The impact of a new partnership outsourcing arrangement: a routine-based case study in detail engineering

This thesis investigated the contemporary phenomenon of detail engineering outsourcing. The case organization had pursued a new outsourcing approach with a trusted partner. The goal of this empirical study was to examine the impact of the consequential partnership outsourcing arrangement. Particularly, the beneficence of the arrangement was evaluated based on the underlying organizational routine and the long-term economic implications of its performance outcome. The case study was needed, as the unit will likely have to rely on such distance outsourcing arrangements more and more in the future, and understanding on the impact of such operations is needed. The main findings revealed that the new outsourcing arrangement is not currently a very attractive strategic option for organizing production. The benefits which stem from the emerged, unique engineering project routine are not significant enough to make the arrangement an advantageous one, especially since increasing partnering costs are being met. This conclusion was drawn via the extended transaction cost view. Benchmarking was done in reliance to an old arrangement from which the new pursuit was a departure from. The case study then enlightened the engineering unit on the impact of its strategic maneuver by combining the routines-theory framework with contemporary methods of governance structure evaluation. Through this, it was shown that greater efforts are needed to make the new outsourcing approach a more beneficial one. However, the studied arrangement was seen to inhold potential for better results. The findings can be used to capitalize on this.

Using passive techniques for vibration damping in mechanical systems

This paper examines two passive techniques for vibration reduction in mechanical systems: the first one is based on dynamic vibration absorbers (DVAs) and the second uses resonant circuit shunted (RCS) piezoceramics. Genetic algorithms are used to determine the optimal design parameters with respect to performance indexes, which are associated with the dynamical behavior of the system over selected frequency bands. The calculation of the frequency response functions (FRFs) of the composite structure (primary system + DVAs) is performed through a substructure coupling technique. A modal technique is used to determine the frequency response function of the structure containing shunted piezoceramics which are bonded to the primary structure. The use of both techniques simultaneously on the same structure is investigated. The methodology developed is illustrated by numerical applications in which the primary structure is represented by simple Euler-Bernoulli beams. However, the design aspects of vibration control devices presented in this paper can be extended to more complex structures.

Experimental validation of a 3-D vision-based measurement system applied to robot calibration

One of the problems that slows the development of off-line programming is the low static and dynamic positioning accuracy of robots. Robot calibration improves the positioning accuracy and can also be used as a diagnostic tool in robot production and maintenance. A large number of robot measurement systems are now available commercially. Yet, there is a dearth of systems that are portable, accurate and low cost. In this work a measurement system that can fill this gap in local calibration is presented. The measurement system consists of a single CCD camera mounted on the robot tool flange with a wide angle lens, and uses space resection models to measure the end-effector pose relative to a world coordinate system, considering radial distortions. Scale factors and image center are obtained with innovative techniques, making use of a multiview approach. The target plate consists of a grid of white dots impressed on a black photographic paper, and mounted on the sides of a 90-degree angle plate. Results show that the achieved average accuracy varies from 0.2mm to 0.4mm, at distances from the target from 600mm to 1000mm respectively, with different camera orientations.

Manifestation of the pairing symmetry in the vortex core structure in iron-based superconductors

The superconducting gap is a basic character of a superconductor. While the cuprates and conventional phonon-mediated superconductors are characterized by distinct d- and s-wave pairing symmetries with nodal and nodeless gap distributions respectively, the superconducting gap distributions in iron-based superconductors are rather diversified. While nodeless gap distributions have been directly observed in Ba1–xKxFe2As2, BaFe2–xCoxAs2, LiFeAs, KxFe2–ySe2, and FeTe1–xSex, the signatures of a nodal superconducting gap have been reported in LaOFeP, LiFeP, FeSe, KFe2As2, BaFe2–xRuxAs2, and BaFe2(As1–xPx)2. Due to the multiplicity of the Fermi surface in these compounds s± and d pairing states can be both nodeless and nodal. A nontrivial orbital structure of the order parameter, in particular the presence of the gap nodes, leads to effects in which the disorder is much richer in dx2–y2-wave superconductors than in conventional materials. In contrast to the s-wave case, the Anderson theorem does not work, and nonmagnetic impurities exhibit a strong pair-breaking influence. In addition, a finite concentration of disorder produces a nonzero density of quasiparticle states at zero energy, which results in a considerable modification of the thermodynamic and transport properties at low temperatures. The influence of order parameter symmetry on the vortex core structure in iron-based pnictide and chalcogenide superconductors has been investigated in the framework of quasiclassical Eilenberger equations. The main results of the thesis are as follows. The vortex core characteristics, such as, cutoff parameter, ξh, and core size, ξ2, determined as the distance at which density of the vortex supercurrent reaches its maximum, are calculated in wide temperature, impurity scattering rate, and magnetic field ranges. The cutoff parameter, ξh(B; T; Г), determines the form factor of the flux-line lattice, which can be obtained in _SR, NMR, and SANS experiments. A comparison among the applied pairing symmetries is done. In contrast to s-wave systems, in dx2–y2-wave superconductors, ξh/ξc2 always increases with the scattering rate Г. Field dependence of the cutoff parameter affects strongly on the second moment of the magnetic field distributions, resulting in a significant difference with nonlocal London theory. It is found that normalized ξ2/ξc2(B/Bc2) dependence is increasing with pair-breaking impurity scattering (interband scattering for s±-wave and intraband impurity scattering for d-wave superconductors). Here, ξc2 is the Ginzburg-Landau coherence length determined from the upper critical field Bc2 = Φ0/2πξ2 c2, where Φ0 is a flux quantum. Two types of ξ2/ξc2 magnetic field dependences are obtained for s± superconductors. It has a minimum at low temperatures and small impurity scattering transforming in monotonously decreasing function at strong scattering and high temperatures. The second kind of this dependence has been also found for d-wave superconductors at intermediate and high temperatures. In contrast, impurity scattering results in decreasing of ξ2/ξc2(B/Bc2) dependence in s++ superconductors. A reasonable agreement between calculated ξh/ξc2 values and those obtained experimentally in nonstoichiometric BaFe2–xCoxAs2 (μSR) and stoichiometric LiFeAs (SANS) was found. The values of ξh/ξc2 are much less than one in case of the first compound and much more than one for the other compound. This is explained by different influence of two factors: the value of impurity scattering rate and pairing symmetry.

Geo-enabling repositories - techniques, tools, and challenges

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

A comparative analysis of preprocessing techniques of cardiac event series for the study of heart rhythm variability using simulated signals

In the present study, using noise-free simulated signals, we performed a comparative examination of several preprocessing techniques that are used to transform the cardiac event series in a regularly sampled time series, appropriate for spectral analysis of heart rhythm variability (HRV). First, a group of noise-free simulated point event series, which represents a time series of heartbeats, was generated by an integral pulse frequency modulation model. In order to evaluate the performance of the preprocessing methods, the differences between the spectra of the preprocessed simulated signals and the true spectrum (spectrum of the model input modulating signals) were surveyed by visual analysis and by contrasting merit indices. It is desired that estimated spectra match the true spectrum as close as possible, showing a minimum of harmonic components and other artifacts. The merit indices proposed to quantify these mismatches were the leakage rate, defined as a measure of leakage components (located outside some narrow windows centered at frequencies of model input modulating signals) with respect to the whole spectral components, and the numbers of leakage components with amplitudes greater than 1%, 5% and 10% of the total spectral components. Our data, obtained from a noise-free simulation, indicate that the utilization of heart rate values instead of heart period values in the derivation of signals representative of heart rhythm results in more accurate spectra. Furthermore, our data support the efficiency of the widely used preprocessing technique based on the convolution of inverse interval function values with a rectangular window, and suggest the preprocessing technique based on a cubic polynomial interpolation of inverse interval function values and succeeding spectral analysis as another efficient and fast method for the analysis of HRV signals

Algorithmic Techniques in Gene Expression Processing. From Imputation to Visualization

The amount of biological data has grown exponentially in recent decades. Modern biotechnologies, such as microarrays and next-generation sequencing, are capable to produce massive amounts of biomedical data in a single experiment. As the amount of the data is rapidly growing there is an urgent need for reliable computational methods for analyzing and visualizing it. This thesis addresses this need by studying how to efficiently and reliably analyze and visualize high-dimensional data, especially that obtained from gene expression microarray experiments. First, we will study the ways to improve the quality of microarray data by replacing (imputing) the missing data entries with the estimated values for these entries. Missing value imputation is a method which is commonly used to make the original incomplete data complete, thus making it easier to be analyzed with statistical and computational methods. Our novel approach was to use curated external biological information as a guide for the missing value imputation. Secondly, we studied the effect of missing value imputation on the downstream data analysis methods like clustering. We compared multiple recent imputation algorithms against 8 publicly available microarray data sets. It was observed that the missing value imputation indeed is a rational way to improve the quality of biological data. The research revealed differences between the clustering results obtained with different imputation methods. On most data sets, the simple and fast k-NN imputation was good enough, but there were also needs for more advanced imputation methods, such as Bayesian Principal Component Algorithm (BPCA). Finally, we studied the visualization of biological network data. Biological interaction networks are examples of the outcome of multiple biological experiments such as using the gene microarray techniques. Such networks are typically very large and highly connected, thus there is a need for fast algorithms for producing visually pleasant layouts. A computationally efficient way to produce layouts of large biological interaction networks was developed. The algorithm uses multilevel optimization within the regular force directed graph layout algorithm.

Minimizing Conducted RF-Emissions in Switch Mode Power Supplies Using Spread-Spectrum Techniques

Switching power supplies are usually implemented with a control circuitry that uses constant clock frequency turning the power semiconductor switches on and off. A drawback of this customary operating principle is that the switching frequency and harmonic frequencies are present in both the conducted and radiated EMI spectrum of the power converter. Various variable-frequency techniques have been introduced during the last decade to overcome the EMC problem. The main objective of this study was to compare the EMI and steady-state performance of a switch mode power supply with different spread-spectrum/variable-frequency methods. Another goal was to find out suitable tools for the variable-frequency EMI analysis. This thesis can be divided into three main parts: Firstly, some aspects of spectral estimation and measurement are presented. Secondly, selected spread spectrum generation techniques are presented with simulations and background information. Finally, simulations and prototype measurements from the EMC and the steady-state performance are carried out in the last part of this work. Combination of the autocorrelation function, the Welch spectrum estimate and the spectrogram were used as a substitute for ordinary Fourier methods in the EMC analysis. It was also shown that the switching function can be used in preliminary EMC analysis of a SMPS and the spectrum and autocorrelation sequence of a switching function correlates with the final EMI spectrum. This work is based on numerous simulations and measurements made with the prototype. All these simulations and measurements are made with the boost DC/DC converter. Four different variable-frequency modulation techniques in six different configurations were analyzed and the EMI performance was compared to the constant frequency operation. Output voltage and input current waveforms were also analyzed in time domain to see the effect of the spread spectrum operation on these quantities. According to the results presented in this work, spread spectrum modulation can be utilized in power converter for EMI mitigation. The results from steady-state voltage measurements show, that the variable-frequency operation of the SMPS has effect on the voltage ripple, but the ripple measured from the prototype is still acceptable in some applications. Both current and voltage ripple can be controlled with proper main circuit and controller design.

Graphene from Graphite by Chemical and Physical Techniques.

Graphene is a material with extraordinary properties. Its mechanical and electrical properties are unparalleled but the difficulties in its production are hindering its breakthrough in on applications. Graphene is a two-dimensional material made entirely of carbon atoms and it is only a single atom thick. In this work, properties of graphene and graphene based materials are described, together with their common preparation techniques and related challenges. This Thesis concentrates on the topdown techniques, in which natural graphite is used as a precursor for the graphene production. Graphite consists of graphene sheets, which are stacked together tightly. In the top-down techniques various physical or chemical routes are used to overcome the forces keeping the graphene sheets together, and many of them are described in the Thesis. The most common chemical method is the oxidisation of graphite with strong oxidants, which creates a water-soluble graphene oxide. The properties of graphene oxide differ significantly from pristine graphene and, therefore, graphene oxide is often reduced to form materials collectively known as reduced graphene oxide. In the experimental part, the main focus is on the chemical and electrochemical reduction of graphene oxide. A novel chemical route using vanadium is introduced and compared to other common chemical graphene oxide reduction methods. A strong emphasis is placed on electrochemical reduction of graphene oxide in various solvents. Raman and infrared spectroscopy are both used in in situ spectroelectrochemistry to closely monitor the spectral changes during the reduction process. These in situ techniques allow the precise control over the reduction process and even small changes in the material can be detected. Graphene and few layer graphene were also prepared using a physical force to separate these materials from graphite. Special adsorbate molecules in aqueous solutions, together with sonic treatment, produce stable dispersions of graphene and few layer graphene sheets in water. This mechanical exfoliation method damages the graphene sheets considerable less than the chemical methods, although it suffers from a lower yield.

PCR-based ribotyping of Staphylococcus aureus

Genotyping techniques are valuable tools for the epidemiologic study of Staphylococcus aureus infections in the hospital setting. Pulsed-field gel electrophoresis (PFGE) is the current method of choice for S. aureus strain typing. However, the method is laborious and requires expensive equipment. In the present study, we evaluated the natural polymorphism of the genomic 16S-23S rRNA region for genotyping purpose, by PCR-based ribotyping. Three primer pairs were tested to determine the size of amplicons produced and to obtain better discrimination with agar gel electrophoresis and ethidium bromide staining. The resolution of the typing system was determined using sets of bacteria obtained from clinical specimens from a large tertiary care hospital. These included DNA from three samples obtained from a bacteremic patient, six strains with known and diverse PGFE patterns, and 88 strains collected over a 3-month period in the same hospital. Amplification patterns obtained from samples from the same patient were identical, and PFGE from samples known to be different produced three genotypes. Amplification of DNA from 61 methicillin-resistant isolates produced only one pattern. Methicillin-sensitive strains yielded a diversity of patterns, pointing to a true polyclonal distribution throughout the hospital (22 unique patterns from 27 strains). Computer-based software can be used to differentiate among identifiable strains, given the low number of bands and good characterization of PCR products. PCR-based ribotyping can be a useful technique for genotyping methicillin-sensitive S. aureus strains, but is of limited value for methicillin-resistant strains.

Surface studies of limestones and dolostones : characterisation using various techniques and batch dissolution experiments with hydrochloric acid solutions

In this thesis, stepwise titration with hydrochloric acid was used to obtain chemical reactivities and dissolution rates of ground limestones and dolostones of varying geological backgrounds (sedimentary, metamorphic or magmatic). Two different ways of conducting the calculations were used: 1) a first order mathematical model was used to calculate extrapolated initial reactivities (and dissolution rates) at pH 4, and 2) a second order mathematical model was used to acquire integrated mean specific chemical reaction constants (and dissolution rates) at pH 5. The calculations of the reactivities and dissolution rates were based on rate of change of pH and particle size distributions of the sample powders obtained by laser diffraction. The initial dissolution rates at pH 4 were repeatedly higher than previously reported literature values, whereas the dissolution rates at pH 5 were consistent with former observations. Reactivities and dissolution rates varied substantially for dolostones, whereas for limestones and calcareous rocks, the variation can be primarily explained by relatively large sample standard deviations. A list of the dolostone samples in a decreasing order of initial reactivity at pH 4 is: 1) metamorphic dolostones with calcite/dolomite ratio higher than about 6% 2) sedimentary dolostones without calcite 3) metamorphic dolostones with calcite/dolomite ratio lower than about 6% The reactivities and dissolution rates were accompanied by a wide range of experimental techniques to characterise the samples, to reveal how different rocks changed during the dissolution process, and to find out which factors had an influence on their chemical reactivities. An emphasis was put on chemical and morphological changes taking place at the surfaces of the particles via X-ray Photoelectron Spectroscopy (XPS) and Scanning Electron Microscopy (SEM). Supporting chemical information was obtained with X-Ray Fluorescence (XRF) measurements of the samples, and Inductively Coupled Plasma-Mass Spectrometry (ICP-MS) and Inductively Coupled Plasma-Optical Emission Spectrometry (ICP-OES) measurements of the solutions used in the reactivity experiments. Information on mineral (modal) compositions and their occurrence was provided by X-Ray Diffraction (XRD), Energy Dispersive X-ray analysis (EDX) and studying thin sections with a petrographic microscope. BET (Brunauer, Emmet, Teller) surface areas were determined from nitrogen physisorption data. Factors increasing chemical reactivity of dolostones and calcareous rocks were found to be sedimentary origin, higher calcite concentration and smaller quartz concentration. Also, it is assumed that finer grain size and larger BET surface areas increase the reactivity although no certain correlation was found in this thesis. Atomic concentrations did not correlate with the reactivities. Sedimentary dolostones, unlike metamorphic ones, were found to have porous surface structures after dissolution. In addition, conventional (XPS) and synchrotron based (HRXPS) X-ray Photoelectron Spectroscopy were used to study bonding environments on calcite and dolomite surfaces. Both samples are insulators, which is why neutralisation measures such as electron flood gun and a conductive mask were used. Surface core level shifts of 0.7 ± 0.1 eV for Ca 2p spectrum of calcite and 0.75 ± 0.05 eV for Mg 2p and Ca 3s spectra of dolomite were obtained. Some satellite features of Ca 2p, C 1s and O 1s spectra have been suggested to be bulk plasmons. The origin of carbide bonds was suggested to be beam assisted interaction with hydrocarbons found on the surface. The results presented in this thesis are of particular importance for choosing raw materials for wet Flue Gas Desulphurisation (FGD) and construction industry. Wet FGD benefits from high reactivity, whereas construction industry can take advantage of slow reactivity of carbonate rocks often used in the facades of fine buildings. Information on chemical bonding environments may help to create more accurate models for water-rock interactions of carbonates.

Optimization and Measuring Techniques for Collect-and-Place Machines in Printed Circuit Board Industry

This thesis considers optimization problems arising in printed circuit board assembly. Especially, the case in which the electronic components of a single circuit board are placed using a single placement machine is studied. Although there is a large number of different placement machines, the use of collect-and-place -type gantry machines is discussed because of their flexibility and increasing popularity in the industry. Instead of solving the entire control optimization problem of a collect-andplace machine with a single application, the problem is divided into multiple subproblems because of its hard combinatorial nature. This dividing technique is called hierarchical decomposition. All the subproblems of the one PCB - one machine -context are described, classified and reviewed. The derived subproblems are then either solved with exact methods or new heuristic algorithms are developed and applied. The exact methods include, for example, a greedy algorithm and a solution based on dynamic programming. Some of the proposed heuristics contain constructive parts while others utilize local search or are based on frequency calculations. For the heuristics, it is made sure with comprehensive experimental tests that they are applicable and feasible. A number of quality functions will be proposed for evaluation and applied to the subproblems. In the experimental tests, artificially generated data from Markov-models and data from real-world PCB production are used. The thesis consists of an introduction and of five publications where the developed and used solution methods are described in their full detail. For all the problems stated in this thesis, the methods proposed are efficient enough to be used in the PCB assembly production in practice and are readily applicable in the PCB manufacturing industry.

Spatial modeling techniques for mapping and characterization of acid sulfate soils

Acid sulfate (a.s.) soils constitute a major environmental issue. Severe ecological damage results from the considerable amounts of acidity and metals leached by these soils in the recipient watercourses. As even small hot spots may affect large areas of coastal waters, mapping represents a fundamental step in the management and mitigation of a.s. soil environmental risks (i.e. to target strategic areas). Traditional mapping in the field is time-consuming and therefore expensive. Additional more cost-effective techniques have, thus, to be developed in order to narrow down and define in detail the areas of interest. The primary aim of this thesis was to assess different spatial modeling techniques for a.s. soil mapping, and the characterization of soil properties relevant for a.s. soil environmental risk management, using all available data: soil and water samples, as well as datalayers (e.g. geological and geophysical). Different spatial modeling techniques were applied at catchment or regional scale. Two artificial neural networks were assessed on the Sirppujoki River catchment (c. 440 km2) located in southwestern Finland, while fuzzy logic was assessed on several areas along the Finnish coast. Quaternary geology, aerogeophysics and slope data (derived from a digital elevation model) were utilized as evidential datalayers. The methods also required the use of point datasets (i.e. soil profiles corresponding to known a.s. or non-a.s. soil occurrences) for training and/or validation within the modeling processes. Applying these methods, various maps were generated: probability maps for a.s. soil occurrence, as well as predictive maps for different soil properties (sulfur content, organic matter content and critical sulfide depth). The two assessed artificial neural networks (ANNs) demonstrated good classification abilities for a.s. soil probability mapping at catchment scale. Slightly better results were achieved using a Radial Basis Function (RBF) -based ANN than a Radial Basis Functional Link Net (RBFLN) method, narrowing down more accurately the most probable areas for a.s. soil occurrence and defining more properly the least probable areas. The RBF-based ANN also demonstrated promising results for the characterization of different soil properties in the most probable a.s. soil areas at catchment scale. Since a.s. soil areas constitute highly productive lands for agricultural purpose, the combination of a probability map with more specific soil property predictive maps offers a valuable toolset to more precisely target strategic areas for subsequent environmental risk management. Notably, the use of laser scanning (i.e. Light Detection And Ranging, LiDAR) data enabled a more precise definition of a.s. soil probability areas, as well as the soil property modeling classes for sulfur content and the critical sulfide depth. Given suitable training/validation points, ANNs can be trained to yield a more precise modeling of the occurrence of a.s. soils and their properties. By contrast, fuzzy logic represents a simple, fast and objective alternative to carry out preliminary surveys, at catchment or regional scale, in areas offering a limited amount of data. This method enables delimiting and prioritizing the most probable areas for a.s soil occurrence, which can be particularly useful in the field. Being easily transferable from area to area, fuzzy logic modeling can be carried out at regional scale. Mapping at this scale would be extremely time-consuming through manual assessment. The use of spatial modeling techniques enables the creation of valid and comparable maps, which represents an important development within the a.s. soil mapping process. The a.s. soil mapping was also assessed using water chemistry data for 24 different catchments along the Finnish coast (in all, covering c. 21,300 km2) which were mapped with different methods (i.e. conventional mapping, fuzzy logic and an artificial neural network). Two a.s. soil related indicators measured in the river water (sulfate content and sulfate/chloride ratio) were compared to the extent of the most probable areas for a.s. soils in the surveyed catchments. High sulfate contents and sulfate/chloride ratios measured in most of the rivers demonstrated the presence of a.s. soils in the corresponding catchments. The calculated extent of the most probable a.s. soil areas is supported by independent data on water chemistry, suggesting that the a.s. soil probability maps created with different methods are reliable and comparable.

Novel virtual environment and real-time simulation based methods for improving life-cycle efficiency of non-road mobile machinery

Virtual environments and real-time simulators (VERS) are becoming more and more important tools in research and development (R&D) process of non-road mobile machinery (NRMM). The virtual prototyping techniques enable faster and more cost-efficient development of machines compared to use of real life prototypes. High energy efficiency has become an important topic in the world of NRMM because of environmental and economic demands. The objective of this thesis is to develop VERS based methods for research and development of NRMM. A process using VERS for assessing effects of human operators on the life-cycle efficiency of NRMM was developed. Human in the loop simulations are ran using an underground mining loader to study the developed process. The simulations were ran in the virtual environment of the Laboratory of Intelligent Machines of Lappeenranta University of Technology. A physically adequate real-time simulation model of NRMM was shown to be reliable and cost effective in testing of hardware components by the means of hardware-in-the-loop (HIL) simulations. A control interface connecting integrated electro-hydraulic energy converter (IEHEC) with virtual simulation model of log crane was developed. IEHEC consists of a hydraulic pump-motor and an integrated electrical permanent magnet synchronous motorgenerator. The results show that state of the art real-time NRMM simulators are capable to solve factors related to energy consumption and productivity of the NRMM. A significant variation between the test drivers is found. The results show that VERS can be used for assessing human effects on the life-cycle efficiency of NRMM. HIL simulation responses compared to that achieved with conventional simulation method demonstrate the advances and drawbacks of various possible interfaces between the simulator and hardware part of the system under study. Novel ideas for arranging the interface are successfully tested and compared with the more traditional one. The proposed process for assessing the effects of operators on the life-cycle efficiency will be applied for wider group of operators in the future. Driving styles of the operators can be analysed statistically from sufficient large result data. The statistical analysis can find the most life-cycle efficient driving style for the specific environment and machinery. The proposed control interface for HIL simulation need to be further studied. The robustness and the adaptation of the interface in different situations must be verified. The future work will also include studying the suitability of the IEHEC for different working machines using the proposed HIL simulation method.