Developing smart services by Internet of Things in manufacturing business

Manufacturing companies have passed from selling uniquely tangible products to adopting a service-oriented approach to generate steady and continuous revenue streams. Nowadays, equipment and machine manufacturers possess technologies to track and analyze product-related data for obtaining relevant information from customers’ use towards the product after it is sold. The Internet of Things on Industrial environments will allow manufacturers to leverage lifecycle product traceability for innovating towards an information-driven services approach, commonly referred as “Smart Services”, for achieving improvements in support, maintenance and usage processes. The aim of this study is to conduct a literature review and empirical analysis to present a framework that describes a customer-oriented approach for developing information-driven services leveraged by the Internet of Things in manufacturing companies. The empirical study employed tools for the assessment of customer needs for analyzing the case company in terms of information requirements and digital needs. The literature review supported the empirical analysis with a deep research on product lifecycle traceability and digitalization of product-related services within manufacturing value chains. As well as the role of simulation-based technologies on supporting the “Smart Service” development process. The results obtained from the case company analysis show that the customers mainly demand information that allow them to monitor machine conditions, machine behavior on different geographical conditions, machine-implement interactions, and resource and energy consumption. Put simply, information outputs that allow them to increase machine productivity for maximizing yields, save time and optimize resources in the most sustainable way. Based on customer needs assessment, this study presents a framework to describe the initial phases of a “Smart Service” development process, considering the requirements of Smart Engineering methodologies.

Numerical Simulation of Stochastic Di erential Equations

Stochastic differential equation (SDE) is a differential equation in which some of the terms and its solution are stochastic processes. SDEs play a central role in modeling physical systems like finance, Biology, Engineering, to mention some. In modeling process, the computation of the trajectories (sample paths) of solutions to SDEs is very important. However, the exact solution to a SDE is generally difficult to obtain due to non-differentiability character of realizations of the Brownian motion. There exist approximation methods of solutions of SDE. The solutions will be continuous stochastic processes that represent diffusive dynamics, a common modeling assumption for financial, Biology, physical, environmental systems. This Masters' thesis is an introduction and survey of numerical solution methods for stochastic differential equations. Standard numerical methods, local linearization methods and filtering methods are well described. We compute the root mean square errors for each method from which we propose a better numerical scheme. Stochastic differential equations can be formulated from a given ordinary differential equations. In this thesis, we describe two kind of formulations: parametric and non-parametric techniques. The formulation is based on epidemiological SEIR model. This methods have a tendency of increasing parameters in the constructed SDEs, hence, it requires more data. We compare the two techniques numerically.

Adaptive Markov chain Monte Carlo and Bayesian filtering for state space models

This thesis is concerned with the state and parameter estimation in state space models. The estimation of states and parameters is an important task when mathematical modeling is applied to many different application areas such as the global positioning systems, target tracking, navigation, brain imaging, spread of infectious diseases, biological processes, telecommunications, audio signal processing, stochastic optimal control, machine learning, and physical systems. In Bayesian settings, the estimation of states or parameters amounts to computation of the posterior probability density function. Except for a very restricted number of models, it is impossible to compute this density function in a closed form. Hence, we need approximation methods. A state estimation problem involves estimating the states (latent variables) that are not directly observed in the output of the system. In this thesis, we use the Kalman filter, extended Kalman filter, Gauss–Hermite filters, and particle filters to estimate the states based on available measurements. Among these filters, particle filters are numerical methods for approximating the filtering distributions of non-linear non-Gaussian state space models via Monte Carlo. The performance of a particle filter heavily depends on the chosen importance distribution. For instance, inappropriate choice of the importance distribution can lead to the failure of convergence of the particle filter algorithm. In this thesis, we analyze the theoretical Lᵖ particle filter convergence with general importance distributions, where p ≥2 is an integer. A parameter estimation problem is considered with inferring the model parameters from measurements. For high-dimensional complex models, estimation of parameters can be done by Markov chain Monte Carlo (MCMC) methods. In its operation, the MCMC method requires the unnormalized posterior distribution of the parameters and a proposal distribution. In this thesis, we show how the posterior density function of the parameters of a state space model can be computed by filtering based methods, where the states are integrated out. This type of computation is then applied to estimate parameters of stochastic differential equations. Furthermore, we compute the partial derivatives of the log-posterior density function and use the hybrid Monte Carlo and scaled conjugate gradient methods to infer the parameters of stochastic differential equations. The computational efficiency of MCMC methods is highly depend on the chosen proposal distribution. A commonly used proposal distribution is Gaussian. In this kind of proposal, the covariance matrix must be well tuned. To tune it, adaptive MCMC methods can be used. In this thesis, we propose a new way of updating the covariance matrix using the variational Bayesian adaptive Kalman filter algorithm.

On sliding mode control ofhydraulic servo systems and a manipulator

The aim of the study is to developa novel robust controller based on sliding mode control technique for the hydraulic servo system with flexible load and for a flexible manipulator with the lift and jib hydraulic actuators. For the purpose of general control design, a dynamic model is derived describing the principle physical behavior for both the hydraulic servo system and the flexible hydraulic manipulator. The mechanism of hydraulic servo systems is described by basic mathematical equations of fluid powersystems and the dynamics of flexible manipulator is modeled by the assumed modemethod. The controller is constructed so as to track desired trajectories in the presence of model imprecision. Experimental and simulation results demonstratethat sliding mode control has benefits which can be used to guarantee stabilityin uncertain systems and improve the system performance and load tolerance.

Physical layer development in third generation protocol software architecture

Diplomityön tavoitteena oli kehittää kolmannen sukupolven fyysistä protokollakerrosta matkapuhelimen ohjelmistoarkkitehtuurille. Kolmannen sukupolven matkapuhelinjärjestelmät ovat aikaisempia järjestelmiä monimutkaisempia. Ohjelmiston koon ja monimutkaisuuden sekä aikataulujen kiireellisyyden vuoksi on tullut tarve ottaa käyttöön formaaleja menetelmiä ohjelmiston kehitystyöhön. Formaalit kuvauskielet mahdollistavat tarkan, yksiselitteisen ja simuloitavissa olevan järjestelmäkuvauksen muodostamisen. Fyysinen protokollakerros tarjoaa tiedon siirtoa ylemmille protokollakerroksille. Tämän tiedonsiirron hallinta vaatii protokollakerrosten välistä viestinvälitystä. Formaaleja kuvauskieliä käyttämällä voidaan viestinvälityksen toteutusta automatisoida ja siinä tarvittavaa logiikkaa havainnollistaa. Työssä suunniteltiin, toteutettiin ja testattiin ylempien protokollakerrosten kanssa kommunikoivaa osaa fyysisestä protokollakerroksesta. Tuloksena saatiin solunvalintatoiminnallisuuden vaatiman kommunikoinnin ja tilakoneen toteutus ohjelmistoarkkitehtuurissa. Ohjelmistonkehityksen alkuvaiheiden havaittiin olevan fyysisen kerroksen suorituskyvyn kannalta merkittävässä asemassa, koska tällöin viestinvälityksen optimointi on helpointa. Formaalit kuvauskielet eivät ole sellaisenaan täysin soveltuvia tarkoin määritellyn ohjelmistoarkkitehtuurin osien kehitykseen.

Remote Condition Monitoring and Asset Management in Offshore Power Systems

Condition monitoring systems for physical assets are constantly becoming more and more common in the industrial sector. At the same time an increasing portion of asset monitoring systems are being remotely supported. As global competitors are actively developing solutions for condition monitoring and condition-based maintenance, which it enables, Wärtsilä too feels the pressure to provide customers with more sophisticated condition-based maintenance solutions. The main aim of this thesis study is to consider Wärtsilä remote condition monitoring solutions and how they relate to similar solutions from other suppliers and end customers’ needs, in the context of offshore assets. A theoretical study is also included in the thesis, where the concepts of condition monitoring, condition-based maintenance, maintenance management and physical asset management are introduced.

Physical Realization of an Optical Automatic Target Recognition System

In the modern warfare there is an active development of a new trend connected with a robotic warfare. One of the critical elements of robotics warfare systems is an automatic target recognition system, allowing to recognize objects, based on the data received from sensors. This work considers aspects of optical realization of such a system by means of NIR target scanning at fixed wavelengths. An algorithm was designed, an experimental setup was built and samples of various modern gear and apparel materials were tested. For pattern testing the samples of actively arm engaged armies camouflages were chosen. Tests were performed both in clear atmosphere and in the artificial extremely humid and hot atmosphere to simulate field conditions.

Design and Analysis of Forward Error Control Coding and Signaling for Guaranteeing QoS in Wireless Broadcast Systems

Broadcasting systems are networks where the transmission is received by several terminals. Generally broadcast receivers are passive devices in the network, meaning that they do not interact with the transmitter. Providing a certain Quality of Service (QoS) for the receivers in heterogeneous reception environment with no feedback is not an easy task. Forward error control coding can be used for protection against transmission errors to enhance the QoS for broadcast services. For good performance in terrestrial wireless networks, diversity should be utilized. The diversity is utilized by application of interleaving together with the forward error correction codes. In this dissertation the design and analysis of forward error control and control signalling for providing QoS in wireless broadcasting systems are studied. Control signaling is used in broadcasting networks to give the receiver necessary information on how to connect to the network itself and how to receive the services that are being transmitted. Usually control signalling is considered to be transmitted through a dedicated path in the systems. Therefore, the relationship of the signaling and service data paths should be considered early in the design phase. Modeling and simulations are used in the case studies of this dissertation to study this relationship. This dissertation begins with a survey on the broadcasting environment and mechanisms for providing QoS therein. Then case studies present analysis and design of such mechanisms in real systems. The mechanisms for providing QoS considering signaling and service data paths and their relationship at the DVB-H link layer are analyzed as the first case study. In particular the performance of different service data decoding mechanisms and optimal signaling transmission parameter selection are presented. The second case study investigates the design of signaling and service data paths for the more modern DVB-T2 physical layer. Furthermore, by comparing the performances of the signaling and service data paths by simulations, configuration guidelines for the DVB-T2 physical layer signaling are given. The presented guidelines can prove useful when configuring DVB-T2 transmission networks. Finally, recommendations for the design of data and signalling paths are given based on findings from the case studies. The requirements for the signaling design should be derived from the requirements for the main services. Generally, these requirements for signaling should be more demanding as the signaling is the enabler for service reception.

Modeling of electrolyte sorption – from phase equilibria to dynamic separation systems

In this thesis, general approach is devised to model electrolyte sorption from aqueous solutions on solid materials. Electrolyte sorption is often considered as unwanted phenomenon in ion exchange and its potential as an independent separation method has not been fully explored. The solid sorbents studied here are porous and non-porous organic or inorganic materials with or without specific functional groups attached on the solid matrix. Accordingly, the sorption mechanisms include physical adsorption, chemisorption on the functional groups and partition restricted by electrostatic or steric factors. The model is tested in four Cases Studies dealing with chelating adsorption of transition metal mixtures, physical adsorption of metal and metalloid complexes from chloride solutions, size exclusion of electrolytes in nano-porous materials and electrolyte exclusion of electrolyte/non-electrolyte mixtures. The model parameters are estimated using experimental data from equilibrium and batch kinetic measurements, and they are used to simulate actual single-column fixed-bed separations. Phase equilibrium between the solution and solid phases is described using thermodynamic Gibbs-Donnan model and various adsorption models depending on the properties of the sorbent. The 3-dimensional thermodynamic approach is used for volume sorption in gel-type ion exchangers and in nano-porous adsorbents, and satisfactory correlation is obtained provided that both mixing and exclusion effects are adequately taken into account. 2-Dimensional surface adsorption models are successfully applied to physical adsorption of complex species and to chelating adsorption of transition metal salts. In the latter case, comparison is also made with complex formation models. Results of the mass transport studies show that uptake rates even in a competitive high-affinity system can be described by constant diffusion coefficients, when the adsorbent structure and the phase equilibrium conditions are adequately included in the model. Furthermore, a simplified solution based on the linear driving force approximation and the shrinking-core model is developed for very non-linear adsorption systems. In each Case Study, the actual separation is carried out batch-wise in fixed-beds and the experimental data are simulated/correlated using the parameters derived from equilibrium and kinetic data. Good agreement between the calculated and experimental break-through curves is usually obtained indicating that the proposed approach is useful in systems, which at first sight are very different. For example, the important improvement in copper separation from concentrated zinc sulfate solution at elevated temperatures can be correctly predicted by the model. In some cases, however, re-adjustment of model parameters is needed due to e.g. high solution viscosity.

A cyber security architecture for military networks using a cognitive network approach

Cyber security is one of the main topics that are discussed around the world today. The threat is real, and it is unlikely to diminish. People, business, governments, and even armed forces are networked in a way or another. Thus, the cyber threat is also facing military networking. On the other hand, the concept of Network Centric Warfare sets high requirements for military tactical data communications and security. A challenging networking environment and cyber threats force us to consider new approaches to build security on the military communication systems. The purpose of this thesis is to develop a cyber security architecture for military networks, and to evaluate the designed architecture. The architecture is described as a technical functionality. As a new approach, the thesis introduces Cognitive Networks (CN) which are a theoretical concept to build more intelligent, dynamic and even secure communication networks. The cognitive networks are capable of observe the networking environment, make decisions for optimal performance and adapt its system parameter according to the decisions. As a result, the thesis presents a five-layer cyber security architecture that consists of security elements controlled by a cognitive process. The proposed architecture includes the infrastructure, services and application layers that are managed and controlled by the cognitive and management layers. The architecture defines the tasks of the security elements at a functional level without introducing any new protocols or algorithms. For evaluating two separated method were used. The first method is based on the SABSA framework that uses a layered approach to analyze overall security of an organization. The second method was a scenario based method in which a risk severity level is calculated. The evaluation results show that the proposed architecture fulfills the security requirements at least at a high level. However, the evaluation of the proposed architecture proved to be very challenging. Thus, the evaluation results must be considered very critically. The thesis proves the cognitive networks are a promising approach, and they provide lots of benefits when designing a cyber security architecture for the tactical military networks. However, many implementation problems exist, and several details must be considered and studied during the future work.

Project Management Tools in Agile Embedded Systems Development

Agile methods have become increasingly popular in the field of software engineering. While agile methods are now generally considered applicable to software projects of many different kinds, they have not been widely adopted in embedded systems development. This is partly due to the natural constraints that are present in embedded systems development (e.g. hardware–software interdependencies) that challenge the utilization of agile values, principles and practices. The research in agile embedded systems development has been very limited, and this thesis tackles an even less researched theme related to it: the suitability of different project management tools in agile embedded systems development. The thesis covers the basic aspects of many different agile tool types from physical tools, such as task boards and cards, to web-based agile tools that offer all-round solutions for application lifecycle management. In addition to these two extremities, there is also a wide range of lighter agile tools that focus on the core agile practices, such as backlog management. Also other non-agile tools, such as bug trackers, can be used to support agile development, for instance, with plug-ins. To investigate the special tool requirements in agile embedded development, the author observed tool related issues and solutions in a case study involving three different companies operating in the field of embedded systems development. All three companies had a distinct situation in the beginning of the case and thus the tool solutions varied from a backlog spreadsheet built from scratch to plug-in development for an already existing agile software tool. Detailed reports are presented of all three tool cases. Based on the knowledge gathered from agile tools and the case study experiences, it is concluded that there are tool related issues in the pilot phase, such as backlog management and user motivation. These can be overcome in various ways epending on the type of a team in question. Finally, five principles are formed to give guidelines for tool selection and usage in agile embedded systems development.

Influence of surface functionalization on the behavior of silica nanoparticles in biological systems

Personalized nanomedicine has been shown to provide advantages over traditional clinical imaging, diagnosis, and conventional medical treatment. Using nanoparticles can enhance and clarify the clinical targeting and imaging, and lead them exactly to the place in the body that is the goal of treatment. At the same time, one can reduce the side effects that usually occur in the parts of the body that are not targets for treatment. Nanoparticles are of a size that can penetrate into cells. Their surface functionalization offers a way to increase their sensitivity when detecting target molecules. In addition, it increases the potential for flexibility in particle design, their therapeutic function, and variation possibilities in diagnostics. Mesoporous nanoparticles of amorphous silica have attractive physical and chemical characteristics such as particle morphology, controllable pore size, and high surface area and pore volume. Additionally, the surface functionalization of silica nanoparticles is relatively straightforward, which enables optimization of the interaction between the particles and the biological system. The main goal of this study was to prepare traceable and targetable silica nanoparticles for medical applications with a special focus on particle dispersion stability, biocompatibility, and targeting capabilities. Nanoparticle properties are highly particle-size dependent and a good dispersion stability is a prerequisite for active therapeutic and diagnostic agents. In the study it was shown that traceable streptavidin-conjugated silica nanoparticles which exhibit a good dispersibility could be obtained by the suitable choice of a proper surface functionalization route. Theranostic nanoparticles should exhibit sufficient hydrolytic stability to effectively carry the medicine to the target cells after which they should disintegrate and dissolve. Furthermore, the surface groups should stay at the particle surface until the particle has been internalized by the cell in order to optimize cell specificity. Model particles with fluorescently-labeled regions were tested in vitro using light microscopy and image processing technology, which allowed a detailed study of the disintegration and dissolution process. The study showed that nanoparticles degrade more slowly outside, as compared to inside the cell. The main advantage of theranostic agents is their successful targeting in vitro and in vivo. Non-porous nanoparticles using monoclonal antibodies as guiding ligands were tested in vitro in order to follow their targeting ability and internalization. In addition to the targeting that was found successful, a specific internalization route for the particles could be detected. In the last part of the study, the objective was to clarify the feasibility of traceable mesoporous silica nanoparticles, loaded with a hydrophobic cancer drug, being applied for targeted drug delivery in vitro and in vivo. Particles were provided with a small molecular targeting ligand. In the study a significantly higher therapeutic effect could be achieved with nanoparticles compared to free drug. The nanoparticles were biocompatible and stayed in the tumor for a longer time than a free medicine did, before being eliminated by renal excretion. Overall, the results showed that mesoporous silica nanoparticles are biocompatible, biodegradable drug carriers and that cell specificity can be achieved both in vitro and in vivo.

Critical infrastructure protection against cyber threats

A postgraduate seminar series with a title Critical Infrastructure Protection against Cyber Threats held at the Department of Military Technology of the National Defence University in the fall of 2013 and 2014. This book is a collection of some of talks that were presented in the seminar. The papers address origin of critical infrastructure protection, wargaming cyberwar in critical infrastructure defence, cyber-target categorization, supervisory control and data acquisition systems vulnerabilities, electric power as critical infrastructure, improving situational awareness of critical infrastructure and trust based situation awareness in high security cloud environment. This set of papers tries to give some insight to current issues of the network-centric critical infrastructure protection. The seminar has always made a publication of the papers but this has been an internal publication of the Finnish Defence Forces and has not hindered publication of the papers in international conferences. Publication of these papers in peer reviewed conferences has indeed been always the goal of the seminar, since it teaches writing conference level papers. We still hope that an internal publication in the department series is useful to the Finnish Defence Forces by offering an easy access to these papers.

Development of Measurement Systems in Scientific Research: Case Study

In recent years, technological advancements in microelectronics and sensor technologies have revolutionized the field of electrical engineering. New manufacturing techniques have enabled a higher level of integration that has combined sensors and electronics into compact and inexpensive systems. Previously, the challenge in measurements was to understand the operation of the electronics and sensors, but this has now changed. Nowadays, the challenge in measurement instrumentation lies in mastering the whole system, not just the electronics. To address this issue, this doctoral dissertation studies whether it would be beneficial to consider a measurement system as a whole from the physical phenomena to the digital recording device, where each piece of the measurement system affects the system performance, rather than as a system consisting of small independent parts such as a sensor or an amplifier that could be designed separately. The objective of this doctoral dissertation is to describe in depth the development of the measurement system taking into account the challenges caused by the electrical and mechanical requirements and the measurement environment. The work is done as an empirical case study in two example applications that are both intended for scientific studies. The cases are a light sensitive biological sensor used in imaging and a gas electron multiplier detector for particle physics. The study showed that in these two cases there were a number of different parts of the measurement system that interacted with each other. Without considering these interactions, the reliability of the measurement may be compromised, which may lead to wrong conclusions about the measurement. For this reason it is beneficial to conceptualize the measurement system as a whole from the physical phenomena to the digital recording device where each piece of the measurement system affects the system performance. The results work as examples of how a measurement system can be successfully constructed to support a study of sensors and electronics.