166 resultados para process model consolidation


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Software is a key component in many of our devices and products that we use every day. Most customers demand not only that their devices should function as expected but also that the software should be of high quality, reliable, fault tolerant, efficient, etc. In short, it is not enough that a calculator gives the correct result of a calculation, we want the result instantly, in the right form, with minimal use of battery, etc. One of the key aspects for succeeding in today's industry is delivering high quality. In most software development projects, high-quality software is achieved by rigorous testing and good quality assurance practices. However, today, customers are asking for these high quality software products at an ever-increasing pace. This leaves the companies with less time for development. Software testing is an expensive activity, because it requires much manual work. Testing, debugging, and verification are estimated to consume 50 to 75 per cent of the total development cost of complex software projects. Further, the most expensive software defects are those which have to be fixed after the product is released. One of the main challenges in software development is reducing the associated cost and time of software testing without sacrificing the quality of the developed software. It is often not enough to only demonstrate that a piece of software is functioning correctly. Usually, many other aspects of the software, such as performance, security, scalability, usability, etc., need also to be verified. Testing these aspects of the software is traditionally referred to as nonfunctional testing. One of the major challenges with non-functional testing is that it is usually carried out at the end of the software development process when most of the functionality is implemented. This is due to the fact that non-functional aspects, such as performance or security, apply to the software as a whole. In this thesis, we study the use of model-based testing. We present approaches to automatically generate tests from behavioral models for solving some of these challenges. We show that model-based testing is not only applicable to functional testing but also to non-functional testing. In its simplest form, performance testing is performed by executing multiple test sequences at once while observing the software in terms of responsiveness and stability, rather than the output. The main contribution of the thesis is a coherent model-based testing approach for testing functional and performance related issues in software systems. We show how we go from system models, expressed in the Unified Modeling Language, to test cases and back to models again. The system requirements are traced throughout the entire testing process. Requirements traceability facilitates finding faults in the design and implementation of the software. In the research field of model-based testing, many new proposed approaches suffer from poor or the lack of tool support. Therefore, the second contribution of this thesis is proper tool support for the proposed approach that is integrated with leading industry tools. We o er independent tools, tools that are integrated with other industry leading tools, and complete tool-chains when necessary. Many model-based testing approaches proposed by the research community suffer from poor empirical validation in an industrial context. In order to demonstrate the applicability of our proposed approach, we apply our research to several systems, including industrial ones.

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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.

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Nykypäivän monimutkaisessa ja epävakaassa liiketoimintaympäristössä yritykset, jotka kykenevät muuttamaan tuottamansa operatiivisen datan tietovarastoiksi, voivat saavuttaa merkittävää kilpailuetua. Ennustavan analytiikan hyödyntäminen tulevien trendien ennakointiin mahdollistaa yritysten tunnistavan avaintekijöitä, joiden avulla he pystyvät erottumaan kilpailijoistaan. Ennustavan analytiikan hyödyntäminen osana päätöksentekoprosessia mahdollistaa ketterämmän, reaaliaikaisen päätöksenteon. Tämän diplomityön tarkoituksena on koota teoreettinen viitekehys analytiikan mallintamisesta liike-elämän loppukäyttäjän näkökulmasta ja hyödyntää tätä mallinnusprosessia diplomityön tapaustutkimuksen yritykseen. Teoreettista mallia hyödynnettiin asiakkuuksien mallintamisessa sekä tunnistamalla ennakoivia tekijöitä myynnin ennustamiseen. Työ suoritettiin suomalaiseen teollisten suodattimien tukkukauppaan, jolla on liiketoimintaa Suomessa, Venäjällä ja Balteissa. Tämä tutkimus on määrällinen tapaustutkimus, jossa tärkeimpänä tiedonkeruumenetelmänä käytettiin tapausyrityksen transaktiodataa. Data työhön saatiin yrityksen toiminnanohjausjärjestelmästä.

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Financial time series have a tendency of abruptly changing their behavior and maintain this behavior for several consecutive periods, and commodity futures returns are not an exception. This quality proposes that nonlinear models, as opposed to linear models, can more accurately describe returns and volatility. Markov regime switching models are able to match this behavior and have become a popular way to model financial time series. This study uses Markov regime switching model to describe the behavior of energy futures returns on a commodity level, because studies show that commodity futures are a heterogeneous asset class. The purpose of this thesis is twofold. First, determine how many regimes characterize individual energy commodities’ returns in different return frequencies. Second, study the characteristics of these regimes. We extent the previous studies on the subject in two ways: We allow for the possibility that the number of regimes may exceed two, as well as conduct the research on individual commodities rather than on commodity indices or subgroups of these indices. We use daily, weekly and monthly time series of Brent crude oil, WTI crude oil, natural gas, heating oil and gasoil futures returns over 1994–2014, where available, to carry out the study. We apply the likelihood ratio test to determine the sufficient number of regimes for each commodity and data frequency. Then the time series are modeled with Markov regime switching model to obtain the return distribution characteristics of each regime, as well as the transition probabilities of moving between regimes. The results for the number of regimes suggest that daily energy futures return series consist of three to six regimes, whereas weekly and monthly returns for all energy commodities display only two regimes. When the number of regimes exceeds two, there is a tendency for the time series of energy commodities to form groups of regimes. These groups are usually quite persistent as a whole because probability of a regime switch inside the group is high. However, individual regimes in these groups are not persistent and the process oscillates between these regimes frequently. Regimes that are not part of any group are generally persistent, but show low ergodic probability, i.e. rarely prevail in the market. This study also suggests that energy futures return series characterized with two regimes do not necessarily display persistent bull and bear regimes. In fact, for the majority of time series, bearish regime is considerably less persistent. Rahoituksen aikasarjoilla on taipumus arvaamattomasti muuttaa käyttäytymistään ja jatkaa tätä uutta käyttäytymistä useiden periodien ajan, eivätkä hyödykefutuurien tuotot tee tähän poikkeusta. Tämän ominaisuuden johdosta lineaaristen mallien sijasta epälineaariset mallit pystyvät tarkemmin kuvailemaan esimerkiksi tuottojen jakauman parametreja. Markov regiiminvaihtomallit pystyvät vangitsemaan tämän ominaisuuden ja siksi niistä on tullut suosittuja rahoituksen aikasarjojen mallintamisessa. Tämä tutkimus käyttää Markov regiiminvaihtomallia kuvaamaan yksittäisten energiafutuurien tuottojen käyttäytymistä, sillä tutkimukset osoittavat hyödykefutuurien olevan hyvin heterogeeninen omaisuusluokka. Tutkimuksen tarkoitus on selvittää, kuinka monta regiimiä tarvitaan kuvaamaan energiafutuurien tuottoja eri tuottofrekvensseillä ja mitkä ovat näiden regiimien ominaisuudet. Aiempaa tutkimusta aiheesta laajennetaan määrittämällä regiimien lukumäärä tilastotieteellisen testauksen menetelmin sekä tutkimalla energiafutuureja yksittäin; ei indeksi- tai alaindeksitasolla. Tutkimuksessa käytetään päivä-, viikko- ja kuukausiaikasarjoja Brent-raakaöljyn, WTI-raakaöljyn, maakaasun, lämmitysöljyn ja polttoöljyn tuotoista aikaväliltä 1994–2014, siltä osin kuin aineistoa on saatavilla. Likelihood ratio -testin avulla estimoidaan kaikille aikasarjoille regiimien määrä,jonka jälkeen Markov regiiminvaihtomallia hyödyntäen määritetään yksittäisten regiimientuottojakaumien ominaisuudet sekä regiimien välinen transitiomatriisi. Tulokset regiimien lukumäärän osalta osoittavat, että energiafutuurien päiväkohtaisten tuottojen aikasarjoissa regiimien lukumäärä vaihtelee kolmen ja kuuden välillä. Viikko- ja kuukausituottojen kohdalla kaikkien energiafutuurien prosesseissa regiimien lukumäärä on kaksi. Kun regiimejä on enemmän kuin kaksi, on prosessilla taipumus muodostaa regiimeistä koostuvia ryhmiä. Prosessi pysyy ryhmän sisällä yleensä pitkään, koska todennäköisyys siirtyä ryhmään kuuluvien regiimien välillä on suuri. Yksittäiset regiimit ryhmän sisällä eivät kuitenkaan ole kovin pysyviä. Näin ollen prosessi vaihtelee ryhmän sisäisten regiimien välillä tiuhaan. Regiimit, jotka eivät kuulu ryhmään, ovat yleensä pysyviä, mutta prosessi ajautuu niihin vain harvoin, sillä todennäköisyys siirtyä muista regiimeistä niihin on pieni. Tutkimuksen tulokset osoittavat myös, että prosesseissa, joita ohjaa kaksi regiimiä, nämä regiimit eivät välttämättä ole pysyvät bull- ja bear-markkinatilanteet. Tulokset osoittavat sen sijaan, että bear-markkinatilanne on energiafutuureissa selvästi vähemmän pysyvä.

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The aim of this thesis is to define effects of lignin separation process on Pulp mill chemical balance especially on sodium/sulphur-balance. The objective is to develop a simulation model with WinGEMS Process Simulator and use that model to simulate the chemical balances and process changes. The literature part explains what lignin is and how kraft pulp is produced. It also introduces to the methods that can be used to extract lignin from black liquor stream and how those methods affect the pulping process. In experimental part seven different cases are simulated with the created simulation model. The simulations are based on selected reference mill that produces 500 000 tons of bleached air-dried (90 %) pulp per year. The simulations include the chemical balance calculation and the estimated production increase. Based on the simulations the heat load of the recovery boiler can be reduced and the pulp production increased when lignin is extracted. The simulations showed that decreasing the waste acid stream intake from the chlorine dioxide plant is an effective method to control the sulphidity level when about 10 % of lignin is extracted. With higher lignin removal rates the in-mill sulphuric acid production has been discovered to be a better alternative to the sulphidity control.

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Tämä diplomityö arvioi hitsauksen laadunhallintaohjelmistomarkkinoiden kilpailijoita. Kilpailukenttä on uusi ja ei ole tarkkaa tietoa siitä minkälaisia kilpailijoita on markkinoilla. Hitsauksen laadunhallintaohjelmisto auttaa yrityksiä takaamaan korkean laadun. Ohjelmisto takaa korkean laadun varmistamalla, että hitsaaja on pätevä, hän noudattaa hitsausohjeita ja annettuja parametreja. Sen lisäksi ohjelmisto kerää kaiken tiedon hitsausprosessista ja luo siitä vaadittavat dokumentit. Diplomityön teoriaosuus muodostuu kirjallisuuskatsauksesta ratkaisuliike-toimintaan, kilpailija-analyysin ja kilpailuvoimien teoriaan sekä hitsauksen laadunhallintaan. Työn empiriaosuus on laadullinen tutkimus, jossa tutkitaan kilpailevia hitsauksen laadunhallintaohjelmistoja ja haastatellaan ohjelmistojen käyttäjiä. Diplomityön tuloksena saadaan uusi kilpailija-analyysimalli hitsauksen laadunhallintaohjelmistoille. Mallin avulla voidaan arvostella ohjelmistot niiden tarjoamien primääri- ja sekundääriominaisuuksien perusteella. Toiseksi tässä diplomityössä analysoidaan nykyinen kilpailijatilanne hyödyntämällä juuri kehitettyä kilpailija-analyysimallia.

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The computer game industry has grown steadily for years, and in revenues it can be compared to the music and film industries. The game industry has been moving to digital distribution. Computer gaming and the concept of business model are discussed among industrial practitioners and the scientific community. The significance of the business model concept has increased in the scientific literature recently, although there is still a lot of discussion going on on the concept. In the thesis, the role of the business model in the computer game industry is studied. Computer game developers, designers, project managers and organization leaders in 11 computer game companies were interviewed. The data was analyzed to identify the important elements of computer game business model, how the business model concept is perceived and how the growth of the organization affects the business model. It was identified that the importance of human capital is crucial to the business. As games are partly a product of creative thinking also innovation and the creative process are highly valued. The same applies to technical skills when performing various activities. Marketing and customer relationships are also considered as key elements in the computer game business model. Financing and partners are important especially for startups, when the organization is dependent on external funding and third party assets. The results of this study provide organizations with improved understanding on how the organization is built and what business model elements are weighted.

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The importance of industrial maintenance has been emphasized during the last decades; it is no longer a mere cost item, but one of the mainstays of business. Market conditions have worsened lately, investments in production assets have decreased, and at the same time competition has changed from taking place between companies to competition between networks. Companies have focused on their core functions and outsourced support services, like maintenance, above all to decrease costs. This new phenomenon has led to increasing formation of business networks. As a result, a growing need for new kinds of tools for managing these networks effectively has arisen. Maintenance costs are usually a notable part of the life-cycle costs of an item, and it is important to be able to plan the future maintenance operations for the strategic period of the company or for the whole life-cycle period of the item. This thesis introduces an itemlevel life-cycle model (LCM) for industrial maintenance networks. The term item is used as a common definition for a part, a component, a piece of equipment etc. The constructed LCM is a working tool for a maintenance network (consisting of customer companies that buy maintenance services and various supplier companies). Each network member is able to input their own cost and profit data related to the maintenance services of one item. As a result, the model calculates the net present values of maintenance costs and profits and presents them from the points of view of all the network members. The thesis indicates that previous LCMs for calculating maintenance costs have often been very case-specific, suitable only for the item in question, and they have also been constructed for the needs of a single company, without the network perspective. The developed LCM is a proper tool for the decision making of maintenance services in the network environment; it enables analysing the past and making scenarios for the future, and offers choices between alternative maintenance operations. The LCM is also suitable for small companies in building active networks to offer outsourcing services for large companies. The research introduces also a five-step constructing process for designing a life-cycle costing model in the network environment. This five-step designing process defines model components and structure throughout the iteration and exploitation of user feedback. The same method can be followed to develop other models. The thesis contributes to the literature of value and value elements of maintenance services. It examines the value of maintenance services from the perspective of different maintenance network members and presents established value element lists for the customer and the service provider. These value element lists enable making value visible in the maintenance operations of a networked business. The LCM added with value thinking promotes the notion of maintenance from a “cost maker” towards a “value creator”.

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In the new age of information technology, big data has grown to be the prominent phenomena. As information technology evolves, organizations have begun to adopt big data and apply it as a tool throughout their decision-making processes. Research on big data has grown in the past years however mainly from a technical stance and there is a void in business related cases. This thesis fills the gap in the research by addressing big data challenges and failure cases. The Technology-Organization-Environment framework was applied to carry out a literature review on trends in Business Intelligence and Knowledge management information system failures. A review of extant literature was carried out using a collection of leading information system journals. Academic papers and articles on big data, Business Intelligence, Decision Support Systems, and Knowledge Management systems were studied from both failure and success aspects in order to build a model for big data failure. I continue and delineate the contribution of the Information System failure literature as it is the principal dynamics behind technology-organization-environment framework. The gathered literature was then categorised and a failure model was developed from the identified critical failure points. The failure constructs were further categorized, defined, and tabulated into a contextual diagram. The developed model and table were designed to act as comprehensive starting point and as general guidance for academics, CIOs or other system stakeholders to facilitate decision-making in big data adoption process by measuring the effect of technological, organizational, and environmental variables with perceived benefits, dissatisfaction and discontinued use.

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In the new age of information technology, big data has grown to be the prominent phenomena. As information technology evolves, organizations have begun to adopt big data and apply it as a tool throughout their decision-making processes. Research on big data has grown in the past years however mainly from a technical stance and there is a void in business related cases. This thesis fills the gap in the research by addressing big data challenges and failure cases. The Technology-Organization-Environment framework was applied to carry out a literature review on trends in Business Intelligence and Knowledge management information system failures. A review of extant literature was carried out using a collection of leading information system journals. Academic papers and articles on big data, Business Intelligence, Decision Support Systems, and Knowledge Management systems were studied from both failure and success aspects in order to build a model for big data failure. I continue and delineate the contribution of the Information System failure literature as it is the principal dynamics behind technology-organization-environment framework. The gathered literature was then categorised and a failure model was developed from the identified critical failure points. The failure constructs were further categorized, defined, and tabulated into a contextual diagram. The developed model and table were designed to act as comprehensive starting point and as general guidance for academics, CIOs or other system stakeholders to facilitate decision-making in big data adoption process by measuring the effect of technological, organizational, and environmental variables with perceived benefits, dissatisfaction and discontinued use.

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The Finnish legislation requires for a safe and secure learning environment. However, the comprehensive, risk based safety and security management (SSM) and the management commitment in the implementation and development of the SSM are not mentioned in the legislation. Multiple institutions, operators and researchers have studied and developed safety and security in educational institutions over the past decade. Typically the approach has been fragmented and without bringing up the importance of the comprehensive SSM. The development needs of the safety and security operations in universities have been studied. However, in universities of applied sciences (UASs) and in elementary schools (ESs), the performance level, strengths and weaknesses of the comprehensive SSM have not been studied. The objective of this study was to develop the comprehensive, risk based SSM of educational institutions by developing the new Asteri consultative auditing process and study its effects on auditees. Furthermore, the performance level in the comprehensive SSM in UASs and ESs were studied using Asteri and the TUTOR model developed by the Keski-Uusimaa Department for Rescue Services. In addition, strengths, development needs and differences were identified. In total, 76 educational institutions were audited between the years 2011 and 2014. The study is based on logical empiricism, and an observational applied research design was used. Auditing, observation and an electronic survey were used for data collection. Statistical analysis was used to analyze the collected information. In addition, thematic analysis was used to analyze the development areas of the organizations mentioned by the respondents in the survey. As one of the main contributions, this research presents the new Asteri consultative auditing process. Organizations with low performance levels on the audited subject benefit the most from the Asteri consultative auditing process. Asteri may be usable in many different types of audits, not only in SSM audits. As a new result, this study provides new knowledge on attitudes related to auditing. According to the research findings, auditing may generate negative attitudes and the auditor should take them into account when planning and preparing for audits. Negative attitudes can be compensated by producing added value, objectivity and positivity for the audit and, thus, improve the positive effects of auditing on knowledge and skills. Moreover, as the results of this study shows, auditing safety and security issues do not increase feelings of insecurity, but rather increase feelings of safety and security when using the new Asteri consultative auditing process with the TUTOR model. The results showed that the SSM in the audited UASs was statistically significantly more advanced than that in the audited ESs. However, there is still room for improvement in the ESs and the UASs as the approach to the SSM was fragmented. It can be assumed that the majority of Finnish UASs and ESs do not likely meet the basic level of the comprehensive, risk based the SSM.

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The purpose of this study is to investigate the challenges of the adaptation process of education export. The research is conducted as a single case study that concentrates on three education export projects. The case company in the research is Team Academy. The study goes through the different forms of education export, the adaptation of education export and the challenges of the education export –process by means of theory and empirical data. The research is carried out as a qualitative research and the method used is a qualitative content analysis. More specifically the research is an abductive content analysis. The research data is collected in four in-depth interviews from Team academy representatives who have been strongly involved in certain education export –project of Team Academy. The research confirms the theory in the challenge of hierarchy, funding and registration issues, and refutes it in the challenge of competition, legislation, different governmental attitudes and knowledge in productization. The main challenges of the adaptation process are related to funding, differences in values, sudden changes, the complex nature of the learning model, concept of time, teamwork as method and accreditation. It is highlighted that in the future operations, anticipating problems that arise from for example cultural differences and differences in values, communication, managing the money flows and the company form is recommended. Future research could continue with investigating the suitable company form for education exports of this kind, and how to stand out and communicate when operating under another institution. It is considered a potential risk that a brand encloses the brand that operates under it.

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The objective of this research is to create a current state analysis of pulp supply chain processes from production planning to deliveries to customers. A cross-functional flowchart is being used to model these processes. These models help finding key performance indicators (KPIs) which enable examinations of the supply chain efficiency. Supply chain measures in different processes reveal the changes need processes that affect the whole supply chain and its efficiency and competitiveness. Structure of pulp supply chain differs from most of the other supply chains. The fact that there are big volumes of bulk products, small product variations and supply forecasts are made for the year ahead make the difference. This factor brings different benefits but also challenges when developing supply chain. This thesis divides pulp supply chain in three different main categories: production planning, warehousing and transportation. It provides tools for estimating the functionality of supply chain as well as developing the efficiency for different functions of supply chain. By having a better understanding of supply chain processes and measurement the whole supply chain structure can be developed significantly.

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This is a Master’s thesis research, which mainly aims at identifying the sustainability issues in sourcing process and to identify the core competencies in sourcing process through triple bottom line adaptation. The focus of this thesis is on apparel industry’s sourcing process. The purpose of this thesis is to examine global apparel industry’s reality in their sourcing process and how buyers-suppliers are cooperating with their sourcing process to incorporate sustainability. Other goal of this research paper is to provide recommendation for sustainable sourcing process for companies and how the stakeholders can be benefitted by sustainable sourcing. The literature review part of this paper has presented the research gaps from the earlier researches along with the key concepts, academic purposes and key definitions. Theoretical framework chapter has focused on global sourcing strategies and firm’s competencies and sustainable strategies. From the theoretical framework, author has presented essential theory which establishes the link between research questions and proposed hypotheses. Main results and findings have been presented in empirical findings and in data analysis chapter. This study is an exploratory research followed by deductive method and primary data has been used to evaluate the current situation of apparel industry; which will assist to build the recommendation model. Primary data has been collected through online questionnaires and secondary data has used to cover the literature and theoretical parts. Therefore, the potential outcome of this paper will display the importance of sustainable sourcing from academic point of view and also from the business perspective. As a final point, this paper has followed the research objectives and has generated some new directions for further studies.

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The issue of selecting an appropriate healthcare information system is a very essential one. If implemented healthcare information system doesn’t fit particular healthcare institution, for example there are unnecessary functions; healthcare institution wastes its resources and its efficiency decreases. The purpose of this research is to develop a healthcare information system selection model to assist the decision-making process of choosing healthcare information system. Appropriate healthcare information system helps healthcare institutions to become more effective and efficient and keep up with the times. The research is based on comparison analysis of 50 healthcare information systems and 6 interviews with experts from St-Petersburg healthcare institutions that already have experience in healthcare information system utilization. 13 characteristics of healthcare information systems: 5 key and 7 additional features are identified and considered in the selection model development. Variables are used in the selection model in order to narrow the decision algorithm and to avoid duplication of brunches. The questions in the healthcare information systems selection model are designed to be easy-to-understand for common a decision-maker in healthcare institution without permanent establishment.