative frameworks for annual profit limits and quality through outage cost, increasing end-customer demands, climatic changes and increasing use of data system tools, such as Distribution Management System (DMS). The doctoral thesis addresses the questions a) whether there exist conditions and qualifications for competitive markets within electricity distribution network operation and b) if so, identification of limitations and required business mechanisms. This doctoral thesis aims to provide an analytical business framework, primarily for electric utilities, for evaluation and development purposes of dedicated network operation models to meet future market dynamics within network operation. In the thesis, the generic build-up of a business model has been addressed through the use of the strategicbusiness hierarchy levels of mission, vision and strategy for definition of the strategic direction of the business followed by the planning, management and process execution levels of enterprisestrategy execution. Research questions within electricity distribution network operation are addressed at the specified hierarchy levels. The results of the research represent interdisciplinary findings in the areas of electrical engineering and production economics. The main scientific contributions include further development of the extended transaction cost economics (TCE) for government decisions within electricity networks and validation of the usability of the methodology for the electricity distribution industry. Moreover, DMS benefit evaluations in the thesis based on the outage cost calculations propose theoretical maximum benefits of DMS applications equalling roughly 25% of the annual outage costs and 10% of the respective operative costs in the case electric utility. Hence, the annual measurable theoretical benefits from the use of DMS applications are considerable. The theoretical results in the thesis are generally validated by surveys and questionnaires.

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The Switched Reluctance technology is probably best suited for industrial low-speed or zerospeed applications where the power can be small but the torque or the force in linear movement cases might be relatively high. Because of its simple structure the SR-motor is an interesting alternative for low power applications where pneumatic or hydraulic linear drives are to be avoided. This study analyses the basic parts of an LSR-motor which are the two mover poles and one stator pole and which form the “basic pole pair” in linear-movement transversal-flux switchedreluctance motors. The static properties of the basic pole pair are modelled and the basic design rules are derived. The models developed are validated with experiments. A one-sided one-polepair transversal-flux switched-reluctance-linear-motor prototype is demonstrated and its static properties are measured. The modelling of the static properties is performed with FEM-calculations. Two-dimensional models are accurate enough to model the static key features for the basic dimensioning of LSRmotors. Three-dimensional models must be used in order to get the most accurate calculation results of the static traction force production. The developed dimensioning and modelling methods, which could be systematically validated by laboratory measurements, are the most significant contributions of this thesis.

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The objective of this master’s thesis was to examine technology-based smart home devices and services. Topic was approached through basic theories, transaction cost theory and resource-based view in order to build basis for this thesis. Conceptual framework was discussed by means of networks, value networks and service systems which provide a useful framework for service development. The needs of the elderly living at home were discussed in order to find out which technology-based services could be used to satisfy the needs. Segmentation and need data collected previously during proactive home visits was exploited and additionally a survey targeted to experts and professionals of social and health care sector was done to verify the needs. Finally, the results of the survey were analyzed using quality function deployment method to figure out the most important and suitable service offerings for the elderly. As a conclusion of analysis, social media and monitoring services are the most useful technology-based services. However, traditional home services will still maintain their necessity too.

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Metal industries producing thick sections have shown increasing interest in the laser–arc hybrid welding process because of its clear advantages compared with the individual processes of autogenous laser welding and arc welding. One major benefit of laser–arc hybrid welding is that joints with larger gaps can be welded with acceptable quality compared to autogenous laser welding. The laser-arc hybrid welding process has good potential to extend the field of applications of laser technology, and provide significant improvements in weld quality and process efficiency in manufacturing applications. The objective of this research is to present a parameter set-up for laser–arc hybrid welding processes, introduce a methodical comparison of the chosen parameters, and discuss how this technology may be adopted in industrial applications. The research describes the principles, means and applications of different types of laser–arc hybrid welding processes. Conducted experiment processing variables are presented and compared using an analytical model which can also be used for predictive simulations. The main argument in this thesis is that profound understanding of the advanced technology of laser-arc hybrid welding will help improve the productivity of welding in industrial applications. Based on a review of the current knowledge base, important areas for further research are also identified. This thesis consists of two parts. The first part introduces the research topic and discusses laser–arc hybrid welding by characterizing its mechanism and most important variables. The second part comprises four research papers elaborating on the performance of laser– arc hybrid welding in the joining of metals. The study uses quantitative and qualitative research methods which include in-depth, interpretive analyses of results from a number of research groups. In the interpretive analysis, the emphasis is placed on the relevance and usefulness of the investigative results drawn from other research publications. The results of this study contribute to research on laser–arc hybrid welding by increasing understanding of how old and new perspectives on laser–arc hybrid welding are evidenced in industry. The research methodology applied permits continued exploration of how laser–arc hybrid welding and various process factors influence the overall quality of the weld. Thestudy provides a good foundation for future research, creates improved awareness of the laser–arc hybrid welding process, and assists the metal industry to maximize welding productivity.