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Wind energy conversion systems such as wind farms are growing in numbers and capacity all over the globe. The onshore wind energy generation sector witnessed an increase of approximately 144 TWh during 2020, with onshore wind farms capacity addition of 108 GW, which is twice as much as the added capacity during 2019 (IEA, 2021). This staggering increase in capacity imposes higher needs for improved methodologies and expertise, in measuring the performance of wind farms and improving it. Cold climate regions are known to have an appealing potential for attracting wind farms installation and investments. However, the weather conditions in the cold climate regions impose risks and challenges to the operation and maintenance of wind turbines, and to the workers at the wind farms. Another challenge prevails in the lack of data and expertise related to wind energy projects in cold climate regions, due to the fact that wind farms instalments are relatively new in these regions. In addition, parts of the cold climate regions, such as the Arctic region, are known for their sensitive environment, and industrial projects could impact that sensitivity. The risks and challenges discussed in this thesis can be classified in different ways, there are risks that are induced by the weather conditions that affect the operation and performance of wind turbines, such as the reliability, availability and maintainability of the wind turbines, and there are the risks that are induced by the wind farms that will affect the societal, the economic, and the environmental status of the surroundings of the wind farms. This thesis introduces applicable methodologies that can be used to measure performance-related aspects of wind farms in cold climate regions, on different levels and operating under different scenarios. Moreover, in a performance-related context, a methodology for measuring the resilience of wind farms facing disruptive events is introduced, and lastly the different risks related to the operation of wind farms in cold climate regions are identified and analyzed through a methodology that allows for proper ranking of risks to prioritize the measures that can be used to mitigate those risks.

Vehicle crashworthiness assessment is critical to help reduce road accident fatalities and ensure safer vehicles for road users. Techniques to assess crashworthiness include physical tests and mathematical modeling and simulation of crash events, the latter is preferred as mathematical modeling is generally cheaper to perform in comparison with physical testing. The most common mathematical modeling technique used for crashworthiness assessment is nonlinear Finite Element (FE) modeling. However, a problem with the use of Finite Element Model (FEM) for crashworthiness assessment is inaccessibility to individual researchers, public bodies, small universities and engineering companies due to need for detailed CAD data, software licence costs along with high computational demands. This thesis investigates modeling strategies which are affordable, computationally and labour inexpensive, and could be used by the above-mentioned groups. Use of Lumped Parameter Models (LPM) capable of capturing vehicle parameters contributing to vehicle crashworthiness has been proposed as an alternative to adopting FEM, while the later have been used to validate LPMs developed in this thesis. The main crash scenario analysed is a full frontal impact against a rigid barrier. Front-end deformation which can be used to measure crash energy absorption and pitching which could lead to occupant injuries in a frontal crash event are parameters focused on. The thesis investigates two types of vehicles; vehicle with initial structure intact is defined as baseline vehicle, while a vehicle that underwent unprofessional repairs on its structural members made of Ultra High Strength Steel (UHSS) is defined as a modified vehicle. The proposed novel LPM for a baseline vehicle impact is inspired by pendulum motion and expresses the system using Lagrangian formulation to predict the two phases of impact: front-end deformation and vehicle pitching. Changes in crashworthiness performance of a modified vehicle were investigated with a FEM; tensile tests on UHSS coupons were conducted to generate material inputs for this FEM. Further, a full scale crash test was conducted to validate the FE simulations. An LPM to conduct crashworthiness assessment of a modified vehicle has been proposed, it is based on a double pendulum with a torsional spring representing the vehicle undergoing a full frontal impact.

This paper presents a robust model-based technique to detect multiple faults in permanent magnet synchronous motors (PMSMs), namely inter-turn short circuit (ITSC) and encoder faults. The proposed model is based on a structural analysis, which uses the dynamic mathematical model of a PMSM in an abc frame to evaluate the system’s structural model in matrix form. The just-determined and over-determined parts of the system are separated by a Dulmage–Mendelsohn decomposition tool. Subsequently, the analytical redundant relations obtained using the over-determined part of the system are used to form smaller redundant testable sub-models based on the number of defined fault terms. Furthermore, four structured residuals are designed based on the acquired redundant sub-models to detect measurement faults in the encoder and ITSC faults, which are applied in different levels of each phase winding. The effectiveness of the proposed detection method is validated by an in-house test setup of an inverter-fed PMSM, where ITSC and encoder faults are applied to the system in different time intervals using controllable relays. Finally, a statistical detector, namely a generalized likelihood ratio test algorithm, is implemented in the decision-making diagnostic system resulting in the ability to detect ITSC faults as small as one single short-circuited turn out of 102, i.e., when less than 1% of the PMSM phase winding is short-circuited.

This paper proposes a method for calculating a health indicator (HI) for low-speed axial rolling element bearing (REB) health assessment by utilizing the latent representation obtained by variational inference using Variational Autoencoders (VAEs), trained on each speed reference in the dataset. Further, versatility is added by conditioning on the speed, extending the VAE to a conditional VAE (CVAE), thereby incorporating all speeds in a single model. Within the framework, the coefficients of autoregressive (AR) models are used as features. The dimensionality reduction inherent in the proposed method lowers the need of expert knowledge to design good condition indicators. Moreover, the suggested methodology allows for setting the probability of false alarms when encoding new data points to the latent variable space using the trained model. The effectiveness of the proposed method is validated based on two different datasets: from a workshop test of an offshore drilling machine and from an in-house test rig for axial bearings. In both datasets, the HI is exceeding the warning and alarm levels with a probability of false alarm (PFA) of 10 -6 , and the method is most effective at lower shaft speeds. publishedVersion

Permanent magnet synchronous motors (PMSMs) have played a key role in commercial and industrial applications, i.e. electric vehicles and wind turbines. They are popular due to their high efficiency, control simplification and large torque-to-size ratio although they are expensive. A fault will eventually occur in an operating PMSM, either by improper maintenance or wear from thermal and mechanical stresses. The most frequent PMSM faults are bearing faults, short-circuit and eccentricity. PMSM may also suffer from demagnetisation, which is unique in permanent magnet machines. Condition monitoring or fault diagnosis schemes are necessary for detecting and identifying these faults early in their incipient state, e.g. partial demagnetisation and inter-turn short circuit. Successful fault classification will ensure safe operations, speed up the maintenance process and decrease unexpected downtime and cost. The research in recent years is drawn towards fault analysis under dynamic operating conditions, i.e. variable load and speed. Most of these techniques have focused on the use of voltage, current and torque, while magnetic flux density in the air-gap or the proximity of the motor has not yet been fully capitalised. This dissertation focuses on two main research topics in modelling and diagnosis of faulty PMSM in dynamic operations. The first problem is to decrease the computational burden of modelling and analysis techniques. The first contributions are new and faster methods for computing the permeance network model and quadratic time-frequency distributions. Reducing their computational burden makes them more attractive in analysis or fault diagnosis. The second contribution is to expand the model description of a simpler model. This can be achieved through a field reconstruction model with a magnet library and a description of both magnet defects and inter-turn short circuits. The second research topic is to simplify the installation and complexity of fault diagnosis schemes in PMSM. The aim is to reduce required sensors of fault diagnosis schemes, regardless of operation profiles. Conventional methods often rely on either steady-state or predefined operation profiles, e.g. start-up. A fault diagnosis scheme robust to any speed changes is desirable since a fault can be detected regardless of operations. The final contribution is the implementation of reinforcement learning in an active learning scheme to address the imbalance dataset problem. Samples from a faulty PMSM are often initially unavailable and expensive to acquire. Reinforcement learning with a weighted reward function might balance the dataset to enhance the trained fault classifier’s performance.

As a result of several governments closing educational facilities in reaction to the COVID-19 pandemic in 2020, almost 80% of the world’s students were not in school for several weeks. Schools and universities are thus increasing their efforts to leverage educational resources and provide possibilities for remote learning. A variety of educational programs, platforms, and technologies are now accessible to support student learning; while these tools are important for society, they are primarily concerned with the dissemination of theoretical material. There is a lack of support for hands-on laboratory work and practical experience. This is particularly important for all disciplines related to science, technology, engineering, and mathematics (STEM), where labs and pedagogical assets must be continuously enhanced in order to provide effective study programs. In this study, we describe a unique perspective to achieving multi-sensory learning through the integration of virtual and augmented reality (VR/AR) with haptic wearables in STEM education. We address the implications of a novel viewpoint on established pedagogical notions. We want to encourage worldwide efforts to make fully immersive, open, and remote laboratory learning a reality., European Union through the Erasmus+ Program under Grant 2020-1-NO01-KA203-076540, project title Integrating virtual and AUGMENTED reality with WEARable technology into engineering EDUcation (AugmentedWearEdu), https://augmentedwearedu.uia.no/ [34] (accessed on 27 March 2022). This work was also supported by the Top Research Centre Mechatronics (TRCM), University of Agder (UiA), Norway

Vehicle crash modeling has been a challenge for researchers for several decades. Occupant injury prevention and prediction is a critical area within vehicle safety design. The modeling of material failure in structural members during a full frontal crash has been presented in this paper. This study presents a Lumped Parameter Model (LPM) with an elastic double compound pendulum replicating the impact kinematics. The model defined using Lagrangian formulation; presents a novel methodology to represent material fracture caused due to heat affected zones or welding in Ultra High Strength Steels (UHSS) in a non-linear crash event. The material fracture leads to rotation of the vehicle; presented in the form of torsional springs in the LPM developed in this study. The Simulink model has been validated with a finite element simulation and shows good correlation to predict parameters crucial to design for occupant protection in a vehicle crash.

The topology of the static synchronous compensator of reactive power for a low-voltage three-phase utility grid capable of asymmetric reactive power compensation in grid phases has been proposed and analysed. It is implemented using separate, independent cascaded H-bridge multilevel inverters for each phase. Every inverter includes two H-bridge cascades. The first cascade operating at grid frequency is implemented using thyristors, and the second one—operating at high frequency is based on the high-speed MOSFET transistors. The investigation shows that the proposed compensator is able to compensate the reactive power in a low-voltage three-phase grid when phases are loaded by highly asymmetrical reactive loads and provides up to three times lower power losses in the compensator as compared with the situation when the compensator is based on the conventional three-level inverters implemented using IGBT transistors.

Author's accepted manuscript. © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. This paper deals with the online control of a redundant flexible link manipulator to achieve minimum oscillations using the redundancy resolution technique. Different redundancy resolution techniques proposed and used for rigid link manipulators are tested for their use in the case of flexible link manipulators. The simulation model of a planar three-link flexible manipulator is used in this study. The redundancy resolution using kinetic energy minimization techniques is compared with the local joint acceleration minimization method to show the advantage of achieving minimum vibrations.

Autonomous maritime navigation and offshore operations have gained wide attention with the aim of reducing operational costs and increasing reliability and safety. Offshore operations, such as wind farm inspection, sea farm cleaning, and ship mooring, could be carried out autonomously or semi-autonomously by mounting one or more long-reach robots on the ship/vessel. In addition to offshore applications, long-reach manipulators can be used in many other engineering applications such as construction automation, aerospace industry, and space research. Some applications require the design of long and slender mechanical structures, which possess some degrees of flexibility and deflections because of the material used and the length of the links. The link elasticity causes deflection leading to problems in precise position control of the end-effector. So, it is necessary to compensate for the deflection of the long-reach arm to fully utilize the long-reach lightweight flexible manipulators. This thesis aims at presenting a unified understanding of modeling, control, and application of long-reach flexible manipulators. State-of-the-art dynamic modeling techniques and control schemes of the flexible link manipulators (FLMs) are discussed along with their merits, limitations, and challenges. The kinematics and dynamics of a planar multi-link flexible manipulator are presented. The effects of robot configuration and payload on the mode shapes and eigenfrequencies of the flexible links are discussed. A method to estimate and compensate for the static deflection of the multi-link flexible manipulators under gravity is proposed and experimentally validated. The redundant degree of freedom of the planar multi-link flexible manipulator is exploited to minimize vibrations. The application of a long-reach arm in autonomous mooring operation based on sensor fusion using camera and light detection and ranging (LiDAR) data is proposed.

This paper aims to classify local demagnetisation and inter-turn short-circuit (ITSC) on position sensorless permanent magnet synchronous motors (PMSM) in transient states based on external stray flux and learning classifier. Within the framework, four supervised machine learning tools were tested: ensemble decision tree (EDT), k-nearest neighbours (KNN), support vector machine (SVM), and feedforward neural network (FNN). All algorithms are trained on datasets from one operational profile but tested on other different operation profiles. Their input features or spectrograms are computed from resampled time-series data based on the estimated position of the rotor from one stray flux sensor through an optimisation problem. This eliminates the need for the position sensors, allowing for the fault classification of sensorless PMSM drives using only two external stray flux sensors alone. Both SVM and FNN algorithms could identify a single fault of the magnet defect with an accuracy higher than 95% in transient states. For mixed faults, the FNN-based algorithm could identify ITSC in parallel-strands stator winding and local partial demagnetisation with an accuracy of 87.1%.

Research on incubation models indicates that incubators and accelerators are crucial catalysts for the development of start-ups. To facilitate start-ups in financial markets, several regulatory authorities have adopted a new incubation model called a ‘regulatory sandbox’. Regulatory sandboxes enable eligible applicants to test their technology-enabled financial solutions for a certain period of time (subject to conditions the regulator imposes). As such, these instruments allow innovation while preventing severe instability in financial markets caused by systemic risk. Despite their importance, management research has devoted little attention to studying how sandboxes operate as a new incubation model. In our abductive study, we adopt the activity system framework and a qualitative analysis approach to investigate the activities of five leading sandboxes and compare them with the activities of other incubation models. The data analysis yielded an activity model with three design elements (achieving membership, participating and detaching) and one design theme (improving connectedness). Thus, sandboxes are characterized by providing regulatory guidance and facilitating access to testing across international jurisdictions, distinguishing them from both generic and specialized incubation models. Our primary contribution to the incubation literature is extending the knowledge of a unique incubation model through a set of theoretical propositions. publishedVersion

This paper deals with the undesired effects of the heat treatments on the mechanical properties of (UHSS) Ultra High Strength Steel used nowadays in automotive industry to improve crashworthiness performance of vehicles. The UHSS specimens were extracted from certain parts of the car body and subjected to different heat treatments. Four types of specimens were tested: untreated, welded with metal inert gas welding, heat treated at 800 °C, and heat treated at 1250 °C. All heat-treated specimens showed dramatically reduced values of strength. The results suggest that it is important to follow the official repair manuals avoiding unnecessary welding and improper heat treatments of UHSS. The experiments provide the data necessary for constructing a constitutive model and performing a finite-element analysis of improperly repaired UHSS parts.

This paper presents a novel technique for modeling a full frontal vehicle crash. The crash event is divided into two phases; the first until maximum crush and the second part when the vehicle starts pitching forward. This novel technique will help develop a three degrees of freedom (DOF) lumped parameter model (LPM) for crash and support in the vehicle development process. The paper also highlights the design process for reducing vehicle pitching in occupant protection load cases. The model has been validated against a finite element (FE) simulation of a full frontal crash of a Chevrolet Silverado developed by the National Highway Traffic Safety Administration (NHTSA), and the LPM shows good correlation with the FE test data.

In recent years drone racing using human pilots have increased in popularity. This combined with the increased usage of autonomous driving vehicles have sparked a new field of interest which is Autonomous Racing Drones competitions. This thesis explores the field of drone design and avionics with the conclusion of presenting the first Racing Drone prototype that can be used in future work made by students at UiT. The body and avionics have all been designed with the idea of making future iterations and improvements possible. The design considerations and decisions are also explored in-depth to give a reasoning behind the final result.

Author's accepted manuscript. © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The use of camera and LiDAR sensors to sense the environment has gained increasing popularity in robotics. Individual sensors, such as cameras and LiDARs, fail to meet the growing challenges in complex autonomous systems. One such scenario is autonomous mooring, where the ship has to be tied to a fixed rigid structure (bollard) to keep it stationary safely. The detection and pose estimation of the bollard based on data fusion from the camera and LiDAR are presented here. Firstly, a single shot extrinsic calibration of LiDAR with the camera is presented. Secondly, the camera-LiDAR data fusion method using camera intrinsic parameters and camera to LiDAR extrinsic parameters is proposed. Finally, the use of an image-based segmentation method to segment the corresponding point cloud from the fused camera-LiDAR data is developed and tailored for its application in autonomous mooring operation.

Nowadays, due to the concern of environmental challenges, global warming and climate change, companies across the globe have increasingly focused on the sustainable operations and management of their supply chains. Closed-loop supply chain (CLSC) is a new concept and practice, which combines both traditional forward supply chain and reverse logistics in order to simultaneously maximize the utilization of resource and minimize the generation of waste. In this paper, a stochastic CLSC network optimization problem with capacity flexibility is investigated. The proposed optimization model is able to appropriately handle the uncertainties from different sources, and the network configuration and decisions are adjusted by the capacity flexibility under different scenarios. The sample average approximation (SAA) method is used to solve the stochastic optimization problem. The model is validated by a numerical experiment and the result has revealed that the quality and consistency of the decision-making can be dramatically improved by modelling the capacity flexibility.

It is inevitable that technological improvements have affected human’s life in any aspect to a large extent. Automation, artificial intelligence, robotics, etc., are some advances contributed to the fourth industrial revolution: Industry 4.0. Despite there are still many arguments, Internet of Things (IoT) and Cyber Physical Systems (CPS) have been widely acknowledged as the main fundaments of Industry 4.0. This paper introduces the concept of CPS by providing an explicit framework that unifies the existing theories in this regard. Nine exquisite technologies attributed to Industry 4.0 are investigated, among which virtual technology (VT) and digital twin (DT) are considered as two of the core criteria and are thus focused on in this paper. However, for providing an acceptable level of integration and intelligence, noticeable gap between the virtual world and the real factory is still a significant challenge. Holistic approaches addressing this issue suggest VTs and DT have the potential to form the fundaments for more improvements in terms of both interoperability and consciousness. Furthermore, they may pave the way for achieving the highest level of CPS and Industry 4.0.

A full-scale crash test is conventionally used for vehicle crashworthiness analysis. However, this approach is expensive and time-consuming. Vehicle crash reconstructions using different numerical modelling approaches can predict vehicle behavior and reduce the need for multiple full-scale crash tests, thus research on the crash reconstruction has received a great attention in the last few decades. Among modelling approaches, lumped parameters models (LPM) and finite element models (FEM) are commonly used in the vehicle crash reconstruction. This thesis focuses on developing and improving the LPM for vehicle frontal crash analysis. The study aims at reconstructing crash scenarios for vehicle-to-barrier (VTB), vehicleoccupant (V-Occ), and vehicle-to-vehicle (VTV), respectively. In this study, a single mass-spring-damper (MSD) is used to simulate a vehicle to-barrier or a wall. A double MSD is used to model the response of the chassis and passenger compartment in a frontal crash, a vehicle-occupant, and a vehicle-tovehicle, respectively. A curve fitting, state-space, and genetic algorithm are used to estimate parameters of the model for reconstructing the vehicle crash kinematics. Further, the piecewise LPM is developed to mimic the crash characteristics for VTB, VO, and VTV crash scenarios, and its predictive capability is compared with the explicit FEM. Within the framework, the advantages of the proposed methods are explained in detail, and suggested solutions are presented to address the limitations in the study.

Because of an increasing focus on environmental impact, including CO2 emissions and fluid spill pollution, inefficient hydraulic systems are being replaced by more environmentally friendly alternatives in several industries. For instance, in some offshore applications that have multiple diesel generators continuously running to produce electricity, all hydraulic rotating actuators supplied from a central hydraulic power unit have been replaced with AC induction motors containing a variable frequency drive and gearbox. However, hydraulic linear actuators are still needed in most load-carrying applications mainly because of their high reliability associated with external impact shocks. Moreover, their force capacity is higher than that of their linear electromechanical counterparts. Valve-controlled linear actuators (cylinders) supplied from a centralized hydraulic power unit are standard in offshore load-carrying applications. In addition to the advantages mentioned above of hydraulic linear actuators, they have, nevertheless, a number of important drawbacks, which include: 1) a high level of energy consumption due to significant power losses caused by flow throttling in both the pipelines and valves, 2) reduced motion performance due to the influence of load-holding valves, 3) high CO2 emissions and fuel costs related to the diesel generator that supplies electricity to the hydraulic power unit, 4) significant potential for hydraulic fluid leakage because of many leakage points, 5) demanding efforts with respect to installation and maintenance, as well as 6) costly piping due to the centralized hydraulic power supply. The work presented in this dissertation and the appended papers are devoted to replacing inefficient hydraulic linear actuation systems traditionally used in offshore load-carrying applications with more environmentally friendly solutions. Two alternative technologies are identified, namely electro-mechanical and electro-hydraulic self-contained cylinders. The feasibility of replacing conventional valve-controlled cylinders with self-contained cylinder concepts is investigated in two relevant case studies.

This research paper presents guidelines on how to select between self-contained electro-hydraulic and electromechanical cylinders. An example based on the motion control of a single-boom crane is studied. The sizing process of the different off-the-shelf components is analyzed in terms of design impact when replacing a traditional valve-controlled hydraulic cylinder. The self-contained electro-hydraulic solution is the best choice when a risk for high impact forces is present, when the required output power level lies continuously above 2 kW, or when installation space, weight, and cost are critical design objectives. However, the electro-mechanical solution is expected to show more controllability due to the fact that it has higher levels of drive stiffness, and energy efficiency as well as lower system complexity. This solution also requires less effort to control the actuator’s linear motion accurately. All of these factors result in a more straightforward design approach.

This thesis investigates the topic of modeling and control of PWA systems based on two experimental cases of an electrical and hydraulic nature with varying complexity that were also built, instrumented and evaluated. A full-order model has been created for both systems, including all dominant system dynamics and non-linearities. The unknown parameters and characteristics have been identi ed via an extensive parameter identi cation. In the following, the non-linear characteristics are linearized at several points, resulting in PWA models for each respective setup. Regarding the closed loop control of the generated models and corresponding experimental setups, a linear control structure comprised of integral error, feed-forward and state-feedback control has been used. Additionally, the hydraulic setup has been controlled in an autonomous hybrid position/force control mode, resulting in a switched system with each mode's dynamics being de ned by the previously derived PWA-based model in combination with the control structure and respective mode-dependent controller gains. The autonomous switch between control modes has been de ned by a switching event capable of consistently switching between modes in a deterministic manner despite the noise-a icted measurements. Several methods were used to obtain suitable controller gains, including optimization routines and pole placement. Validation of the system's fast and accurate response was obtained through simulations and experimental evaluation. The controlled system's local stability was proven for regions in state-space associated with operational points by using pole-zero analysis. The stability of the hybrid control approach was proven by using multiple Lyapunov functions for the investigated test scenarios.

The location decision on service facilities is of significant importance in determining the accessibility of the service provided. Due to this reason, it has been extensively focused over the past decades by both researchers and practitioners. This paper investigates a novel two-phase hybrid method combining both optimization model and agent-based simulation in order to solve the location problem of printers at a building of UiT The Arctic University of Norway, Narvik campus. In the first phase, the p-median location problem is employed to select the optimal locations of printers from a number of pre-determined candidate points so that the total travel distance by both employees and students can be minimized. In the second phase, both the original and the optimal location plans of printers are tested, validated and visualized with the help of AnyLogic simulation package. The result of the case study shows, however, the mathematically optimized solution may not yield a better performance under a realistic environment due to the simplification made and incapability to deal with the randomness. This has revealed that AnyLogic simulation can be used as a powerful tool to validate and visualize the result obtained from an optimization model and to make suggestions on the improvement.

S-N curves found in various rules and regulations are the basic tool for the practicing engineer when carrying out life predictions for welded details in dynamically loaded structures. The present work is investigating the expected fatigue life and associated scatter for welded steel joints subjected to Constant Amplitude (CA) loading. The objective is to obtain more reliable life predictions based on advancements in the probabilistic model fitted to collected life data. A Random Fatigue Limit Model (RFLM) is proposed to obtain fatigue resistance curves at given probability levels of survival. As a distinction to more conventional statistical methods, the model is treating both the fatigue life and the fatigue limit as random variables. The focus is on high cycle fatigue and long-life data and runouts are included in a rational and logical manner by using a maximum likelihood method. Life data for a transverse fillet welded attachment originally designated as a category 71 detail in Eurocode 3 Part 1-9 are collected and analysed. The plate thickness of the specimens ranges from 20 mm to 32 mm and the steel quality is mild and medium strength Carbon-Manganese steel. The results are compared with the results obtained by conventional S-N curves. The compatibility between the fitted probabilistic models and the underlying fatigue damage mechanisms is emphasized.

Maintenance is a key operation function that is required to improve business performance by avoiding equipment breakdown. In 1971, Total Productive Maintenance (TPM), a lean manufacturing approach, has been developed and widely used as a maintenance strategy to gain a competitive advantage in industry. However, with the advent of new technology and the internet of things, manufacturing process are subject to evolve from the old traditional ways of manufacturing to digitalized manufacturing. In this stage, the utilization of data for understanding current operating conditions and detecting faults and failures is an important topic to research. However, that alone is not enough to ensure long term survival and success in the market. Today, with the applications and technologies of Industry 4.0, components and systems are able to gain self-awareness and self-predictiveness which will provide management with more insight on the status of the factory. Systems are able to make use of both historical and live data which was not possible before. In this context, this thesis aims on developing a framework for productive and efficient maintenace with the use of Industry 4.0 technologies. The thesis discusses the new benefits that predictive maintenance has the potential of providing and it discusses several machine learning algorithms that are promising in the field of maintenacne. Throughout the thesis several models are developed and discussed to provide a framework that would ease the transition of mainentance from the old traditional ways to the newly emerging concept of a smart factory in Industry 4.0.

A crucial aspect of the supply chain network design process is deciding on optimal locations to situate new facilities. Facility location decisions rely on many factors, some of which might be conflicting with each other. The decision factors can be either quantitative or qualitative, thus a brute-force prioritization of one over another could be detrimental overall. To ensure the efficacy of the selection process, decision makers must consider both the quantitative and qualitative factors in tandem. Some of the common methods employed in the literature by organizations to facilitate their decision-making process include: optimization models and algorithms, decision support systems and computerized analytics tools. To this end, this thesis proposes a hybrid Multi-Criteria Decision Making (MCDM) model to aid the selection of an optimal location that suits the strategic fit of an organization. The proposed model integrates the Analytic Hierarchy Process (AHP) methodology for Multi-Attribute Decision Making (MADM) with Mixed Integer Programming (MIP). The solution is modeled and implemented with the AIMMS modeling language as well as the Gurobi Optimization tool in Python. This thesis work is based on a case study from Biim Ultrasound.

A small and medium sized enterprise (SME) with an assembly to order manufacturing system (ATO-MS) depending on a global supply chain has especially challenges when it comes to secure the quality. The parts procured from a global supply chain represent a big amount of value invested in to the short line of the MS. Depending on the definition of quality from the suppliers, how can the company react to this challenges? This project is focused on finding good engineering strategies for each step of the MS which contributes to assure the quality of the procured parts. Finally based on a theoretical case and the use of the house of quality as a quality tool, the impact on the quality of the procured parts, by using this engineering strategies is done.

Manufacturing of thin wall structure by wire arc additive manufacturing (WAAM) is on the main application of additive manufacturing. 3D-printing technology has significant advantages over traditional milling and machining techniques or welded analogs. Thin wall structure constitutes an essential and growing proportion of engineering construction, within common areas as in structural aerospace and large scale-components. The dissertation utilized a layer-wise production technique known as gas arc tungsten arc welding (GTAW), performed by a programmed KUKA-30 robot. The thesis aspect of welded structures is the degree of how disposable the product is after manufactured, due to the different set of welding parameters. Therefore are an investigation of residual stresses and deformation implemented by different structure geometries. The research includes two practical and analytical experiment tests in addition to an FEA-simulation. The experiments involve; ultrasound measurement by a self-programmed measuring device developed by BiT, calculation due to measured deformation along the welding length and simulation performed in ANSYS. Findings of the methods implicate an estimated value of residual stresses and distortion in the thin wall structure and substrate. Through ten tests of the welding process can the technique of this technology state as slow with frequently sources of error, using the KUKA-30 robot welding system for a certain height. The level of residual stresses depends on the severity of the manufacturing process, which this research confirmed a generally low value along the length of the structural components and base plate due to the parameters developed in this study.

As global trade increases, sizes of vessels and cargo throughputs have also experienced a sudden rise thereby putting excess pressure on ship berths and ports. This is shifting most ports to much smarter technological solutions with the aim of optimizing operations, increasing efficiency and reducing logistics cost without the need for huge infrastructural and equipment investments. Developing the right strategy, lack of data security and inadequate cost-study analysis of the required smart port technology to be adopted remains the major challenge for Small and Medium sized Ports in adopting smart technologies in their operations. Almost all prior smart port researches focuses on larger ports with no attention to small and medium sized ports despite their irreplaceable role in global trade and national development. In this report, a smart port framework focusing on technology, safety and security, sustainable development, and port operations is developed for SMPs, with an integrated implementation plan and a cost benefit analysis. This work will serve as a guide for SMPs in choosing and implementing the right smart initiatives and also lays the foundation for further research in technological innovations for SMPs.

With the growing aquaculture, improved management of the environmental, logistic-managerial, social, and economic aspect are vital to preserving sustainability in the industry. The dissertation addresses the potential processing of the fish waste in aquaponics (a combination of two highly effective production technologies: hydroponics and recirculating aquaculture). Involving a suggestion for sustainable management by implementing a circular business model to the industry, lessens the ecological footprint, and supports an environmental friendly production of both fish and plant. Aquaponics in Northern Norway has definite potential. However, no blueprint for success exists, which means each individual producer needs to carefully assemble the system to utilize the available local resources. In Norway, the cold water species, salmon and trout, are the most extensive farmed, showing great potential in an aquaponic system. With mapped living, nutritional, and environmental requirement, the dissertation combines salmon and trout to potential plants. The plant types taken into consideration were selected in terms of economic viability, system design, plant category, and the nutrient match between the plants nutritional value, and the nutrient value of the aquatic species waste emission. During the analysis of the potential of aquaponics in Northern Norway many factors were taken into considerations, among these, the electricity costs were proven to be one of the critical aspects, while others, such as existing facilities and already established water connections, were found to be suitable for the development of the system. Therefore the thesis consists of an extensive cost-benefit analysis of the electricity costs, with a significant focus on lighting and heating costs. Four plants were analyzed, tomato, parsley, tomato and lettuce where it was the herbs: parsley and basil, that proved to bestow the greatest potential with the highest overall profit margin with the electricity and lighting costs taken into considerations. Additionally, Rakocy defined feed rate ratio is used in the calculations with 60g/m3 for the leafy herbs and 80g/m3 for fruity plants to balance the ecosystem, determine the annual plant productivity, and in that regard the annual profit potential.

China’s state council has unveiled a ten-year national plan, Made in China 2025, designed to transform China from a manufacturing giant into a world manufacturing power. Of all the projects includes in the “Made in China 2025” plan, intelligent and automated manufacturing is crucial. It is based on concepts i.e., internet of things, cloud computing, and big data. These technologies will be involved in every aspect of the manufacturing process, to realize optimized decisions in manufacturing operations. Manufacturing is the engine to drive rapid growth of economy, which is also one of the basic elements to the development of the country. Advanced manufacturing technology (AMT) benefits from the development of a new generation of information technology. And concept i.e., Intelligent Manufacturing Technology (IMT), has become the mainstream in AMT. This project aims to explore “Made in China 2025” and apply to a manufacturer. To show that will improve the manufacturing industry. In this project, a case study at a Chinese company in introducing the concept “transformation” (from the traditional to Made in China 2015) will be conducted.

Working with large quantities of digital images can often lead to prohibitive computational challenges due to their massive number of pixels and high dimensionality. The extraction of compressed vectorial representations from images is therefore a task of vital importance in the field of computer vision. In this paper, we propose a new architecture for extracting such features from images in an unsupervised manner, which is based on convolutional neural networks. The model is referred to as the Unsupervised Convolutional Siamese Network (UCSN), and is trained to embed a set of images in a vector space, such that local distance structure in the space of images is approximately preserved. We compare the UCSN to several classical methods by using the extracted features as input to a classification system. Our results indicate that the UCSN produces vectorial representations that are suitable for classification purposes.

In this paper, we present a new mixed-integer linear goal programming (MILGP) model for a fuzzy single-source capacitated facility location problem (F-SSCFLP), in which demands are considered as triangular fuzzy values and capacity of facilities are fuzzy constraints. At first, the basic fuzzy model for the given problem is presented. Then, utilizing goal programming (GP) approach and fuzzy principals the proposed MILGP model is introduced. Accordingly, considering a certain acceptable deviation from capacities and demands, the cost of selecting facilities and serving the demand points is minimized. Finally, to investigate the effectiveness of the presented model some large-sized problems generated randomly and all of them are solved globally in a reasonable time.

Accepted manuscript version. Published version available at: https://doi.org/10.1016/j.energy.2018.11.050 In order to contribute to the reduction of greenhouse gas emissions, electric vehicles (EVs) should be charged using electricity from renewable energy sources. This paper describes a study of photovoltaics (PV) utilization for EV charging in two Scandinavian cities: Tromsø in Norway and Uppsala in Sweden, with the objective to evaluate self-sufficiency and self-consumption. The suitable areas for PV were determined using building area statistics and utilization factors. The PV yield was simulated for integration scenarios of 10%-100% of the suitable area. EV charging patterns were generated using a stochastic model based on travel survey data. The scenarios include EV penetration of 10%-100% of the personal vehicle fleet. The results show that the PV energy yield could cover the EV load in most of the scenarios, but that the temporal load match could be improved. The energy balance was positive for all seasons and EV levels if the PV integration was over 50%. The highest self-sufficiency was achieved in Tromsø during summer, due to the longer days. For high EV penetration and low PV integration, the self-sufficiency was higher in Uppsala, indicating that installed PV power is more important than yield profile above a certain number of EVs.

This thesis explores the history, concept and criteria of flexible manufacturing systems. A small-scale test bench is designed and constructed for educational and demonstrational pur- poses. The test bench in comprised of an industrial robot, a CNC machine, and a conveyor. These are all controlled and automated from a PLC with a connected touch panel for human machine interface. It describes in detail the three main parts of building the test bench. First is the physical construction of the test bench and how the parts were machined using a metal band saw and a milling machine. Second is the interfacing between the components with electrical wiring, signal configuration and usage of OPC, PLC and PC to enable communication. The third and final step is the programming of the components where python, g-code, robot code and two different PLC codes all work together to create a seamless system with many customisation options.

Lean Six Sigma has proven to be a valuable tool for improving flow and quality in any business activities. It is being implemented by almost all business forms globally. It is now an important curriculum for engineering and management students. UiT- The Arctic University of Norway, Narvik is one of the fine institutions which provide training course on Lean Six Sigma for Master’s students studying Industrial Engineering. For the past years, UiT-Narvik has been adopting this training exercise from external sources. Now, UiT aims to develop its own training exercise. This project is all about proposing a new training exercise for UiT. The new training exercise is a project based problem-solving exercise where the students (group of ca. 6) will run a simulation of a mini- beverage factory for at least two times, first run is for documenting current situation of the factory and next run is for improved process. The training activity follows DMAIC (Define Measure Analyze Improve Control) methodology and has been designed such that some of its contents are linked with other Industrial Engineering courses. The entire training kit has been built inside the UiT workshop lab. To facilitate the exercise, a separate student manual and an excel model have been constructed. This exercise is not only limited for engineering students. It has a full potential to be used for people with different professions.

This paper considers a non-preemptive open shop scheduling problem (OSSP), in which machines are not available to process jobs on known periodic interval times resulted from periodic service repair, rest period, and so on. Asymmetric transportation time between machines is considered, which can be different from one job to another. The objective is to minimize the weighted mean completion time (WMCT). Since the problem is categorized into NP-hard class, two meta-heuristic algorithms including genetic algorithm (GA) and differential evolution (DE) are proposed. Meanwhile, a new initial population is introduced, which significantly improves the performance of the algorithms. Finally, the performance of the algorithms is validated through some large-sized instances and the results are discussed.

Preventive methods are important group of methods used in the process of design and which are known as quality design methods. The aim of these methods is identification of potential failures and cause-and-effect relationships in consistent and systematic way, and then taking appropriate preventive or corrective actions. The well-known examples of preventive methods also used for modelling and analysis of the criticality (risk) factor are FMEA analysis and FTA analysis. A matrix FMEA analysis method has been presented and discussed in the work. The basic assumptions related to this method were characterized and algorithms for each stages of analysis have been presented. It has been presented practical application of FMEA method on example of selected components of hydraulic system.

Hydraulic power systems are widely used in heavy machinery. Safety of such a systems have a major importance due to the fact that any failure may cause environmental contamination or serious injury. One of the component which protects hydraulic drive systems against excessive rising of working pressure is a safety valve which aim is to maintain pressure in the systems below acceptable level. Pressure control valves which plays important role in a hydraulic systems may have very simple or complex structure. Even in case of the simplest structure of such valve modeling is not an easy task. The new quality in designing hydraulic valves bring CFD method and FSI (Fluid Structure Interaction) methods.

This paper proposes an adaptive nonlinear controller for a 2-Degree of Freedom (DOF) helicopter. The proposed controller is designed using backstepping control technique and is used to track the pitch and yaw position references independently. A MIMO nonlinear mathematical model is derived for the 2DOF helicopter based on Euler-Lagrange equations, where the system parameters and the control coefficients are uncertain. Unlike some existing control schemes for the helicopter control, the developed controller does not require the knowledge on the system uncertain parameters. Updating laws are used to estimate the unknown parameters. It is shown that not only the global stability is guaranteed by the proposed controller, but also asymptotic tracking and transient performances are quantified as explicit functions of the design parameters. Simulations and experiments are carried out on the Quanser helicopter to validate the effectiveness, robustness and control capability of the proposed scheme.

A digital twin is a new and emerging tool of the fourth industrial revolution. It is an extensive part of connecting the manufacturing equipment together to develop a smart factory. Investigation of simulating manufacturing system to bind the digital world with the physical, allows for analysis of data and monitoring of systems to head off problems before they even occur, preventing downtime, develop new opportunities and even plan for the future by using simulations. In this study, a KUKA KR 30-3 Robot was used as a main vessel of motors to mirror the programmed movement initiated in the visualizing software Visual Components. The investigation of the connection between the robot and simulation was therefore conducted with an old version of the robot controller [KR C2], where an OPC UA server was utilized to share the data throughout the work. Additional to the existing digital twin an AVG was planned to interfere conjointly with the system. In purpose to illustrate the capability of the OPC UA to store information for a common system. Findings of the research-study resulted in a stable digital twin of the KUKA robot using RSI communication. Using the OPC UA server provides the possibility to connect future manufacturing equipment to the digital twin.

This is a post-peer-review, pre-copyedit version of an article published in Lecture Notes in Electrical Engineering. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-981-13-2375-1_5 When operators and industrial robots are sharing the same task, there are multiple factors, which effect if a system is safe for the human operator or not. In general this is solved by introducing Collaborative Robot for cooperation, but what happens when we would extend our already existing production facilities with newer comfort features? In this paper we propose to include industrial robots and humans executing the same task, while their safety is supervised by a simulation environment, where all necessary precautions are taken. The task is a simple nut-screw operation, where the industrial robot is executing the hard lifting part for the screw and the human holds the nut to be screwed on the screw. Results are demonstrated through simulation and in reality also.

A closed-form dynamic model of the planar multi-link flexible manipulator is presented. The assumed modes method is used with the Lagrangian formulation to obtain the dynamic equations of motion. Explicit equations of motion are derived for a three-link case assuming two modes of vibration for each link. The eigenvalue problem associated with the mass boundary conditions, which changes with the robot configuration and payload, is discussed. The time-domain simulation results and frequency-domain analysis of the dynamic model are presented to show the validity of the theoretical derivation.

Construction of a stable flame is one of the critical design requirements in developing practical combustion systems. Flames stabilised by a bluff-body are extensively used in certain types of combustors. The design promotes mixing of cold reactants and hot products on the flame surface to improve the flame stability. In this study, bluff-body stabilised methane-hydrogen flames are computed using the steady laminar flamelet combustion method in conjunction with the Reynolds-averaged Navier-Stokes (RANS) approach. These flames are known as Sandia jet flames and have different jet mean velocities. The turbulence is modelled using the standard k-ϵ model and the chemical kinetics are modelled using the GRI-mechanism with 325 chemical reactions and 53 species. The computed mean reactive scalars of interest are compared with the experimental measurements at different axial locations in the flame. The computed values are in reasonably good agreement with the experimental data. Although some underpredictions are observed mainly for NO and CO at downstream locations in the flame, these results are consistent with earlier reported studies using more complex combustion models. The reason for these discrepancies is that the flamelet model is not adequate to capture the finite-rate chemistry effects and shear turbulence specifically, for species with a slow time scale such as nitrogen oxides.

Master's thesis Mechatronics MAS500 - University of Agder 2018 In the past years, rotorcraft have received much attention in our society. These provide great accessibility and are utilized in many areas of application. The complex dynamics of rotorcraft make them di cult to control, and the applications demand stable, safe, and agile devices. This thesis investigates the use of advanced control methods and evaluates their e ectiveness using a 2DOF (pitch and yaw) ' ight control experiment-platform'; the Quanser AERO. The main goal of the project is development and evaluation of angular-position controllers for the AERO, using conventional and advanced control theory. This includes cascade P-PI, LQR state-feedback, MPC and MRAC. The controllers are tested in simulation using linear and nonlinear models, and implemented for control of the AERO. The performance of each controller is evaluated in a standardized test. This test is combined step response sequence for pitch and yaw axes. The performance of each controller is evaluated through a performance index, which is based on the squared tracking error between command signal and plant output. This project has shown that model based controllers like LQR and MPC works well when tuned to a speci c case (for both simulation and practical application), but the performance crumbles when the system is changed without changes to the controller parameters. The simulation of control of a linear system for the conventional controller and MRAC gave excellent results, which con rms that the controllers work well in theory. When it comes to practical application, the conventional controller continues to work relatively well. The MRAC, however, shows strange behaviour, which was not anticipated. The results give insight to the practical application of advanced controllers, and inspires further research into the subject.

Master's thesis Mechatronics MAS500 - University of Agder 2018 In the constant effort to improve the efficiency of hydraulic systems, the pressure drop over hydraulic valves has been one of the major obstacles. In the Self-Contained Electro-Hydraulic Cylinder, the directional valve and the hydraulic power unit have been replaced by a bi-directional axial piston pump and a Permanent Magnet Synchronous Motor. Actuation of the cylinder is performed by controlling the direction of rotation and the velocity of the motor. Originally the purpose of this project was to: "Design a proper control algorithm for an existing novel selfcontained electro-hydraulic cylinder, implement it on the main boom of a loader crane, and troubleshoot it". Due to a time delay in having the test bed ready for experiments, more effort was put into modelling and control design. The system is divided into three major parts: The hydraulic system, the electric drive and the external load in the form of a vertical boom with a payload. The main parts of the hydraulic system are the asymmetric cylinder, the fixed displacement axial pump and the load holding system. The load holding part consists of two pilot operated check valves, and a system for controlling the pilot pressure. The electric drive is divided into the inverter and the PMSM. The kinematics of the vertical boom was derived using classical static mechanics. In addition, a dynamic model is available, that was derived from a previous PhD research program, which was tested and compared to the static model. When all three models were combined into one, the overall simulation time was beyond what was considered useful, and it was decided to simplify the electric drive and use the static mechanic model. Then the control design phase started, a linearised model of the system is derived and compared with the the high-fidelity Simulink model. A frequency response test is performed, both model based and on the test bed. Different control architectures are tested; such as P and PI controllers. A feedforward term is also implemented in the structure. The overall performance is then tested on several motion profiles. Search words: Self-Contained Electro Hydraulic Cylinder, Fluid Power, Asymmetric Actuator, Axial Piston Pump, Passive Load Holding, Electric Drives, Permanent Magnet Synchronous Machine, Modelling, Control Design, Experiments.

Master's thesis Mechatronics MAS500 - University of Agder, 2018 Konfidensiell til / confidential until 01.07.2023

Master's thesis Mechatronics MAS500 - University of Agder 2018 This report covers development and implementation of a model-based fault-detection and fault diagnosis algorithm based on structural analysis, providing deeper knowledge of predictive maintenance, which o ers the industry increased uptime and reduced spending. Failure mode and e ect analysis are carried out at component level for an electrical winch. Construction of a Simulink model, used to verify the algorithms, are described in detail including governing equations and implementation. The basis of a structural analysis is outlined and tested on the electrical winch system. Results from the simulation model covers faults in permanent magnet motor, bearings, gearbox and sensors. The structural analysis is able to detect and isolate several types of typical faults that can occur in electrical winch systems.

Master's thesis Mechatronics MAS500 - University of Agder 2018 Konfidensiell til / confidential until 01.07.2023

Master's thesis Mechatronics MAS500 - University of Agder 2018 The reliable traditional hydraulic systems for industrial purposes is being challenged by an emerging technology called digital hydraulics. This technology shows promising improvements in regards to e ciency, especially in comparison to systems dependent on hydraulic pumps or motors with variable displacement. Digital hydraulic motors eliminate the need for a servo valve by connecting each individual motor cylinder directly to the high-pressure and low-pressure line by means of fast-acting on/o -valves. In this thesis, the potential of digital hydraulics is investigated by developing a control system intended for a digital displacement motor used on an industrial winch application. The expected operation modes of the winch system are analysed, and di erent control strategies are discussed. The developed control system is tested for the expected operation modes before it is simulated with a model of an industrial winch. The digital displacement motor performs well during simulated testing of typical load cases for a winch system. Some challenges are discovered when the motor switches operation mode and when the reference velocity is zero. Solutions for counteracting the mentioned challenges are implemented, and further possible improvements are proposed. The presented results prove that the suggested control strategy has the potential for good reference tracking and that the overall solution is suitable for a winch system.