| 1. |
- Aziz, Abdullah, 1992-
(author)
-
Virtualizing Operational Technology by Distributed Digital Twins
- 2023
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Doctoral thesis (other academic/artistic)abstract
- Industrial digitalization, stemming from the convergence of Information Technology (IT) and Operational Technology (OT), is a transformative force in modern industries. The Industrial Internet of Things (IIoT) and Industrial Cyber-Physical Systems (ICPS) empower industries with enhanced production processes, data-driven insights, and advanced automation. Accompanying these trends, digital twins bridge the gap between the physical and digital realms, promising dynamic representations of entities. This convergence holds great promise for fostering efficient and agile industrial ecosystems.However, amidst the promise, a series of challenges loom large across a multitude of domains. These challenges span a multitude of domains. The convergence of IT and OT engenders a spectrum of complexities, including interoperability issues, data integration dilemmas, and the imperative need to tackle the historical hardware-centricity of industrial systems. This includes enhancing energy efficiency and security in the digital realm and addressing fundamental issues within the fabric of modern industries.The scope of our research addresses these multifaceted challenges by encompassing three overarching research questions. The first explores the integration of IIoT architectures and data integration models, striving to augment interoperability and data exchange for industries, offering practical benefits. The second delves into the realm of ICPS and industrial automation, investigating how Digital Twins can optimize energy efficiency, security, and service availability. The third widens the horizon by examining the potential of distributed digital twins as proxies to foster composability and adaptability, bridge the physical-virtual gap, and meet the evolving needs of industrial IoT and cyber-physical systems.Our thesis unfolds with five key contributions, each addressing fundamental challenges in industrial digitalization. First, we present a synthesized IIoT architecture tailored for the mining industry, aligning seamlessly with IoT and Industry 4.0 standards and frameworks. Second, we explore data integration through service-based and event-driven communication models across industries. We provide a qualitative analysis of these models to present guidelines for designing data integration solutions according to needs.In the third contribution, we focus on digital twins for Industrial Cyber-Physical Systems (ICPS) and introduce the concept of a digital twin as proxy. This concept enables the virtualization of tangible devices and assets from the OT domain to the IT domain. This contribution addresses energy efficiency, security, and service availability challenges. Building on this, our fourth contribution implements and integrates the concept of the digital twin as a proxy with the Eclipse Arrowhead Framework, extending its applicability to industrial automation and reinforcing our response to the second research question.Our fifth contribution further envisions the virtualization of the OT within IT. Grounded in service-oriented and microservice architectural principles, we propose the concept of purpose-oriented composable digital twins by utilizing distributed digital twins as proxies. This concept offers a forward-looking solution to address evolving needs. Together with the third and fourth contributions, our work ensures a comprehensive and forward-looking impact on the discourse of industrial digitalization.
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| 2. |
- Borngrund, Carl, 1992-
(author)
-
Automation of Navigation During the Short-loading Cycle Using Machine Vision
- 2022
-
Licentiate thesis (other academic/artistic)abstract
- Earth-moving machines are machines used in a wide range of industries, such as the construction industry, to perform tasks related to earthworks.Currently, the vast majority of earth-moving machines are human-operated where expert operators perform these industry vital tasks.One such task is the short-loading cycle which is a repetitive work cycle performed in high quantities within the construction industry.This work cycle aims to use a wheel-loader to move material from a pile or from the ground to the tipping body of a dump truck.Not only is this task repetitive and performed in high quantities, but it is also representative of the knowledge required to perform a wide set of other work cycles, hence a good candidate for automation.Skilled operators use their sensory input to perform the tasks required, such as tactile, sound and sight.One of the most important senses leveraged during normal operations is sight, as it is used to locate dynamic objects and detect dangers.Thus to be able to replace the driver of an earth-moving machine with an autonomous system, the system requires similar vision capabilities.Machine Vision is a field where the goal is to use some type of vision sensor, such as cameras, to extract relevant high-level information from images or video streams.This thesis aims to examine how machine vision can be used within the short-loading cycle to facilitate performing said work cycle autonomously.The main findings in this thesis are threefold: Firstly, two knowledge gaps are identified in the domain of automation during the short-loading cycle.These relate to the loading of heterogeneous material and navigation during loading and unloading.Secondly, we show that it is possible to train a deep learning model to detect the cab, wheels and tipping body of a scale-model dump truck while mimicking the approach towards the load carrier during the short-loading cycle.This model can then be applied to real vehicles to detect the same objects, with no additional training.Lastly, we show that linear interpolation can be used to perform semi-automatic labelling of camera-based video data of the approach of a wheel-loader towards a dump truck during the short-loading cycle.This technique decreases the annotation workload by around 95% while retaining comparable performance.The future direction of this work includes using techniques such as reinforcement learning to teach a model to perform the navigation required during the short-loading cycle.Future work also includes using world models to learn representations of underlying structures in the environment, open-ended learning to transfer the learned knowledge to adjacent work cycles and using machine vision to find the point of attack for scooping heterogeneous material.
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| 3. |
- Lam, An Ngoc
(author)
-
Dynamic Adaptation in Industrial IoT Systems
- 2021
-
Doctoral thesis (other academic/artistic)abstract
- The evolution of the current technological landscape has opened an emergent paradigm that enables interoperability between the digital and physical world, leading to a new generation of industrial systems. This new digitalization era marks the beginning of the fourth industrial revolution, usually referred to as "Industry 4.0". By employing recent technologies and concepts such as Industrial Internet of Things (IIoT), Cyber-physical Systems (CPS), Cloud-based technologies, , Service-oriented Architecture (SoA), and Artificial Intelligence (AI), the Industry 4.0 approach aims to address the dynamic evolution of contemporary requirements as well as improve the sustainability and efficiency in industrial production. While this new industrial paradigm facilitates the integration and collaboration among industrial components, it also introduces greater complexity to the industrial systems, thereby potentially increasing costs related to system development and maintenance. Specifically, significant engineering effort is dedicated to addressing the heterogeneity, interoperability and scalability of those integrated components. As a result, in order to mitigate those challenges, the self-adaptive solution appears as a potential approach to automate the management and supervision of the systems. Self-adaptation allows the system to adapt in the face of changes in its operating environment and in the system itself without human intervention.This thesis outlines the progress made towards self-adaptation in industrial production. It proposes an architectural design that enables dynamic adaptation for IIoT systems. Particularly, in order to facilitate the integration of heterogeneous and numerous physical components, the proposed approach shifts from tightly-coupled automation systems to loosely-coupled flexible information and communication infrastructure by employing service-oriented and decentralized technologies. Furthermore, the concept of Autonomic Computing (AC) is exploited to address the interoperability among the systems with the goal to enable autonomous decision-making based on real-time information from the integrated components. To illustrate the potential of this design, an Autonomic Adaptation System is proposed to provide dynamic adaptation as a service in order to assist IIoT systems to re-orchestrate the communication among them or re-configure their internal functionality. The prototype of the system has been implemented and tested with a simulated industrial use case.
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| 4. |
- Maksuti, Silia, 1989-
(author)
-
Autonomic Management of System of Systems Security
- 2021
-
Doctoral thesis (other academic/artistic)abstract
- The digitalization of manufacturing industry and the profound reliance on interconnected System of Systems (SoS) is demanding for innovative solutions that can handle production processes, while making use of the new data that is being generated by various connected devices. Innovations based on collecting, evaluating, and using this data can improve existing processes and create new business models. Although this is beneficial to the user, at the same time, it opens the way for adversaries to exploit new vulnerabilities. Since the factories are exposing their internal production processes to the internet, security is one of the challenges that should be addressed in this new digitalization era, referred to as the fourth industrial revolution or Industry 4.0. Furthermore, security cannot be seen as independent from other non-functional requirements of SoS, e.g. performance or safety aspects. Addressing security without risking to negatively affect other aspects and vice versa is a main concern for such interconnected systems.This thesis outlines the progress made towards security management and mitigation in SoS. It proposes an automated and secure onboarding procedure, which is required to introduce a new device in a SoS environment without compromising the already on-boarded devices and the underlying infrastructure. The proposed procedure establishes a chain of trust from the hardware device to its hosted application systems and their provided services by creating a chain of digital certificates. Thus, it allows to rely on the information on which “smart” decisions are being based, while ensuring a secure and trusted communication between the interacting systems.Even with security controls in place, e.g. the automated onboarding procedure, maintaining a required security level for the SoS as a whole is difficult due to uncertainties that may occur at runtime. Uncertainties may occur due to internal factors, e.g. malfunction of a system, or external factors, e.g. malicious attacks. One approach that can tackle these uncertainties at run time and manage trade-offs between security and other non-functional requirements is self-adaptation. Self-adaptation enables a system to adapt in the face of such uncertainties without human intervention.This thesis proposes a generic autonomic management system aimed to support the engineers in building self-adaptive systems that should cope with dynamic changes of the environment and system itself, while considering the expected rapid advances of system attacks. Given its generic property, the system can be reused and extended for a variety of use cases without requiring major modifications. This will reduce the software engineering effort needed to implement the generic control mechanisms. A prototype of the system has been implemented and tested.
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| 5. |
- Borngrund, Carl, 1992-
(author)
-
Towards Deep-learning-based Autonomous Navigation in the Short-loading Cycle
- 2023
-
Doctoral thesis (other academic/artistic)abstract
- Earth-moving machines, such as wheel loaders, are a type of heavy-duty machinery used within the construction industry to perform vital tasks, such as digging, transporting, and mining applications. One of these tasks is the short-loading cycle, where an operator manoeuvres the wheel loader to move material from a pile to the tipping body of a dump truck, through navigation, scooping, and dumping. The short-loading cycle is a repetitive task performed in high quantities, often as part of a larger refinement process, making it interesting for automation.The main objective of this thesis work is to investigate challenges facing the automation of the short-loading cycle, focusing in particular on subtasks that can be efficiently addressed with deep learning methods. A secondary objective is to examine how alternative development paths, such as scale models, or simulations, can be used to enable data-driven automation of the short-loading cycle, as directly experimenting on real vehicles has a high associated cost when large numbers of timesteps are needed to gather enough data.To investigate the two objectives, the literature is systematically reviewed to identify research gaps, challenges, and the usage of deep learning techniques. Secondly, a set of deep learning techniques is investigated to address perception and actuation problems identified as challenging and important for the automation of the short-loading cycle.The investigation of deep learning techniques involves training and validating a realtime object detector neural network to identify key components (wheels, tipping body, and cab) on a scale model dump truck while testing on a real vehicle. This resulted in a localisation and classification degradation of only 14% between the scale model and the real dump truck, with no additional training. In addition, an examination to minimize the annotation workload of humans found that it is possible to decrease the workload by 95% while still retaining similar detection performance by leveraging linear interpolation.Lastly, this thesis presents an investigation regarding the usage of reinforcement learning for navigation during the short-loading cycle. The results indicate that training the agent in simulation is currently required as the agent obtains the maximum reward after timesteps in the order of millions before being capable of performing the task. The results suggest that the trained agent is capable of bridging the gap between simulation and reality to complete a simplified version of the navigation task during the short-loading cycle.The experiments presented in this thesis provide proof of concept that indicates deep learning techniques can aid in the realisation of an autonomous solution. Moreover, the results show that development paths allowing for experiments providing large numbers of timesteps can facilitate the practical use of such techniques.
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| 6. |
- Carlsson, Oscar
(author)
-
Engineering of IoT Automation Systems
- 2017
-
Doctoral thesis (other academic/artistic)abstract
- Major societal challenges such as environmental sustainability, availability of energy and raw materials, and globalisation are creating new requirements for many actors in society. These new requirements relate to efficiency, flexibility, sustainability, and competitiveness. While these aspects have all been around for some time, and many systems have been locally optimised with regards to one or a few of these requirements, recent advances in communication and processing capabilities promise increased possibilities for connecting different parts of society, allowing optimal operation on a much larger scale.While industrial production systems have been controlled electronically for decades, the digitisation of market channels and consumer systems, together with the possibility to interconnect different production facilities, now allow for automated interaction along the whole supply chain from raw materials to end users.Simultaneously, increased demand for efficiency forces increased specialisation among actors, which with increased possibilities of interconnectivity, creates large enterprises of cooperating, specialised stakeholders.One of the major remaining obstacles for a widespread adaptation of more intelligent, more connected systems, able to deliver these envisioned results, is a coherent approach to the engineering and management of Systems-of-Systems involving very large numbers of devices and operating across several automation domains.For traditional automation systems there are established engineering procedures and numerous standards for engineering data, although most are focused on the static processes that have traditionally been the norm. For full integration with a digital society many of the existing automation systems will need significant modifications and as many automation systems are ageing and in need of replacement, a suitable solution to this may be a large scale migration to new automation solutions.The work presented in this thesis includes some new approaches and methodologies to utilise the existing engineering procedures and standards, while introducing some of the flexibility proposed by the emerging technologies. The major technical solutions presented consist of a structure way to organise connected systems and how they are related, regardless of engineering standards used to design their interactions, and an approach to allow configuration of heterogeneous systems through service interactions.Further contributions include an approach for migrating certain categories of existing industrial control systems to a service oriented architecture, as a basic outline for adaption of the next generation of automation systems in industry.Certain remaining challenges have been identified, which have to be addressed for a successful launch of widespread interconnected automation systems based on Internet of Things and associated technologies.
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| 7. |
- Paniagua, Cristina
(author)
-
Autonomous Runtime System of Systems Interoperability
- 2020
-
Doctoral thesis (other academic/artistic)abstract
- The current technological environment is evolving increasingly fast, and the development of new devices, technologies, and architectures has opened an emergent paradigm where the digital and physical world work together, leading to a new digitalizacion era.For the industry, the shift of paradigm represents the start of the fourth industrial revolution, also called Industry 4.0. The Industry 4.0 approach contributes to addressing continuously evolving industrial requirements, and promotes the rise of efficiency and sustainability on industrial production. The implementation and use of systems based on a Service Oriented Architecture (SOA) in conjunction with the Internet of Things (IoT) and Cyber-Physical Systems (CPS) into System of Systems (SoS) have been extended during the last decades in numerous scenarios contributing to reach the Industry 4.0 vision.The new industrial paradigm leads to growing complexity, thus, potentially increasing the development and maintenance costs. Significant engineering time is dedicated to the integration and interoperability of different components. Therefore, one of the major barriers to this approach is the lack of interoperability between heterogeneous systems.This thesis proposes a set of architectural design principles and tools in order to reduce engineering effort by means of finding solutions that enable autonomous integration and increase interoperability without human intervention. The research is focused on the SoS field, taking service definition and SoS integration into account.The presented solution is an service contract translation system that can aid in the generation of new service consumer interfaces at both compile time and runtime. The proposed approach requires a new point of view in the service contract that can provide a holistic description of the information required for the generation of consumer interfaces. The proposed system makes use of service interface descriptions to dynamically instantiate a new autonomously generated interface that solves communication mismatches between the provider and the consumer. To illustrate the potential of this approach, a prototype of the system has been implemented and testedIn addition, aspects related to interoperability, such as the many IoT frameworks in the current market, naming conventions, syntactic modeling and translation, and security, are also partially analyzed.
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| 8. |
- Aziz, Abdullah, 1992-
(author)
-
Industrial IoT, Cyber-Physical Systems, and Digital Twins
- 2021
-
Licentiate thesis (other academic/artistic)abstract
- Industrial digitalization (Industry 4.0) is the digital transformation of industries in a connected environment of people, processes, services, systems, data, and industrial assets to realize smart industry and ecosystem of industrial innovation and collaboration. Three promising aspects of Industry 4.0 are Industrial IoT (IIoT), Cyber-Physical Systems (CPS), and Digital Twin (DT).There are challenges with these aspects. First, there are many generic IIoT stan-dards & frameworks that are alone insufficient in various industrial use-cases. Therefore, engineers must use many standards guidelines to design IIoT architectures from case to case. Second, systems deployed in industries based on different standards and tech-nologies that cannot inter-work with other systems, hence operating in isolation, so that gathering data for analysis, reporting, and decision-making is challenging. Third, in an Industrial-CPS (ICPS) environment, most of the embedded systems are resource con-straint battery-driven devices that are facing challenges such as a short life span due to high energy consumption, lower availability of the services, and low-security capabilities.The scope of this thesis is to research industrial digitalization on the above-mentioned aspects and challenges. First, we study general IIoT standards & frameworks and use them to synthesize a high-level IIoT architecture. As a use-case for verification and validation of the architecture, we specifically study the mining industry, since it is chal-lenging in terms of geographical distribution, infrastructural limitations in communi-cation, data management across different silos, storage, and exchange of information. Second, we study the ad hoc implementation of common models for integrating data between different isolated industrial systems. Most often companies build their ad hoc data integration models based on two architectural designs of Event-Driven Architecture (EDA) and Service-Oriented Architecture (SOA). We conceptually compare and analyze the implementation of both models based on selected criteria essential in an industrial environment with the aim to provide guidelines to achieve data integration between het-erogeneous industrial systems according to their requirements. Third, we define critical properties for ICPS services and we define a digital twin as a proxy (DTaaP) architecture that can meet these properties.The contribution of this thesis includes the proposal of the high-level IIoT architecture suitable for the mining industry use-case, the conceptual analysis of the data integration models, and the concept of DTaaP for ICPS. DTaaP is a four-layer architectural model that provides valuable properties such as energy efficiency, high availability & state per-sistence, remote & contention control, and security. We present a generic proof of concept DTaaP implementation by using open source technologies.
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| 9. |
- Bicaku, Ani, DI, 1988-
(author)
-
Security Standard Compliance in System of Systems
- 2020
-
Doctoral thesis (other academic/artistic)abstract
- The world we live in is becoming digitalized by transforming our society and economyin an unpredicted way. Digital technologies are transforming products, manufacturingassets, and entire supply chains. These technologies revolutionize how organisations en-gage with customers, other partners, and society depending on the ability to connectpeople, technology, and processes. Distributed services through different platforms, or-ganisations, and even regions are becoming very common with the digital transformationof industrial processes. More and more systems are being constructed by interconnectingexisting and new independent systems. The transformation from traditional and isolatedsystems to connected components in a System of Systems (SoS), provides many advan-tages such as flexibility, efficiency, interoperability, and competitiveness. While it is clearthat digital technology will transform most industries, there are a number of challengesto be addressed, especially in terms of standards and security.In the past, providing a secure environment meant isolation from external access andproviding physical protection, usually based on proprietary standards. Nowadays, withthe development of state-of-the-art technologies, these systems have to meet and provideproof of fulfilling several requirements and involving many stakeholders. Thus, to assurethat organisations can move towards this multi-stakeholder cooperation, security is one ofthe challenges that need to be addressed. With the increasing number of devices, systems,and services in these complex systems and the number of standards and regulationsthey should fulfill, the need for automated standard compliance verification is of utmostimportance. Such verification will ensure that the components included in their businessprocesses comply with the imposed standards, laws and regulations.The research presented in this thesis targets the automated and continuous standardcompliance verification in SoS. Standard compliance verification provides evidence thatprocesses and their components satisfy the requirements defined by national and interna-tional standards. The thesis proposes an automated and continuous standard complianceverification framework that provides evidence if SoS components fulfill security standards’requirements based on extracted measurable indicator points. Since these systems evolveover time, the standard compliance is verified in design time and continuously monitoredand verified during run time after the SoS has been deployed.
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| 10. |
- Chiquito, Eric
(author)
-
Decentralized Negotiations and Data Storage for the Circular Economy
- 2024
-
Doctoral thesis (other academic/artistic)abstract
- The shift from traditional modes of operation characterized by manual or analog processes to digitalization represents a fundamental transformation in the way business manage their processes and interact with their customers. Digitalization brings refinement of existing workflows, improved efficiency, enhanced customer experience, and better collaboration within ecosystems. This benefits circularity and reusability, reduces the environmental impact and helps streamlining the supply chain process.The collaboration between diverse organizations with varying data requirements highlights the importance of both political and architectural decentralization as interacting parties may be cautious about sharing sensitive data or entrusting a third party with its processing. Political decentralization eliminates the need for a governing authority to establish trust among collaborating organizations. Architectural decentralization distributes data storage across various actors and defines and enforces access rights and ownership while simultaneously improving security by eliminating a single point of failure. Lately, blockchain systems using Smart Contracts have emerged as a popular approach for achieving decentralization. However, while these implementations offer decentralization, they may not always be the most efficient solution for decentralized systems.This doctoral thesis delves into the digitalization of existing systems, with a focus on decentralized negotiation mechanisms, data storage, and circularity. The work investigates how decentralized systems can effectively represent highly interconnected data to facilitate bidirectional traversal of relationships and proposes a proof-of-concept (PoC) implementation using Interplanetary File System. This work is extended to the realm of sustainability by examining digital product passports, showcasing their role in ensuring traceability and accountability throughout product lifecycles. An analysis of the state-of-the-art blockchain approaches for transitioning electronic auctions toward decentralized systems is presented. Based on this, a system design for a decentralized auction system based on blockchain and a PoC implementation using Hyperledger Fabric are proposed. Finally, the digitalization of agreements for the automatic representation of rights and obligations in price-only and multi-attribute electronic auctions and data sharing is analyzed.The main contributions of this thesis are (1) The use of state-of-the-art decentralized technologies for the bidirectional traceability of highly interconnected data in the context of sustainability. 2) The analysis and implementation of decentralized open-cry auction systems using blockchain technologies. (3) The use of Ricardian contracts for the representation of rights and obligations in electronic auctions and data sharing.
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| 11. |
- Dadhich, Siddharth, 1987-
(author)
-
Automation of Wheel-Loaders
- 2018
-
Doctoral thesis (other academic/artistic)abstract
- Automation and tele-remote operation of mobile earth moving machines is desired for safety and productivity reasons. With tele-operation and automation, operators can avoid harsh ergonomic conditions and hazardous environments with poor air quality, and the productivity can in principle be improved by saving the time required to commute to and from work areas. Tele-remote operation of a wheel-loader is investigated and compared with manual operation, and it is found that the constrained perception of the machine is a challenging problem with remote operations. Real-time video transmission over wireless is difficult, but presents a way towards improving the remote operator’s quality of experience. To avoid glitches in the real-time video, arising from variable wireless conditions, the use of SCReAM (Self-Clocked Rate Adaptation for Multimedia) protocol is proposed. Experiments with a small scale robot over LTE show the usefulness of SCReAM for time-critical remote control applications. Automation of the bucket-filling step in the loading cycle of a wheel-loader has been an open problem, despite three decades of research. To address the bucket-filling problem, imitation learning has been applied using expert operator data, experiments are performed with a 20-tonne Volvo L180H wheel-loader and an automatic bucket-filling solution is proposed, developed and demonstrated in field-tests. The conducted experiments are in the realm of small data (100 bucket-filling examples), shallow time-delayed neural-network (TDNN), and a wheel-loader interacting with a non-stationary pile-environment. The total delay length of the TDNN model is found to be an important hyperparameter, and the trained and tuned model comes close to the performance of an expert operator with slightly longer bucket-filling time. The proposed imitation learning trained on medium coarse gravel succeeds in filling buckets in a gravel cobble pile. However, a general solution for automatic bucket-filling needs to be adaptive to possible changes in operating conditions. To adapt an initial imitation model for unseen operating conditions, a reinforcement learning approach is proposed and evaluated. A deterministic actor-critic algorithm is used to update actor (control policy) and critic (policy evaluation) networks. The experiments show that by use of a carefully chosen reward signal the models learns to improve and maximizes bucket weights in a gravel-cobble pile with only 40 bucket-filling trials. This shows that an imitation learning based bucket-filling solution equipped with a reinforcement learning agent is well suited for the continually changing operating conditions found in the construction industry. The results presented in this thesis are a demonstration of the use of artificial intelligence and machine learning methods for the operation of construction equipment. Wheel-loader OEMs can use these results to develop an autonomous bucket-filling function that can be used in manual, tele-remote or fully autonomous operations.
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| 12. |
- Garcia Represa, Jaime, 1994-
(author)
-
Workflows in Microservice Based System of Systems
- 2022
-
Licentiate thesis (other academic/artistic)abstract
- Social welfare has grown along with the developments of innovative technologies to ease manual work and provide affordable goods for everyone. Advances in science require time to reach practical use. However, when their impact is such as to reshape society, their industrial adoption is accelerated and they become part of modern history. The greatest milestones in the manufacturing domain are represented by the industrial revolutions, which offered an answer to the manufacturing requirements of their time and pushed humankind forward. Currently, at the dawn of the third industrial revolution, society demands products with the same quality and variety as those formerly produced by craftsmen, but now with the price, manufacturing time, and quantity for mass production.As a response to the demand for the mass customization of products, the industry is leveraging the adoption of new technologies in order to upgrade its manufacturing processes. Although industrial production systems have been controlled through embed-ded systems for a long time, the key for disruptive changes came with the advent of digital communications, in what has been coined Internet of Things (IoT). The virtual management of devices has become more relevant, and added to the complexity of ma-chine’s behavior interdependence with the real physical process, it presents a new field of researched captured in the concept of Cyber-Physical System (CPS).The addition of myriad of new devices with the presented capabilities paves the way to a new industrial revolution, denoted Industry 4.0. However, it will be a futile effort as current engineers lack the ability to manage a vast number of complex devices, handle the quantity of data provided, or use the information in advantageous business decisions. Manufacturing systems in a factory are controlled according to an automation architec-ture. Unfortunately, the current ISA-95 standard model adopted by the industry does not cope with modern requirements and constrains the adoption of recent technologies.In this thesis, we explore solutions to the problem of management and integration of heterogeneous software systems, focused on production and grouped in dynamic System of Systems (SoS), framed in the context of Industry 4.0. This work presents an archi-tectural approach to distribute and automate the functionality concentrated in ISA-95 centralized systems into lines of autonomous production workstations on the shop floor. Our solution is based upon the workflow technology, which has been expanded to model and automate many business processes. Specifically, we target the use of manufacturing workflows implemented through microservices, to be provided by shop floor production equipment. As part of the solution, we have implemented two software systems to add support for workflows to a microservice architecture.
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| 13. |
- Hartman, Andreas
(author)
-
Electromagnetic Modeling with Complex Dielectrics : A Partial Element Equivalent Circuit Approach
- 2019
-
Doctoral thesis (other academic/artistic)abstract
- Wireless communication systems have become an integral part of many complex systems in diverse areas of society, for the exchange of data in business and industrial settings. With the advent of Internet of Things (IoT) and wireless sensor network architectures, the tighter demands on interoperability between different devices are putting heavy requirements their ability to exchange data wirelessly among them reliably. However, many environments pose a challenging setting for a wireless communication system to operate within. Consequently, electromagnetic modeling could be used as a crucial part of the analysis and design of a wireless communication system in these environments.In this thesis, means for the electromagnetic modeling of complex materials are considered. Specifically, the incorporation of dielectrics that exhibit loss, dispersion, and anisotropic properties into electromagnetic codes is addressed. The work has been executed within the partial element equivalent circuit (PEEC) method framework.First, a PEEC implementation that incorporates dispersive and lossy dielectrics, represented by equivalent circuit models explicitly included in the PEEC equations, is developed. This provides a descriptor system form of the PEEC model that includes dielectrics with permittivities that can be represented as finite sums of Debye and Lorentz permittivity models and can be integrated by any time integration scheme of choice. Additionally, the description admits the application of model-order reduction techniques, reducing the model complexity of a large-scale PEEC model that consists of frequency-dispersive dielectrics.Next, the incorporation of anisotropic dielectrics in PEEC simulations is considered. A PEEC cell for anisotropic dielectrics, with a general permittivity tensor, is derived. It turns out to be an extension of the standard dielectric PEEC cell for an isotropic dielectric by adding a voltage-dependent current source in parallel with the excess capacitance of the dielectric cell. A cross-coupling excess capacitance concept that defines the dependent current source for the anisotropic PEEC cell is defined and given for orthogonal PEEC meshes. As a result, the PEEC cell for an anisotropic dielectric is possible to extend to handle lossy and dispersive anisotropic dielectrics straightforwardly. The developed PEEC model has been applied to model a patch antenna mounted on an anisotropic substrate. The simulation results are in agreement with other simulation technique results. Consequently, the anisotropic model permits electromagnetic modeling of structures and devices that consist of a broader class of materials.The modeling of dielectrics in different ambient temperature conditions is also considered for the PEEC analysis of its impact on antennas. Dielectrics with temperature dependent permittivity have been modeled with PEEC by standard approaches found in the literature. This has proved useful for frequency-domain simulations in PEEC. The utility has been demonstrated by investigating the impact due to temperature-dependent dielectrics on printed antennas. These types of investigations could provide valuable in-formation in the design of printed antennas in harsh environments.Finally, the problem of designing magneto-dielectric materials that intrinsically provide distortionless propagation for TEM mode signals is investigated. The frequency dependent permittivity and permeability of a slab are related to the per-unit length (p.u.l.) parameters of a two-conductor transmission line. The p.u.l. parameters are specified to approximate the Heaviside condition in a specified and finite frequency interval, while simultaneously enforcing that the corresponding permittivity and permeability represent a passive material. Consequently, the passivity condition ensures the designed material is possible to realize in practice while the Heaviside condition secures that the material is distortionless. The design method has been employed to design a passive material that approximates the Heaviside condition in a narrow frequency interval. Verification in both time and frequency domains indicates that the designed material closely resembles a distortionless material in the specified frequency interval. These results indicate that an approximation of the Heaviside condition could be a potential aid in the design of distortionless materials for bandlimited applications. Further investigations on design method improvements, limitations on the approximation in terms of both accuracy and bandwidth, and the construction of such materials in practice could lead to new distortionless cable or material designs.
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| 14. |
- Häggström, Fredrik, 1984-
(author)
-
Robust energy management for IoT machine elements
- 2018
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Doctoral thesis (other academic/artistic)abstract
- Advancements in semiconductor technology have reached the point at which ambient energy in the surrounding environment can power sensors and microprocessors. This capability enables new strategies for energy management, which are necessary to continue the sensorization of our environment. With the vast amount of interconnected devices and the rate at which the number of such devices is increasing, there is a need to power resource-constrained devices through means other than disposable batteries. Harvesting ambient energy from the surroundings of the device is one solution to this challenge. It has been estimated that the global demand for bearings will reach 104.5 billion dollars in 2018 with an annual increase of 7.3%. Bearings are mechanical parts that are essential for rotating machinery and that have the potential to measure and monitor vital parts of a machine. A scenario in which bearings contain embedded electronics to monitor process and health parameters that can be analyzed on site and collected from remote locations is a crucial motivator for this thesis. The investigated technologies should be applicable in dirty and encapsulated industrial environments; therefore, vibrational and rotational kinetic energies are considered in this thesis. For each energy source, both the physics and the associated electronics are modeled and to some extent experimentally verified. Vibration harvesters are investigated and modeled in SPICE to verify performance gains using a novel circuit for nonlinear power extraction for piezoelectric materials. The simulations revealed that a weak coupling from the electrical system to the mechanical system would greatly benefit nonlinear extraction techniques. Such a weakly coupled system can be created in a bearing. Mechanical load and rotation generate cyclic strain in the bearing's raceway; the cyclic strain can be utilized by applying piezoelectric patches to the raceway to power embedded systems, and sensory information from the piezoelectric patch can also be used to monitor the bearing. Finally, trends and limits for the energy costs of computing, communication and data acquisition are investigated to determine suitable energy storage technologies to combine with the advancements in energy harvesting for machine elements such as rolling element bearings. The results indicate that high integration between the mechanical and electrical parts is desired, which, in combination with capacitive energy storage, appears to be the long-term direction for real-world implementations.
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| 15. |
- Javed, Salman, 1982-
(author)
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Approach Towards Engineering Microservice-Oriented Composable Ecosystems for Smart Industries
- 2023
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Licentiate thesis (other academic/artistic)abstract
- The emergence of smart and integrated industrial ecosystems is replacing traditional manufacturing, where operations are more digitalized and automated. For communication and cooperation, these operations require seamless integration of the devices to ensure interoperability in a secure, reliable, and adaptable environment. Designing a solution with these capabilities raises concerns about automation and engineering optimization. More recently, the rapid progression toward Industry 5.0 (I5.0) is further reshaping the landscape of smart industry ecosystems, necessitating innovative engineering and management solutions based on its core values of resilience, sustainability, and human-centricity.This thesis investigates these challenges and requirements by emphasizing adaptable, secure, reliable, composable, and scalable communication in complex industrial ecosystems. Central to this work is a local cloud-based collaboration approach to the design and development of composable ecosystems using microservices, which facilitate the integration of various information technology and operational technology (IT/OT) systems prevalent in smart industries. These encompass industrial and smart home Internet of Things (IoT)-based smart industry ecosystems and smart energy systems. Using the microservice-oriented Eclipse Arrowhead framework, this research provides scalable and adaptable solutions that adhere to the core values of I5.0. This research also bridges the integration gap between smart manufacturing ecosystems and smart home IoT technologies, laying the foundation for interconnected smart factories and improved energy management systems.Collaboration between IT/OT components and stakeholders in smart industry and smart energy ecosystems improves competitiveness, productivity, and informed decision making, thereby filling a critical research gap. The thesis presents a cloud-based collaborative learning (CCL) approach for automated condition monitoring in smart industry ecosystems. The thesis exemplifies the use cases of wind farms and smart manufacturing ecosystems that use CCL to address the issues of dynamic learning and real-time data sharing between various IoT-based IT/OT systems. Unlike traditional smart manufacturing models that focus primarily on automation and cost efficiency, CCL-based and I5.0 core value-driven ecosystems support human-centricity, sustainability, and resilience. Lastly, the thesis investigates the optimization of demand response based on collaboration among stakeholders in smart energy systems using edge-based automation clouds. The proposed approach promotes resilient and sustainable smart city demand response strategies by ensuring human comfort, security, data privacy, and all stakeholder integration in smart energy systems.
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| 16. |
- Nilsson, Mattias
(author)
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Using Inhomogeneous Neuronal–Synaptic Dynamics for Spatiotemporal Pattern Recognition in Neuromorphic Processors
- 2021
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Licentiate thesis (other academic/artistic)abstract
- Mixed-signal neuromorphic processors emulate the electrochemical dynamics of neurons and synapses using conventional analog CMOS-transistor technology and have potential for ultra-low-power machine learning and inference. However, the energy-efficiency of such systems is dependent on sparse, time-based information encoding and processing, and they are, furthermore, subject to imprecision from “device mismatch” in the analog circuitry. Hence, there is a need for methods for neuromorphic computing based on principles of dynamic neural processing for efficient use and programming of these low-power but inhomogeneous systems.In this thesis, inspiration is drawn from a temporal feature-detection circuit in crickets for the design of a disynaptic delay element—based on excitatory–inhibitory balance—which induces neuronal excitation-delays for resource-efficient coincidence-based pattern recognition. Due to the inhomogeneous dynamics, such disynaptic elements generate a distribution of temporal delays when implemented in mixed-signal hardware, both between and within single neurons. Here, this is utilized as a source of the variability needed for spatiotemporal information representation for processing and learning—as a resource-efficient alternative to dedicated axonal or neuronal delays or emulation of dendritic dynamics.In experiments with a DYNAP-SE neuromorphic processor, connected in a closed loop with a PC and a digital oscilloscope, disynaptic delays of up to 100 ms were characterized, with an intraneuronal variability of order 10 ms. Using the disynaptic delays, spatiotemporal receptive fields with up to five dimensions per hardware neuron were investigated in a Spatiotemporal Correlator (STC) type neural network, as well as in some simple networks inspired by the auditory system of crickets. The energy dissipation of the balanced synaptic elements is one order of magnitude lower per lateral connection (0.65 nJ vs 9.6 nJ per spike) than the original hardware implementation of the STC.Thus, it is shown how the inhomogeneous synaptic circuits could be utilized for resource-efficient implementation of STC-type network layers, in a way that enables synapse-address reprogramming as a discrete mechanism for feature tuning. The presented approach may serve as a complement to more accurate but resource-intensive delay-based coincidence detection or dendritic integration, offering a digital network-state representation and adaptation concept that can fully benefit from the inhomogeneous analog neurosynaptic dynamics in the forward pass.
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| 17. |
- Palm, Emanuel, 1987-
(author)
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Architectures for Automated Contractual Cooperation
- 2021
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Doctoral thesis (other academic/artistic)abstract
- Every agreement freely entered into is a contract. Some are stated in front of witnesses, other are implied by actions, while yet other are meticulously recorded in lengthy documents. They specify the terms of collaboration and allow for disputes to be settled in a court of law. Given their ubiquity, it stands to reason that the potential benefits from digitalizing contracting are enormous. Computers are faster and more consistent than humans are, and they could be capable of analyzing, negotiating, verifying and performing contracts more effectively than humans ever could. However, for digital contracts to be as useful as the ones they replace, they must also be as general-purpose.In this thesis, we contextualize and present the research that culminated in our Contract Network Architecture, which facilitates automatable and general-purpose collaborations by allowing for Ricardian contracts to be negotiated digitally. Furthermore, we outline (1) a method for pruning transactions from blockchains without loosing the ability to derive certain states, (2) a formalism for translating message payloads between encodings without risk of information loss, (3) Kalix, a Java 11 library for Eclipse Arrowhead system-of-systems development, and (4) the predecessor to the architecture we just mentioned, the Exchange Network Architecture.In comparison to other proposed solutions for digital collaboration, our architectures do not have to rely on a blockchain, or other disruptive kind of distributed ledger technology. In addition, neither of them relies on the smart contract, which sidesteps current contractual praxis by being a computer program rather than a conventional contract. This means that the current contractual paradigm can be preserved if using our solution, which should make it an attractive area of pursuit for industrial actors, and others, wishing to have a general-purpose method of collaboration.
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| 18. |
- Paniagua, Cristina
(author)
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Architectural approach for Autonomous System of Systems Interoperability
- 2019
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Licentiate thesis (other academic/artistic)abstract
- The current technological environment is evolving increasingly fast, and the development of new devices, technologies, and architectures has opened an emergent era where the digital and physical world work together. The implementation and use of systems based on a service-oriented architecture (SOA) in conjunction with the Internet of Things (IoT) and cyberphysical systems (CPS) have been extended during the last decades in numerous scenarios in industry and other domains. However, some of the major barriers to this approach are the lack of interoperability and the amount of engineering effort required for their integration. The research presented in this thesis targets issues related to digitalization and automation. It is framed by the Industry 4.0 paradigm, which promotes the rise of efficiency and sustainability on industrial production. The interoperability between heterogeneous systems and different domains is one of the main challenges of Industry 4.0. The quest for solutions that help to increase interoperability is an important part of this research. This thesis proposes a set of architectural design principles and tools in order to reduce engineering effort by means of finding solutions that enable autonomous integration and increase interoperability without human intervention. The research is focused on the IoT field, taking into account resource-constrained devices, system of systems integration, and data models. A detailed investigation of various interoperability mismatch problems is presented in this thesis. The proposed solution is an adapter system that can aid in the generation of new service consumer interfaces at both compile-time and run-time. The proposed approach requires a new point of view in the service description field that can provide a holistic description of the information required for the generation of consumer interfaces.In addition, aspects related to interoperability, such as the multiple IoT frameworks in the current market, naming conventions, syntactic modeling and translation, and security, are also partially analyzed. On a separate track, service composition in resource-constrained devices is analyzed in terms of latency, using the orchestration provided by the Arrowhead Framework.
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| 19. |
- Vattaparambil Sudarsan, Sreelakshmi, 1996-
(author)
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Digital Power of Attorney for Authorization in Industrial Cyber-Physical Systems
- 2023
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Doctoral thesis (other academic/artistic)abstract
- Since ancient times, there has been a practice to authorize individuals that we trust. Today, we grant credentials and privileges digitally, making authorization a crucial part of security control and extending its use cases beyond people and web applications. Authorization plays an important role in emerging technologies such as the Internet of Things (IoT) and Cyber-Physical Systems (CPS), and there is a trend toward intelligent devices such as autonomous vehicles that are capable of executing tasks on our behalf. However, there are challenges in facilitating this evolution. Industrial use cases with many devices, contractors, subcontractors, and other parties need to maintain trust by sub-granting in one or many steps to define a trust chain. Ultimately Industrial CPS and semi-autonomous devices should be authorized to work as agents with defined credentials on behalf of their contractor. This would enable them to function self-sufficiently at a target site or network for a set amount of time.The scope of this thesis is a new way of authorization known as the Digital Power of Attorneys. Traditionally, Power of Attorney is a legal document that is used for granting a person's authority to a trusted individual to act/work (e.g., running a business) on behalf of the first person. The objective of this thesis is to develop digital Power of Attorney based authorization for Cyber-Physical Systems and the Internet of Things. This technique enables devices (agents) such as autonomous or semi-autonomous devices to work/act on behalf of human beings (principals), even if he/she is not available online. The literature study includes both academic concepts and industrial authorization solutions, protocols, and standards such as OAuth, UMA, GNAP, and ACE. PoA based authorization is inspired by the concept of proxy signatures by warrants and developed for industrial use, both as stand-alone libs and as extensions to existing standard protocols. The major standards that we propose to be extended with the PoA based authorization are IETF standards OAuth and ACE. In this way, the work in this thesis is highly correlated with the IETF. In addition to the academic papers on PoA based authorization and its applications, this thesis includes IETF Internet-Drafts as part of the standardization process of the PoA based authorization technique. The development of PoA based authorization technique begins with designing a Proof-of-Concept based on the gaps identified in existing authorization techniques. For implementation in current networks, different ways of providing PoA-based authorization are explored. First, by extending the OAuth protocol as a new OAuth grant type to add the principal entity to the OAuth protocol that can delegate the client. Second, by extension of the ACE framework, which adds a notion of PoA based delegation to ACE. Third, by implementing an open-source library that can be downloaded and used independently by each entity to interpret the PoA. These approaches address the PoA interpretation challenges and enable every entity being part of the process to use and verify PoAs.This thesis defines the architecture, protocol flow, and PoA structure of the proposed authorization technique and demonstrates its implementation in several use cases such as zero touch-device onboarding and delegation of smart devices in a mining station. Furthermore, possible security threats and vulnerabilities of the proposed system are thoroughly analyzed using different approaches such as threat modeling, risk assessment, and exploiting the system in the context of different attack scenarios.
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