Integrated Project Portfolio Management as a Tool for Strategic Steering and Business Control

Tutkielman päätavoitteena oli tutkia miten projektisalkun hallinnalla voidaan tukea organisaation strategista ohjausta ja liiketoimintaa. Tämän lisäksi avaintavoitteina oli kuvata projektisalkun hallinnan nykytilanne kohdeyrityksessä, paljastaa erityisiä kehitystarpeita ja lopulta luoda kohdeyrityksen projektisalkunhallinnalle tavoitetila. Kirjallisuuskatsauksessa pohdittiin projektisalkun hallinnan roolia ja tavoitteita, projektisalkun hallinnassa käyttävää prosessia, sekä menetelmiä ja tekniikoita, joilla salkkua hallitaan. Työn empiirisessä osassa syvennyttiin tutkimaan projektinsalkun hallintaan liittyviä erityispiirteitä kohdeyrityksessä. Tutkimustulosten huolellinen analysointi osoitti, että aikaisempi kirjallisuus ei riittävästi huomioi kokonaisvaltaisen, integroidun lähestymistavan tarvetta ja viestinnän tärkeyttä projektisalkun hallinnassa. Tutkimuksen johtopäätöksinä luotiin uusi integroitu projektisalkun hallintamalli ja määriteltiin kohdeyritykselle projektisalkun hallinnan tavoitetila sekä ne kehitysaskeleet, joita yrityksen tulisi lähitulevaisuudessa ottaa.

Soft Computing Methods in Metallurgy

In metallurgic plants a high quality metal production is always required. Nowadays soft computing applications are more often used for automation of manufacturing process and quality control instead of mechanical techniques. In this thesis an overview of soft computing methods presents. As an example of soft computing application, an effective model of fuzzy expert system for the automotive quality control of steel degassing process was developed. The purpose of this work is to describe the fuzzy relations as quality hypersurfaces by varying number of linguistic variables and fuzzy sets.

Odor emission control and reduce in betaine manufacture

This thesis was made in Naantali plant of Finnfeeds Finland Oy. In this thesis the main study was in reducing, controlling, measuring and processing odour effluents in various methods. Also are considered legislation, marketing issues and environmental requirements of reducing of odour effluents. The literature review introduces odours complications, legislations and various methods of odour removal. There is also a review of volatile organic compounds detection and measuring methods. The experimental section consists TD-GC-MS-measurements and expansive measurements with electronic nose. Electronic nose is a new solution for recognition and measuring industrial odours. In this thesis the electronic nose was adapted into reliable recognition and measuring method. Measurements with electronic nose was made in betaine factory and main targets were odour removal process and other odours from factory. As a result of experimental work with TD-GC-MS-measurements becomes odour compound of 2-and 3- methylbutanal and dimethyldisulfide, which odour is sweet and fug. Extensive study with electronic nose found many developmental subjects. Odour balance measurements of factory and after calculation made adjustment of odour removal process, over all odour effluent to environment will reduce 25 %.

On the Analysis and Control of a Linear Synchronous Servomotor with a Flexible Load

Industry's growing need for higher productivity is placing new demands on mechanisms connected with electrical motors, because these can easily lead to vibration problems due to fast dynamics. Furthermore, the nonlinear effects caused by a motor frequently reduce servo stability, which diminishes the controller's ability to predict and maintain speed. Hence, the flexibility of a mechanism and its control has become an important area of research. The basic approach in control system engineering is to assume that the mechanism connected to a motor is rigid, so that vibrations in the tool mechanism, reel, gripper or any apparatus connected to the motor are not taken into account. This might reduce the ability of the machine system to carry out its assignment and shorten the lifetime of the equipment. Nonetheless, it is usually more important to know how the mechanism, or in other words the load on the motor, behaves. A nonlinear load control method for a permanent magnet linear synchronous motor is developed and implemented in the thesis. The purpose of the controller is to track a flexible load to the desired velocity reference as fast as possible and without awkward oscillations. The control method is based on an adaptive backstepping algorithm with its stability ensured by the Lyapunov stability theorem. As a reference controller for the backstepping method, a hybrid neural controller is introduced in which the linear motor itself is controlled by a conventional PI velocity controller and the vibration of the associated flexible mechanism is suppressed from an outer control loop using a compensation signal from a multilayer perceptron network. To avoid the local minimum problem entailed in neural networks, the initial weights are searched for offline by means of a differential evolution algorithm. The states of a mechanical system for controllers are estimated using the Kalman filter. The theoretical results obtained from the control design are validated with the lumped mass model for a mechanism. Generalization of the mechanism allows the methods derived here to be widely implemented in machine automation. The control algorithms are first designed in a specially introduced nonlinear simulation model and then implemented in the physical linear motor using a DSP (Digital Signal Processor) application. The measurements prove that both controllers are capable of suppressing vibration, but that the backstepping method is superior to others due to its accuracy of response and stability properties.

Adaptive MCMC methods with applications in environmental and geophysical models

This work presents new, efficient Markov chain Monte Carlo (MCMC) simulation methods for statistical analysis in various modelling applications. When using MCMC methods, the model is simulated repeatedly to explore the probability distribution describing the uncertainties in model parameters and predictions. In adaptive MCMC methods based on the Metropolis-Hastings algorithm, the proposal distribution needed by the algorithm learns from the target distribution as the simulation proceeds. Adaptive MCMC methods have been subject of intensive research lately, as they open a way for essentially easier use of the methodology. The lack of user-friendly computer programs has been a main obstacle for wider acceptance of the methods. This work provides two new adaptive MCMC methods: DRAM and AARJ. The DRAM method has been built especially to work in high dimensional and non-linear problems. The AARJ method is an extension to DRAM for model selection problems, where the mathematical formulation of the model is uncertain and we want simultaneously to fit several different models to the same observations. The methods were developed while keeping in mind the needs of modelling applications typical in environmental sciences. The development work has been pursued while working with several application projects. The applications presented in this work are: a winter time oxygen concentration model for Lake Tuusulanjärvi and adaptive control of the aerator; a nutrition model for Lake Pyhäjärvi and lake management planning; validation of the algorithms of the GOMOS ozone remote sensing instrument on board the Envisat satellite of European Space Agency and the study of the effects of aerosol model selection on the GOMOS algorithm.

Modernization of protection and control system of HV/MV substation in Russia

This work describes different possibilities of protection and control system improvement of primary distribution substation. The status of condition and main problems of power networks from reliability point of view in Russia are described. This work studies technologies used today in Russia for protection of distribution networks with their disadvantages. Majority of medium voltage networks (6-35 kV) has isolated network point. There is still no any protection available on the market which allows to estimate distance to fault in case of earth fault. The thesis analyses methods of earth fault distance calculation. On the basis of computer simulation the influence of various factors on calculation accuracy is studied. The practical implementation of the method presupposes usage of digital relay. Application of digital relay is accompanied by numerous opportunities which are described in this work. Also advantages of system implemented on the basis of IEC 61850 standard are examined. Finally, suitability of modern digital relays from GOST standard point of view is analyzed.

Developing of the Variable Speed Drive -control in simulated parallel pumping systems

This thesis presents briefly the basic operation and use of centrifugal pumps and parallel pumping applications. The characteristics of parallel pumping applications are compared to circuitry, in order to search analogy between these technical fields. The purpose of studying circuitry is to find out if common software tools for solving circuit performance could be used to observe parallel pumping applications. The empirical part of the thesis introduces a simulation environment for parallel pumping systems, which is based on circuit components of Matlab Simulink —software. The created simulation environment ensures the observation of variable speed controlled parallel pumping systems in case of different controlling methods. The introduced simulation environment was evaluated by building a simulation model for actual parallel pumping system at Lappeenranta University of Technology. The simulated performance of the parallel pumps was compared to measured values of the actual system. The gathered information shows, that if the initial data of the system and pump perfonnance is adequate, the circuitry based simulation environment can be exploited to observe parallel pumping systems. The introduced simulation environment can represent the actual operation of parallel pumps in reasonably accuracy. There by the circuitry based simulation can be used as a researching tool to develop new controlling ways for parallel pumps.

Position sensorless electrically excited synchronous motor drive for industrial use based on direct flux linkage and torque control

Synchronous machines with an AC converter are used mainly in large drives, for example in ship propulsion drives as well as in rolling mill drives in steel industry. These motors are used because of their high efficiency, high overload capacity and good performance in the field weakening area. Present day drives for electrically excited synchronous motors are equipped with position sensors. Most drives for electrically excited synchronous motors will be equipped with position sensors also in future. This kind of drives with good dynamics are mainly used in metal industry. Drives without a position sensor can be used e.g. in ship propulsion and in large pump and blower drives. Nowadays, these drives are equipped with a position sensor, too. The tendency is to avoid a position sensor if possible, since a sensor reduces the reliability of the drive and increases costs (latter is not very significant for large drives). A new control technique for a synchronous motor drive is a combination of the Direct Flux Linkage Control (DFLC) based on a voltage model and a supervising method (e.g. current model). This combination is called Direct Torque Control method (DTC). In the case of the position sensorless drive, the DTC can be implemented by using other supervising methods that keep the stator flux linkage origin centered. In this thesis, a method for the observation of the drift of the real stator flux linkage in the DTC drive is introduced. It is also shown how this method can be used as a supervising method that keeps the stator flux linkage origin centered in the case of the DTC. In the position sensorless case, a synchronous motor can be started up with the DTC control, when a method for the determination of the initial rotor position presented in this thesis is used. The load characteristics of such a drive are not very good at low rotational speeds. Furthermore, continuous operation at a zero speed and at a low rotational speed is not possible, which is partly due to the problems related to the flux linkage estimate. For operation in a low speed area, a stator current control method based on the DFLC modulator (DMCQ is presented. With the DMCC, it is possible to start up and operate a synchronous motor at a zero speed and at low rotational speeds in general. The DMCC is necessary in situations where high torque (e.g. nominal torque) is required at the starting moment, or if the motor runs several seconds at a zero speed or at a low speed range (up to 2 Hz). The behaviour of the described methods is shown with test results. The test results are presented for the direct flux linkage and torque controlled test drive system with a 14.5 kVA, four pole salient pole synchronous motor with a damper winding and electric excitation. The static accuracy of the drive is verified by measuring the torque in a static load operation, and the dynamics of the drive is proven in load transient tests. The performance of the drive concept presented in this work is sufficient e.g. for ship propulsion and for large pump drives. Furthermore, the developed methods are almost independent of the machine parameters.

On Fault Tolerance Methods for Networks-on-Chip

Technology scaling has proceeded into dimensions in which the reliability of manufactured devices is becoming endangered. The reliability decrease is a consequence of physical limitations, relative increase of variations, and decreasing noise margins, among others. A promising solution for bringing the reliability of circuits back to a desired level is the use of design methods which introduce tolerance against possible faults in an integrated circuit. This thesis studies and presents fault tolerance methods for network-onchip (NoC) which is a design paradigm targeted for very large systems-onchip. In a NoC resources, such as processors and memories, are connected to a communication network; comparable to the Internet. Fault tolerance in such a system can be achieved at many abstraction levels. The thesis studies the origin of faults in modern technologies and explains the classification to transient, intermittent and permanent faults. A survey of fault tolerance methods is presented to demonstrate the diversity of available methods. Networks-on-chip are approached by exploring their main design choices: the selection of a topology, routing protocol, and flow control method. Fault tolerance methods for NoCs are studied at different layers of the OSI reference model. The data link layer provides a reliable communication link over a physical channel. Error control coding is an efficient fault tolerance method especially against transient faults at this abstraction level. Error control coding methods suitable for on-chip communication are studied and their implementations presented. Error control coding loses its effectiveness in the presence of intermittent and permanent faults. Therefore, other solutions against them are presented. The introduction of spare wires and split transmissions are shown to provide good tolerance against intermittent and permanent errors and their combination to error control coding is illustrated. At the network layer positioned above the data link layer, fault tolerance can be achieved with the design of fault tolerant network topologies and routing algorithms. Both of these approaches are presented in the thesis together with realizations in the both categories. The thesis concludes that an optimal fault tolerance solution contains carefully co-designed elements from different abstraction levels

Advanced chemometric methods: Applicability on industrial data

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.

Simulating the performance of paper machine control

The topic of this thesis is the simulation of a combination of several control and data assimilation methods, meant to be used for controlling the quality of paper in a paper machine. Paper making is a very complex process and the information obtained from the web is sparse. A paper web scanner can only measure a zig zag path on the web. An assimilation method is needed to process estimates for Machine Direction (MD) and Cross Direction (CD) profiles of the web. Quality control is based on these measurements. There is an increasing need for intelligent methods to assist in data assimilation. The target of this thesis is to study how such intelligent assimilation methods are affecting paper web quality. This work is based on a paper web simulator, which has been developed in the TEKES funded MASI NoTes project. The simulator is a valuable tool in comparing different assimilation methods. The thesis contains the comparison of four different assimilation methods. These data assimilation methods are a first order Bayesian model estimator, an ARMA model based on a higher order Bayesian estimator, a Fourier transform based Kalman filter estimator and a simple block estimator. The last one can be considered to be close to current operational methods. From these methods Bayesian, ARMA and Kalman all seem to have advantages over the commercial one. The Kalman and ARMA estimators seems to be best in overall performance.

Heating control of an electrical motor

Electrical motors on a ship attackable to different factors which decrease these lifetimes. One of the main external factors on a ship which usually is a reason of the motor failure is a moisture condensation which decreases the motor winding insulation and increase a probability of the short circuit. Therefore, the protection against moisture is necessary for ship electrical motors. The motor should be protected against moisture all time when it does not operate. The necessity of such protection requires a lot of energy consumption. This master’s thesis is focused on the creation of the electrical motor thermal model and on the different methods of the motor protection against moisture analysis with energy consumption point of view.

Energy harvesting methods for wireless sensor nodes in heavy-duty vehicles

The number of autonomous wireless sensor and control nodes has been increasing rapidly during the last decade. Until recently, these wireless nodes have been powered with batteries, which have lead to a short life cycle and high maintenance need. Due to these battery-related problems, new energy sources have been studied to power wireless nodes. One solution is energy harvesting, i.e. extracting energy from the ambient environment. Energy harvesting can provide a long-lasting power source for sensor nodes, with no need for maintenance. In this thesis, various energy harvesting technologies are studied whilst focusing on the theory of each technology and the state-of-the-art solutions of published studies and commercial solutions. In addition to energy harvesting, energy storage and energy management solutions are also studied as a subsystem of a whole energy source solution. Wireless nodes are also used in heavy-duty vehicles. Therefore a reliable, long-lasting and maintenance-free power source is also needed in this kind of environment. A forestry harvester has been used as a case study to study the feasibility of energy harvesting in a forestry harvester’s sliding boom. The energy harvester should be able to produce few milliwatts to power the target system, an independent limit switch.

A study of combustion phenomena in circulating fluidized beds by developing and applying experimental and modelling methods for laboratory-scale reactors

The results shown in this thesis are based on selected publications of the 2000s decade. The work was carried out in several national and EC funded public research projects and in close cooperation with industrial partners. The main objective of the thesis was to study and quantify the most important phenomena of circulating fluidized bed combustors by developing and applying proper experimental and modelling methods using laboratory scale equipments. An understanding of the phenomena plays an essential role in the development of combustion and emission performance, and the availability and controls of CFB boilers. Experimental procedures to study fuel combustion behaviour under CFB conditions are presented in the thesis. Steady state and dynamic measurements under well controlled conditions were carried out to produce the data needed for the development of high efficiency, utility scale CFB technology. The importance of combustion control and furnace dynamics is emphasized when CFB boilers are scaled up with a once through steam cycle. Qualitative information on fuel combustion characteristics was obtained directly by comparing flue gas oxygen responses during the impulse change experiments with fuel feed. A one-dimensional, time dependent model was developed to analyse the measurement data Emission formation was studied combined with fuel combustion behaviour. Correlations were developed for NO, N2O, CO and char loading, as a function of temperature and oxygen concentration in the bed area. An online method to characterize char loading under CFB conditions was developed and validated with the pilot scale CFB tests. Finally, a new method to control air and fuel feeds in CFB combustion was introduced. The method is based on models and an analysis of the fluctuation of the flue gas oxygen concentration. The effect of high oxygen concentrations on fuel combustion behaviour was also studied to evaluate the potential of CFB boilers to apply oxygenfiring technology to CCS. In future studies, it will be necessary to go through the whole scale up chain from laboratory phenomena devices through pilot scale test rigs to large scale, commercial boilers in order to validate the applicability and scalability of the, results. This thesis shows the chain between the laboratory scale phenomena test rig (bench scale) and the CFB process test rig (pilot). CFB technology has been scaled up successfully from an industrial scale to a utility scale during the last decade. The work shown in the thesis, for its part, has supported the development by producing new detailed information on combustion under CFB conditions.

Methods for construction and analysis of computational models in systems biology : applications to the modelling of the heat shock response and the self-assembly of intermediate filaments

Systems biology is a new, emerging and rapidly developing, multidisciplinary research field that aims to study biochemical and biological systems from a holistic perspective, with the goal of providing a comprehensive, system- level understanding of cellular behaviour. In this way, it addresses one of the greatest challenges faced by contemporary biology, which is to compre- hend the function of complex biological systems. Systems biology combines various methods that originate from scientific disciplines such as molecu- lar biology, chemistry, engineering sciences, mathematics, computer science and systems theory. Systems biology, unlike “traditional” biology, focuses on high-level concepts such as: network, component, robustness, efficiency, control, regulation, hierarchical design, synchronization, concurrency, and many others. The very terminology of systems biology is “foreign” to “tra- ditional” biology, marks its drastic shift in the research paradigm and it indicates close linkage of systems biology to computer science. One of the basic tools utilized in systems biology is the mathematical modelling of life processes tightly linked to experimental practice. The stud- ies contained in this thesis revolve around a number of challenges commonly encountered in the computational modelling in systems biology. The re- search comprises of the development and application of a broad range of methods originating in the fields of computer science and mathematics for construction and analysis of computational models in systems biology. In particular, the performed research is setup in the context of two biolog- ical phenomena chosen as modelling case studies: 1) the eukaryotic heat shock response and 2) the in vitro self-assembly of intermediate filaments, one of the main constituents of the cytoskeleton. The range of presented approaches spans from heuristic, through numerical and statistical to ana- lytical methods applied in the effort to formally describe and analyse the two biological processes. We notice however, that although applied to cer- tain case studies, the presented methods are not limited to them and can be utilized in the analysis of other biological mechanisms as well as com- plex systems in general. The full range of developed and applied modelling techniques as well as model analysis methodologies constitutes a rich mod- elling framework. Moreover, the presentation of the developed methods, their application to the two case studies and the discussions concerning their potentials and limitations point to the difficulties and challenges one encounters in computational modelling of biological systems. The problems of model identifiability, model comparison, model refinement, model inte- gration and extension, choice of the proper modelling framework and level of abstraction, or the choice of the proper scope of the model run through this thesis.