Control of Structures with Cubic and Quadratic Non-Linearities with Time Delay Consideration

This paper studies the effect of time delay on the active non-linear control of dynamically loaded flexible structures. The behavior of non-linear systems under state feedback control, considering a fixed time delay for the control force, is investigated. A control method based on non-linear optimal control, using a tensorial formulation and state feedback control is used. The state equations and the control forces are expressed in polynomial form and a performance index, quadratic in both state vector and control forces, is used. General polynomial representations of the non-linear control law are obtained and implemented for control algorithms up to the fifth order. This methodology is applied to systems with quadratic and cubic non-linearities. Strongly non-linear systems are tested and the effectiveness of the control system including a delay for the application of control forces is discussed. Numerical results indicate that the adopted control algorithm can be efficient for non-linear systems, chiefly in the presence of strong non-linearities but increasing time delay reduces the efficiency of the control system. Numerical results emphasize the importance of considering time delay in the project of active structural control systems.

Energy-efficient control strategies for variable speed driven parallel pumping systems based on pump operation point monitoring with frequency converters

The pumping processes requiring wide range of flow are often equipped with parallelconnected centrifugal pumps. In parallel pumping systems, the use of variable speed control allows that the required output for the process can be delivered with a varying number of operated pump units and selected rotational speed references. However, the optimization of the parallel-connected rotational speed controlled pump units often requires adaptive modelling of both parallel pump characteristics and the surrounding system in varying operation conditions. The available information required for the system modelling in typical parallel pumping applications such as waste water treatment and various cooling and water delivery pumping tasks can be limited, and the lack of real-time operation point monitoring often sets limits for accurate energy efficiency optimization. Hence, alternatives for easily implementable control strategies which can be adopted with minimum system data are necessary. This doctoral thesis concentrates on the methods that allow the energy efficient use of variable speed controlled parallel pumps in system scenarios in which the parallel pump units consist of a centrifugal pump, an electric motor, and a frequency converter. Firstly, the suitable operation conditions for variable speed controlled parallel pumps are studied. Secondly, methods for determining the output of each parallel pump unit using characteristic curve-based operation point estimation with frequency converter are discussed. Thirdly, the implementation of the control strategy based on real-time pump operation point estimation and sub-optimization of each parallel pump unit is studied. The findings of the thesis support the idea that the energy efficiency of the pumping can be increased without the installation of new, more efficient components in the systems by simply adopting suitable control strategies. An easily implementable and adaptive control strategy for variable speed controlled parallel pumping systems can be created by utilizing the pump operation point estimation available in modern frequency converters. Hence, additional real-time flow metering, start-up measurements, and detailed system model are unnecessary, and the pumping task can be fulfilled by determining a speed reference for each parallel-pump unit which suggests the energy efficient operation of the pumping system.

Ensuring the efficient utilization of Business Intelligence

In recent years, chief information officers (CIOs) around the world have identified Business Intelligence (BI) as their top priority and as the best way to enhance their enterprises competitiveness. Yet, many enterprises are struggling to realize the business value that BI promises. This discrepancy causes important questions, for example: what are the critical success factors of Business Intelligence and, more importantly, how it can be ensured that a Business Intelligence program enhances enterprises competitiveness. The main objective of the study is to find out how it can be ensured that a BI program meets its goals in providing competitive advantage to an enterprise. The objective is approached with a literature review and a qualitative case study. For the literature review the main objective populates three research questions (RQs); RQ1: What is Business Intelligence and why is it important for modern enterprises? RQ2: What are the critical success factors of Business Intelligence programs? RQ3: How it can be ensured that CSFs are met? The qualitative case study covers the BI program of a Finnish global manufacturer company. The research questions for the case study are as follows; RQ4: What is the current state of the case company’s BI program and what are the key areas for improvement? RQ5: In what ways the case company’s Business Intelligence program could be improved? The case company’s BI program is researched using the following methods; action research, semi-structured interviews, maturity assessment and benchmarking. The literature review shows that Business Intelligence is a technology-based information process that contains a series of systematic activities, which are driven by the specific information needs of decision-makers. The objective of BI is to provide accurate, timely, fact-based information, which enables taking actions that lead to achieving competitive advantage. There are many reasons for the importance of Business Intelligence, two of the most important being; 1) It helps to bridge the gap between an enterprise’s current and its desired performance, and 2) It helps enterprises to be in alignment with key performance indicators meaning it helps an enterprise to align towards its key objectives. The literature review also shows that there are known critical success factors (CSFs) for Business Intelligence programs which have to be met if the above mentioned value is wanted to be achieved, for example; committed management support and sponsorship, business-driven development approach and sustainable data quality. The literature review shows that the most common challenges are related to these CSFs and, more importantly, that overcoming these challenges requires a more comprehensive form of BI, called Enterprise Performance Management (EPM). EPM links measurement to strategy by focusing on what is measured and why. The case study shows that many of the challenges faced in the case company’s BI program are related to the above-mentioned CSFs. The main challenges are; lack of support and sponsorship from business, lack of visibility to overall business performance, lack of rigid BI development process, lack of clear purpose for the BI program and poor data quality. To overcome these challenges the case company should define and design an enterprise metrics framework, make sure that BI development requirements are gathered and prioritized by business, focus on data quality and ownership, and finally define clear goals for the BI program and then support and sponsor these goals.

Thermal-Aware Networked Many-Core Systems

Advancements in IC processing technology has led to the innovation and growth happening in the consumer electronics sector and the evolution of the IT infrastructure supporting this exponential growth. One of the most difficult obstacles to this growth is the removal of large amount of heatgenerated by the processing and communicating nodes on the system. The scaling down of technology and the increase in power density is posing a direct and consequential effect on the rise in temperature. This has resulted in the increase in cooling budgets, and affects both the life-time reliability and performance of the system. Hence, reducing on-chip temperatures has become a major design concern for modern microprocessors. This dissertation addresses the thermal challenges at different levels for both 2D planer and 3D stacked systems. It proposes a self-timed thermal monitoring strategy based on the liberal use of on-chip thermal sensors. This makes use of noise variation tolerant and leakage current based thermal sensing for monitoring purposes. In order to study thermal management issues from early design stages, accurate thermal modeling and analysis at design time is essential. In this regard, spatial temperature profile of the global Cu nanowire for on-chip interconnects has been analyzed. It presents a 3D thermal model of a multicore system in order to investigate the effects of hotspots and the placement of silicon die layers, on the thermal performance of a modern ip-chip package. For a 3D stacked system, the primary design goal is to maximise the performance within the given power and thermal envelopes. Hence, a thermally efficient routing strategy for 3D NoC-Bus hybrid architectures has been proposed to mitigate on-chip temperatures by herding most of the switching activity to the die which is closer to heat sink. Finally, an exploration of various thermal-aware placement approaches for both the 2D and 3D stacked systems has been presented. Various thermal models have been developed and thermal control metrics have been extracted. An efficient thermal-aware application mapping algorithm for a 2D NoC has been presented. It has been shown that the proposed mapping algorithm reduces the effective area reeling under high temperatures when compared to the state of the art.

Comparison between dSPACE and NI systems based on real-time intelligent control of a teleoperated hydraulic servo system

The Laboratory of Intelligent Machine researches and develops energy-efficient power transmissions and automation for mobile construction machines and industrial processes. The laboratory's particular areas of expertise include mechatronic machine design using virtual technologies and simulators and demanding industrial robotics. The laboratory has collaborated extensively with industrial actors and it has participated in significant international research projects, particularly in the field of robotics. For years, dSPACE tools were the lonely hardware which was used in the lab to develop different control algorithms in real-time. dSPACE's hardware systems are in widespread use in the automotive industry and are also employed in drives, aerospace, and industrial automation. But new competitors are developing new sophisticated systems and their features convinced the laboratory to test new products. One of these competitors is National Instrument (NI). In order to get to know the specifications and capabilities of NI tools, an agreement was made to test a NI evolutionary system. This system is used to control a 1-D hydraulic slider. The objective of this research project is to develop a control scheme for the teleoperation of a hydraulically driven manipulator, and to implement a control algorithm between human and machine interaction, and machine and task environment interaction both on NI and dSPACE systems simultaneously and to compare the results.

Wind Turbine Direct-Drive Permanent-Magnet Generator with Direct Liquid Cooling for Mass Reduction

Today’s electrical machine technology allows increasing the wind turbine output power by an order of magnitude from the technology that existed only ten years ago. However, it is sometimes argued that high-power direct-drive wind turbine generators will prove to be of limited practical importance because of their relatively large size and weight. The limited space for the generator in a wind turbine application together with the growing use of wind energy pose a challenge for the design engineers who are trying to increase torque without making the generator larger. When it comes to high torque density, the limiting factor in every electrical machine is heat, and if the electrical machine parts exceed their maximum allowable continuous operating temperature, even for a short time, they can suffer permanent damage. Therefore, highly efficient thermal design or cooling methods is needed. One of the promising solutions to enhance heat transfer performances of high-power, low-speed electrical machines is the direct cooling of the windings. This doctoral dissertation proposes a rotor-surface-magnet synchronous generator with a fractional slot nonoverlapping stator winding made of hollow conductors, through which liquid coolant can be passed directly during the application of current in order to increase the convective heat transfer capabilities and reduce the generator mass. This doctoral dissertation focuses on the electromagnetic design of a liquid-cooled direct-drive permanent-magnet synchronous generator (LC DD-PMSG) for a directdrive wind turbine application. The analytical calculation of the magnetic field distribution is carried out with the ambition of fast and accurate predicting of the main dimensions of the machine and especially the thickness of the permanent magnets; the generator electromagnetic parameters as well as the design optimization. The focus is on the generator design with a fractional slot non-overlapping winding placed into open stator slots. This is an a priori selection to guarantee easy manufacturing of the LC winding. A thermal analysis of the LC DD-PMSG based on a lumped parameter thermal model takes place with the ambition of evaluating the generator thermal performance. The thermal model was adapted to take into account the uneven copper loss distribution resulting from the skin effect as well as the effect of temperature on the copper winding resistance and the thermophysical properties of the coolant. The developed lumpedparameter thermal model and the analytical calculation of the magnetic field distribution can both be integrated with the presented algorithm to optimize an LC DD-PMSG design. Based on an instrumented small prototype with liquid-cooled tooth-coils, the following targets have been achieved: experimental determination of the performance of the direct liquid cooling of the stator winding and validating the temperatures predicted by an analytical thermal model; proving the feasibility of manufacturing the liquid-cooled tooth-coil winding; moreover, demonstration of the objectives of the project to potential customers.

Cost-efficient virtual machine management : provisioning, admission control, and consolidation

One of the main challenges in Software Engineering is to cope with the transition from an industry based on software as a product to software as a service. The field of Software Engineering should provide the necessary methods and tools to develop and deploy new cost-efficient and scalable digital services. In this thesis, we focus on deployment platforms to ensure cost-efficient scalability of multi-tier web applications and on-demand video transcoding service for different types of load conditions. Infrastructure as a Service (IaaS) clouds provide Virtual Machines (VMs) under the pay-per-use business model. Dynamically provisioning VMs on demand allows service providers to cope with fluctuations on the number of service users. However, VM provisioning must be done carefully, because over-provisioning results in an increased operational cost, while underprovisioning leads to a subpar service. Therefore, our main focus in this thesis is on cost-efficient VM provisioning for multi-tier web applications and on-demand video transcoding. Moreover, to prevent provisioned VMs from becoming overloaded, we augment VM provisioning with an admission control mechanism. Similarly, to ensure efficient use of provisioned VMs, web applications on the under-utilized VMs are consolidated periodically. Thus, the main problem that we address is cost-efficient VM provisioning augmented with server consolidation and admission control on the provisioned VMs. We seek solutions for two types of applications: multi-tier web applications that follow the request-response paradigm and on-demand video transcoding that is based on video streams with soft realtime constraints. Our first contribution is a cost-efficient VM provisioning approach for multi-tier web applications. The proposed approach comprises two subapproaches: a reactive VM provisioning approach called ARVUE and a hybrid reactive-proactive VM provisioning approach called Cost-efficient Resource Allocation for Multiple web applications with Proactive scaling. Our second contribution is a prediction-based VM provisioning approach for on-demand video transcoding in the cloud. Moreover, to prevent virtualized servers from becoming overloaded, the proposed VM provisioning approaches are augmented with admission control approaches. Therefore, our third contribution is a session-based admission control approach for multi-tier web applications called adaptive Admission Control for Virtualized Application Servers. Similarly, the fourth contribution in this thesis is a stream-based admission control and scheduling approach for on-demand video transcoding called Stream-Based Admission Control and Scheduling. Our fifth contribution is a computation and storage trade-o strategy for cost-efficient video transcoding in cloud computing. Finally, the sixth and the last contribution is a web application consolidation approach, which uses Ant Colony System to minimize the under-utilization of the virtualized application servers.

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.

Efficient retrovirus-mediated transfer of cell-cycle control genes to transformed cells

The use of gene therapy continues to be a promising, yet elusive, alternative for the treatment of cancer. The origins of cancer must be well understood so that the therapeutic gene can be chosen with the highest chance of successful tumor regression. The gene delivery system must be tailored for optimum transfer of the therapeutic gene to the target tissue. In order to accomplish this, we study models of G1 cell-cycle control in both normal and transformed cells in order to understand the reasons for uncontrolled cellular proliferation. We then use this information to choose the gene to be delivered to the cells. We have chosen to study p16, p21, p53 and pRb gene transfer using the pCL-retrovirus. Described here are some general concepts and specific results of our work that indicate continued hope for the development of genetically based cancer treatments.

Antigenic stimulation is more efficient than LPS in inducing nitric oxide production by human mononuclear cells on the in vitro granuloma reaction in schistosomiasis

Nitric oxide (NO) is an extremely important and versatile messenger in biological systems. It has been identified as a cytotoxic factor in the immune system, presenting anti- or pro-inflammatory properties under different circumstances. In murine monocytes and macrophages, stimuli by cytokines or lipopolysaccharide (LPS) are necessary for inducing the immunologic isoform of the enzyme responsible for the high-output production of NO, nitric oxide synthase (iNOS). With respect to human cells, however, LPS seems not to stimulate NO production in the same way. Addressing this issue, we demonstrate here that peripheral blood mononuclear cells (PBMC) obtained from schistosomiasis-infected patients and cultivated with parasite antigens in the in vitro granuloma (IVG) reaction produced more nitrite in the absence of LPS. Thus, LPS-induced nitrite levels are easily detectable, although lower than those detected only with antigenic stimulation. Concomitant addition of LPS and L-N-arginine methyl ester (L-NAME) restored the ability to produce detectable levels of nitrite, which had been lost with L-NAME treatment. In addition, LPS caused a mild decrease of the IVG reaction and its association with L-NAME was responsible for reversal of the L-NAME-exacerbating effect on the IVG reaction. These results show that LPS alone is not as good an NO inducer in human cells as it is in rodent cells or cell lines. Moreover, they provide evidence for interactions between LPS and NO inhibitors that require further investigation.

New families of highly efficient, halogen-free flame retardants for polypropylene (PP)

The driving forces for current research of flame retardants are increased fire safety in combination with flame retardant formulations that fulfill the criteria of sustainable production and products. In recent years, important questions about the environmental safety of antimony, and in particular, brominated flame retardants have been raised. As a consequence of this, the current doctoral thesis work describes efforts to develop new halogen-free flame retardants that are based on various radical generators and phosphorous compounds. The investigation was first focused on compounds that are capable of generating alkyl radicals in order to study their role on flame retardancy of polypropylene. The family of azoalkanes was selected as the cleanest and most convenient source of free alkyl radicals. Therefore, a number of symmetrical and unsymmetrical azoalkanes of the general formula R-N=N-R’ were prepared. The experimental results show that in the series of different sized azocycloalkanes the flame retardant efficacy decreased in the following order: R = R´= cyclohexyl > cyclopentyl > cyclobutyl > cyclooctanyl > cyclododecanyl. However, in the series of aliphatic azoalkanes compounds, the efficacy decreased as followed: R = R´= n-alkyl > tert-butyl > tert-octyl. The most striking difference in flame retardant efficacy was observed in thick polypropylene plaques of 1 mm, e.g. azocyclohexane (AZO) had a much better flame retardant performance than did the commercial reference FR (Flamestab® NOR116) in thick PP sections. In addition, some of the prepared azoalkane flame retardants e.g. 4’4- bis(cyclohexylazocyclohexyl) methane (BISAZO) exhibited non-burning dripping behavior. Extrusion coating experiments of flame retarded low density polyethylene (LDPE) onto a standard machine finished Kraft paper were carried out in order to investigate the potential of azoalkanes in multilayer facings. The results show that azocyclohexane (AZO) and 4’4-bis (cyclohexylazocyclohexyl) methane (BISAZO) can significantly improve the flame retardant properties of low density polyethylene coated paper already at 0.5 wt.% loadings, provided that the maximum extrusion temperature of 260 oC is not exceeded and coating weight is kept low at 13 g/m2. In addition, various triazene-based flame retardants (RN1=N2-N3R’R’’) were prepared. For example, polypropylene samples containing a very low concentration of only 0.5 wt.% of bis- 4’4’-(3’3’-dimethyltriazene) diphenyl ether and other triazenes passed the DIN 4102-1 test with B2 classification. It is noteworthy that no burning dripping could be detected and the average burning times were very short with exceptionally low weight losses. Therefore, triazene compounds constitute a new and interesting family of radical generators for flame retarding of polymeric materials. The high flame retardant potential of triazenes can be attributed to their ability to generate various types of radicals during their thermal decomposition. According to thermogravimetric analysis/Fourier transform infrared spectroscopy/MS analysis, triazene units are homolytically cleaved into various aminyl, resonance-stabilized aryl radicals, and different CH fragments with simultaneous evolution of elemental nitrogen. Furthermore, the potential of thirteen aliphatic, aromatic, thiuram and heterocyclic substituted organic disulfide derivatives of the general formula R-S-S-R’ as a new group of halogen-free flame retardants for polypropylene films have been investigated. According to the DIN 4102- 1 standard ignitibility test, for the first time it has been demonstrated that many of the disulfides alone can effectively provide flame retardancy and self-extinguishing properties to polypropylene films at already very low concentrations of 0.5 wt.%. For the disulfide family, the highest FR activity was recorded for 5’5’-dithiobis (2-nitrobenzoic acid). Very low values for burning length (53 mm) and burning time (10 s) reflect significantly increased fire retardant performance of this disulfide compared to other compounds in this series as well as to Flamestab® NOR116. Finally, two new, phosphorus-based flame retardants were synthesized: P’P-diphenyl phosphinic hydrazide (PAH) and melamine phenyl phosphonate (MPhP). The DIN 4102-1 test and the more stringent UL94 vertical burning test (UL94 V) were used to assess the formulations ability to extinguish a flame once ignited. A very strong synergistic effect with azoalkanes was found, i.e. in combination with these radical generators even UL94 V0 rate could be obtained.

Efficient Optimization Algorithms for Nonlinear Data Analysis

Identification of low-dimensional structures and main sources of variation from multivariate data are fundamental tasks in data analysis. Many methods aimed at these tasks involve solution of an optimization problem. Thus, the objective of this thesis is to develop computationally efficient and theoretically justified methods for solving such problems. Most of the thesis is based on a statistical model, where ridges of the density estimated from the data are considered as relevant features. Finding ridges, that are generalized maxima, necessitates development of advanced optimization methods. An efficient and convergent trust region Newton method for projecting a point onto a ridge of the underlying density is developed for this purpose. The method is utilized in a differential equation-based approach for tracing ridges and computing projection coordinates along them. The density estimation is done nonparametrically by using Gaussian kernels. This allows application of ridge-based methods with only mild assumptions on the underlying structure of the data. The statistical model and the ridge finding methods are adapted to two different applications. The first one is extraction of curvilinear structures from noisy data mixed with background clutter. The second one is a novel nonlinear generalization of principal component analysis (PCA) and its extension to time series data. The methods have a wide range of potential applications, where most of the earlier approaches are inadequate. Examples include identification of faults from seismic data and identification of filaments from cosmological data. Applicability of the nonlinear PCA to climate analysis and reconstruction of periodic patterns from noisy time series data are also demonstrated. Other contributions of the thesis include development of an efficient semidefinite optimization method for embedding graphs into the Euclidean space. The method produces structure-preserving embeddings that maximize interpoint distances. It is primarily developed for dimensionality reduction, but has also potential applications in graph theory and various areas of physics, chemistry and engineering. Asymptotic behaviour of ridges and maxima of Gaussian kernel densities is also investigated when the kernel bandwidth approaches infinity. The results are applied to the nonlinear PCA and to finding significant maxima of such densities, which is a typical problem in visual object tracking.

Gliclazide and bedtime insulin are more efficient than insulin alone for type 2 diabetic patients with sulfonylurea secondary failure

To determine the effects of combined therapy of gliclazide and bedtime insulin on glycemic control and C-peptide secretion, we studied 25 patients with type 2 diabetes and sulfonylurea secondary failure, aged 56.8 ± 8.3 years, with a duration of diabetes of 10.6 ± 6.6 years, fasting plasma glucose of 277.3 ± 64.6 mg/dl and a body mass index of 27.4 ± 4.8 kg/m². Patients were submitted to three therapeutic regimens lasting 2 months each: 320 mg gliclazide (phase 1), 320 mg gliclazide and bedtime NPH insulin (phase 2), and insulin (phase 3). At the end of each period, glycemic and C-peptide curves in response to a mixed meal were determined. During combined therapy, there was a decrease in all glycemic curve values (P<0.01). Twelve patients (48%) reached fasting plasma glucose <140 mg/dl with a significant weight gain of 64.8 kg (43.1-98.8) vs 66.7 kg (42.8-101.4) (P<0.05), with no increase in C-peptide secretion or decrease in HbA1. C-Peptide glucose score (C-peptide/glucose x 100) increased from 0.9 (0.2-2.1) to 1.3 (0.2-4.7) during combined therapy (P<0.01). Despite a 50% increase in insulin doses in phase 3 (12 U (9-30) vs 18 U (11-60); P<0.01) only 3 patients who responded to combined therapy maintained fasting plasma glucose <140 mg/dl (P<0.02). A tendency to a higher absolute increase in C-peptide (0.99 (0.15-2.5) vs 0.6 (0-2.15); P = 0.08) and C-peptide incremental area (2.47 (0.22-6.2) vs 1.2 (0-3.35); P = 0.07) was observed among responders. We conclude that combined therapy resulted in a better glucose response to a mixed meal than insulin alone and should be tried in type 2 diabetic patients before starting insulin monotherapy, despite difficulties in predicting the response.

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.