Submitted by Johnny Rodrigues (johnnyrodrigues@ufcg.edu.br) on 2018-05-09T17:24:59Z No. of bitstreams: 1 LENARDO CHAVES E SILVA - TESE PPGCC 2015..pdf: 9863003 bytes, checksum: b4ff7a7517f3ec159596b4b3c8730219 (MD5) / Made available in DSpace on 2018-05-09T17:24:59Z (GMT). No. of bitstreams: 1 LENARDO CHAVES E SILVA - TESE PPGCC 2015..pdf: 9863003 bytes, checksum: b4ff7a7517f3ec159596b4b3c8730219 (MD5) Previous issue date: 2015-11-12 / Capes / Sistemas Médicos Físico-Cibernéticos (SMFC) são sistemas críticos cientes de contexto que têm a segurança do paciente como principal requisito, demandando processos rigorosos de validação para garantir a conformidade com os requisitos do usuário e a corretude orientada à especificação. Neste trabalho é proposta uma arquitetura baseada em modelos para validação de SMFC, focando em promover a reúso e a produtividade. Tal abordagem permite que desenvolvedores de sistemas construam modelos formais de SMFC baseados em uma biblioteca de modelos de pacientes e dispositivos médicos, bem como simular o SMFC para identificar comportamentos indesejados em tempo de projeto. A abordagem proposta foi aplicada a três diferentes cenários clínicos para avaliar seu potencial de reúso para diferentes contextos. A abordagem foi também validada por meio de uma avaliação empírica com desenvolvedores para avaliar o reúso e a produtividade. Finalmente, os modelos foram formalmente verificados considerando os requisitos funcionais e de segurança, além da cobertura dos modelos. / Medical Cyber-Physical Systems (MCPS) are context-aware, life-critical systems with patient safety as the main concern, demanding rigorous processes for validation to guarantee user requirement compliance and specification-oriented correctness. In this article, we propose a model-based approach for early validation of MCPS, focusing on promoting reusability and productivity. It enables system developers to build MCPS formal models based on a library of patient and medical device models, and simulate the MCPS to identify undesirable behaviors at design time. Our approach has been applied to three different clinical scenarios to evaluate its reusability potential for different context. We have also validated our approach through an empirical evaluation with developers to assess productivity and reusability. Finally, our models have been formally verified considering functional and safety requirements and model coverage.

Idag pratas det mycket om smart teknik och man säger att den fjärde industriella revolutionen är på väg. Revolutionen kallas för Industri 4.0 och innebär två tekniska förbättringar, Internet of Things (IoT) och Cyber-Physical Systems (CPS). IoT låter fysiska enheter sammankopplas i ett system med andra enheter med hjälp av elektromagnetiska vågor och CPS ger möjligheten till att få in information från omvärlden och implementera informationen i digital form. När det kommer till implementering i tillverkningsindustrin används begreppen Industrial Internet of Things och Cyber-Physical Production Systems. Arbetet består av en djupgående litteraturstudie och undersöker vad implementering av IoT och CPS i personbilsbranschens tillverkningssystem kan leda till och hur de fungerar i praktiken. Teorin utgår från vetenskapliga artiklar, tidskrifter och journaler samt en studie från Atlas Copco. Eftersom att smart teknik är ett brett ämne och vi behövde förhålla oss till en tidsgräns på 18 veckor avgränsades arbetet till endast IoT och CPS i tillverkande personbilsföretag. Branschen för personbilar valdes för att i jämförelse med andra branscher är både kvaliteten och kvantiteten avgörande. Samtidigt som det produceras många personbilar måste varje personbil uppfylla en rad olika krav och varje enhet utgör en betydande del av kapitalet i företaget. Resultatet visar hur IoT och CPS fungerar som helhet och vad för positiva och negativa konsekvenser implementering av begreppen ger. Av resultatet framgår också att faktorerna produktion, ekonomi och människa ska analyseras som en helhet och inte enskilt för att implementeringen ska vara framgångsrik i tillverkande personbilsföretag. Möjligheterna som IoT och CPS medför är snabbare och exaktare beslut, systemövervakning och insamling, utbyte och analysering av data för personbilsbranschens företag. Den största utmaningen som implementeringen av begreppen medför är datahantering. Det finns en risk att oönskade mottagare får tillgång till konfidentiell information genom bland annat dataläckage och dataintrång. Således bör fokus ligga på att förebygga detta för att få ut fördelarna och samtidigt reducera nackdelarna. Slutsatsen som kan dras av resultatet är att en kombination av IoT och CPS i personbilsbranschens tillverkningssystem skapar ett kommunikationsnätverk bland heterogena enheter som gör att system kan kommunicera och utbyta data med varandra på ett effektivt sätt. Implementering av begreppen leder till minskning av defekter, introduktionskostnader, energianvändning och upplärning för arbetare samt ökad verktygsdrift och produktivitet. / Today, there is much talk about smart technology and it is said that the fourth industrial revolution is on its way. The revolution is called Industry 4.0 and involves two technical improvements, the Internet of Things (IoT) and Cyber-Physical Systems (CPS). IoT allows physical devices to be interconnected in a system with other devices using electromagnetic waves and CPS provides the opportunity to get information from the outside world and implement the information in digital form. When it comes to implementation in the manufacturing industry, the concepts Industrial Internet of Things and Cyber-Physical Production Systems are used. The thesis consists of an in-depth literature study and investigates what implementation of IoT and CPS in the automotive industry's manufacturing system can lead to and how they work in practice. The theory is based on scientific articles, paper and journals, and a study by Atlas Copco. Because smart technology is a broad topic and we needed to relate to a time limit of 18 weeks, the work was limited to IoT and CPS only in manufacturing passenger car companies. The industry for passenger cars was chosen so that, in comparison with other industries, both the quality and the quantity are decisive. While many passenger cars are being produced, each passenger car must meet a variety of requirements and each unit constitutes a significant part of the capital of the company. The result shows how IoT and CPS work as a whole and what positive and negative consequences the implementation of the concepts gives. The result also shows that the factors of production, economy and humanity should be analysed as a whole and not individually in order for the implementation to be successful in manufacturing passenger car companies. The opportunities that IoT and CPS entail are faster and more precise decisions, system monitoring and collection, exchange and analysis of data for the automotive industry's companies. The biggest challenge that the implementation of the concepts entails is data management. There is a risk that unwanted recipients will have access to confidential information through, among other things, data leakage and hacking. Thus, the focus should be on preventing this in order to get the benefits and at the same time reduce the disadvantages. The conclusion that can be drawn from the result is that IoT and CPS in the automotive industry's manufacturing system create a communication network among heterogeneous units that enable systems to communicate and exchange data with each other in an efficient manner. Implementation of the concepts leads to a reduction of defects, introduction costs, energy use and training for workers, as well as increased tool operation and productivity.

Nous abordons des problèmes de sécurité dans des systèmes cyber-physiques industriels. Les attaques contre ces systèmes doivent être traitées à la fois en matière de sûreté et de sécurité. Les technologies de contrôles imposés par les normes industrielles, couvrent déjà la sûreté. Cependant, du point de vue de la sécurité, la littérature a prouvé que l’utilisation de techniques cyber pour traiter la sécurité de ces systèmes n’est pas suffisante, car les actions physiques malveillantes seront ignorées. Pour cette raison, on a besoin de mécanismes pour protéger les deux couches à la fois. Certains auteurs ont traité des attaques de rejeu et d’intégrité en utilisant une attestation physique, p. ex., le tatouage des paramètres physiques du système. Néanmoins, ces détecteurs fonctionnent correctement uniquement si les adversaires n’ont pas assez de connaissances pour tromper les deux couches. Cette thèse porte sur les limites mentionnées ci-dessus. Nous commençons en testant l’efficacité d’un détecteur qui utilise une signature stationnaire afin de détecter des actions malveillantes. Nous montrons que ce détecteur est incapable d’identifier les adversaires cyber-physiques qui tentent de connaître la dynamique du système. Nous analysons son ratio de détection sous la présence de nouveaux adversaires capables de déduire la dynamique du système. Nous revisitons le design original, en utilisant une signature non stationnaire, afin de gérer les adversaires visant à échapper à la détection. Nous proposons également une nouvelle approche qui combine des stratégies de contrôle et de communication. Toutes les solutions son validées à l’aide de simulations et maquettes d’entraînement / We address security issues in cyber-physical industrial systems. Attacks against these systems shall be handled both in terms of safety and security. Control technologies imposed by industrial standards already cover the safety dimension. From a security standpoint, the literature has shown that using only cyber information to handle the security of cyber-physical systems is not enough, since physical malicious actions are ignored. For this reason, cyber-physical systems have to be protected from threats to their cyber and physical layers. Some authors handle the attacks by using physical attestations of the underlying processes, f.i., physical watermarking to ensure the truthfulness of the process. However, these detectors work properly only if the adversaries do not have enough knowledge to mislead crosslayer data. This thesis focuses on the aforementioned limitations. It starts by testing the effectiveness of a stationary watermark-based fault detector, to detect, as well, malicious actions produced by adversaries. We show that the stationary watermark-based detector is unable to identify cyber-physical adversaries. We show that the approach only detects adversaries that do not attempt to get any knowledge about the system dynamics. We analyze the detection performance of the original design under the presence of adversaries that infer the system dynamics to evade detection. We revisit the original design, using a non-stationary watermark-based design, to handle those adversaries. We also propose a novel approach that combines control and communication strategies. We validate our solutions using numeric simulations and training cyber-physical testbeds

In the era of Industry 4.0, the Internet-of-Things (IoT) plays the driving role comparable to steam power in the first industrial revolution. IoT provides the potential to combine machine-to-machine (M2M) interaction and real time data collection within the field of manufacturing. Therefore, the adoption of IoT in industry enhances dynamic optimization, control and data-driven decision making. However, the domain suffers due to interoperability issues, with massive numbers of IoT devices connecting to the internet despite the absence of communication standards upon. Heterogeneity is pervasive in IoT ranging from the low levels (device connectivity, network connectivity, communication protocols) to high levels (services, applications, and platforms). The project investigates the current state of industrial IoT (IIoT) ecosystem, to draw a comprehensive understanding on interoperability challenges and current solutions in supporting of IoT-based smart manufacturing. Based upon a literature review, IIoT interoperability issues were classified into four levels: technical, syntactical, semantic, and organizational level interoperability. Regarding each level of interoperability, the current solutions that addressing interoperability were grouped and analyzed. Nine reference architectures were compared in the context of supporting industrial interoperability. Based on the analysis, interoperability research trends and challenges were identified. FIWARE Generic Enablers (FIWARE GEs) were identified as a possible solution in supporting interoperability for manufacturing applications. FIWARE GEs were evaluated with a scenario-based Method for Evaluating Middleware Architectures (MEMS).  Nine key scenarios were identified in order to evaluate the interoperability attribute of FIWARE GEs. A smart manufacturing use case was prototyped and a test bed adopting FIWARE Orion Context Broker as its main component was designed. The evaluation shows that FIWARE GEs meet eight out of nine key scenarios’ requirements. These results show that FIWARE GEs have the ability to enhance industrial IoT interoperability for a smart manufacturing use case. The overall performance of FIWARE GEs was also evaluated from the perspectives of CPU usage, network traffic, and request execution time. Different request loads were simulated and tested in our testbed. The results show an acceptable performance in terms with a maximum CPU usage (on a Macbook Pro (2018) with a 2.3 GHz Intel Core i5 processor) of less than 25% with a load of 1000 devices, and an average execution time of less than 5 seconds for 500 devices to publish their measurements under the prototyped implementation. / I en tid präglad av Industry 4.0, Internet-of-things (IoT) spelar drivande roll jämförbar med ångkraft i den första industriella revolutionen. IoT ger potentialen att kombinera maskin-till-maskin (M2M) -interaktion och realtidsdatainsamling inom tillverkningsområdet. Därför förbättrar antagandet av IoT i branschen dynamisk optimering, kontroll och datadriven beslutsfattande. Domänen lider dock på grund av interoperabilitetsproblem, med enorma antal IoT-enheter som ansluter till internet trots avsaknaden av kommunikationsstandarder på. Heterogenitet är genomgripande i IoT som sträcker sig från de låga nivåerna (enhetskonnektivitet, nätverksanslutning, kommunikationsprotokoll) till höga nivåer (tjänster, applikationer och plattformar). Projektet undersöker det nuvarande tillståndet för det industriella IoT (IIoT) ekosystemet, för att få en omfattande förståelse för interoperabilitetsutmaningar och aktuella lösningar för att stödja IoT-baserad smart tillverkning. Baserat på en litteraturöversikt klassificerades IIoT-interoperabilitetsfrågor i fyra nivåer: teknisk, syntaktisk, semantisk och organisatorisk nivå interoperabilitet. När det gäller varje nivå av driftskompatibilitet grupperades och analyserades de nuvarande lösningarna för adressering av interoperabilitet. Nio referensarkitekturer jämfördes i samband med att stödja industriell driftskompatibilitet. Baserat på analysen identifierades interoperabilitetstrender och utmaningar. FIWARE Generic Enablers (FIWARE GEs) identifierades som en möjlig lösning för att stödja interoperabilitet för tillverkningstillämpningar. FIWARE GEs utvärderades med en scenariebaserad metod för utvärdering av Middleware Architectures (MEMS). Nio nyckelscenarier identifierades för att utvärdera interoperabilitetsattributet för FIWARE GEs. Ett smart tillverkningsfodral tillverkades med prototyper och en testbädd som antog FIWARE Orion Context Broker som huvudkomponent designades. Utvärderingen visar att FIWARE GE uppfyller åtta av nio krav på nyckelscenarier. Dessa resultat visar att FIWARE GE har förmågan att förbättra industriell IoT-interoperabilitet för ett smart tillverkningsfodral. FIWARE GEs totala prestanda utvärderades också utifrån perspektivet för CPU-användning, nätverkstrafik och begär exekveringstid. Olika förfrågningsbelastningar simulerades och testades i vår testbädd. Resultaten visar en acceptabel prestanda i termer av en maximal CPU-användning (på en Macbook Pro (2018) med en 2,3 GHz Intel Core i5-processor) på mindre än 25% med en belastning på 1000 enheter och en genomsnittlig körningstid på mindre än 5 sekunder för 500 enheter att publicera sina mätningar under den prototyperna implementateringen.

Sammanfattning Industri 4.0 tyder på den senaste fasen av industrialiseringen och fokuserar på digitalisering, automatisering och datautbyte. Den fjärde industriella revolutionen, Industri 4.0, bygger på tidigare industriella revolutioner och använder sig av olika teknologier såsom IoT, Big Data Analytics och Cloud Services. Inom inköpsprocessen innebär Industri 4.0 ett behov att effektivisera och uppnå flexibla processer för att möta ökade krav på innovation och kvalitet. Syftet med arbetet är att identifiera och analysera användningen av Industri 4.0-teknologier i inköpsprocessen för att förbättra effektiviteten. Forskningsfrågorna fokuserar på vilka teknologier som används i inköpsprocessen och på vilket sätt de används samt att analysera deras roll i att förbättra effektiviteten. Arbetet begränsas till inköpsprocessen inom supply chain management och använder en strukturerad litteraturgenomgång som metod. Användningen av IoT, CPS, Big Data-analys, Blockchain och Cloud Services automatiserar och effektiviserar inköpsaktiviteter. IoT används för realtidsövervakning och automatiserad påfyllning av lager. CPS samordnar både digitala och fysiska komponenter i syfte att förbättra spårbarhet och beslutsfattande. Big Data-analys förutser efterfrågan samt utvärderar leverantörers prestationer. Blockchain säkerställer transparenta och säkra transaktioner med hjälp av smarta kontrakt. Cloud Services hanterar realtidsdata och förbättrar kommunikation och samarbete i leveranskedjan. Dessa teknologier spelar en central roll för effektiviseringen i inköpsprocessen där manuella lager minskar, leverantörsförhandlingar effektiviseras och efterfrågeprognoser, spårbarhet och beslutsfattande förbättras. Det ökar i sin tur transparensen, säkerställer transaktioner och underlättar strategiska beslut, vilket leder till förbättrad effektivitet, resursförvaltning och konkurrenskraft. Syfte  Syftet med arbetet är att sammanställa information om Industri 4.0-teknologier med hjälp av systematisk litteraturgenomgång för att identifiera användningen av teknologierna i inköpsprocessen samt analysera vilken roll dessa teknologier spelar för att förbättra effektiviteten. Metod  En systematisk litteraturgenomgång genomfördes för att samla in relevant data som i sin tur användes för att analysera och besvara forskningsfrågorna. / Abstract Industry 4.0 signifies the latest phase of industrialization, focusing on digitalization, automation, and data exchange, utilizing different technologies to increase productivity and competitiveness. This work aims to identify and analyze the use of Industry 4.0 technologies in the procurement process to improve efficiency. The research questions focus on which technologies are used and their role in improving efficiency, limited to the procurement process within supply chain management, using a structured literature review as a method. The use of IoT, CPS, Big Data Analytics, Blockchain, and Cloud Services automates procurement activities. IoT is used for real-time monitoring and automated inventory replenishment. CPS coordinates both digital and physical components in order to improve traceability and decision-making. Big Data Analytics forecasts demand as well as evaluates supplier performance. Blockchain ensures transparent and secure transactions with the help of smart contracts. Cloud Services manage real-time data and improve communication and collaboration in the supply chain. These technologies play a central role in effectiveness for the procurement process where manual inventories decrease, supplier negotiations become more efficient and demand forecasts, traceability, and decision-making improve. This, in turn, increases transparency, ensures transactions, and facilitates strategic decisions, leading to improved efficiency, resource management, and competitiveness. Purpose  The purpose of the work is to compile information on Industry 4.0 technologies using a systematic literature review to identify the use of technologies in the purchasing process and analyze what role these technologies play in improving efficiency. Methodology  A systematic literature review was conducted to gather relevant data which in turn was used to analyze and answer the research questions.

<p dir="ltr">Cyber-physical-human systems (CPHSs) integrate human cognitive capabilities into the decision and control processes of complex dynamical systems. While artificial intelligence (AI) has shown promise in controlling such systems, it often encounters challenges such as conflict with human behavior and brittleness. Moreover, even successful AI implementations may lead to negative impacts on humans, such as the degradation of manual skills and diminished situation awareness, thereby weakening humans' ability to effectively monitor and intervene in off-nominal conditions as the final decision-makers of the systems. To address these unique challenges within CPHSs, this dissertation proposes three key approaches. First, human behavior modeling approaches are proposed to enhance understanding and prediction of human behavior from the perspective of AI. Accurate modeling enables better calibration of AI's expectations regarding human teammates' intentions and skill-levels. Second, a novel shared control approach is developed to expedite human training for complex dynamic control tasks. An assistant agent supports human novices in emulating human experts by leveraging human behavior models to gauge the human's skill-levels and provide tailored assistance to help improve one's skill. Lastly, human-autonomy teaming (HAT) design is addressed from a resource allocation perspective. A systematic computational simulation approach is proposed to optimize function and attention allocation to manage trade-offs in performance, situation awareness, workload, and other considerations. The proposed frameworks are demonstrated via examples in drone applications. Numerical and experimental results, utilizing simulation platforms and human subjects, validate the efficacy of the proposed approaches. This dissertation presents significant progress in the design and implementation of CPHSs in that it offers insights and methodologies to enhance collaborative interactions between humans and autonomous systems in complex environments.</p>

Doctor of Philosophy / Department of Computing and Information Sciences / Gurdip Singh / Cyber-Physical Systems (CPSs) represent the next-generation systems characterized by strong coupling of computing, sensing, communication, and control technologies. They have the potential to transform our world with more intelligent and efficient systems, such as Smart Home, Intelligent Transportation System, Energy-Aware Building, Smart Power Grid, and Surgical Robot. A CPS is composed of a computational and a physical subsystem. The computational subsystem monitors, coordinates and controls operations of the physical subsystem to create desired physical effects, while the physical subsystem performs physical operations and gives feedback to the computational subsystem. This dissertation contributes to the research of CPSs by proposing a new transaction model for Environmental Resource Dependent Cyber-Physical Systems (ERDCPSs). The physical operations of such type of CPSs rely on environmental resources, and they are commonly seen in areas such as transportation and manufacturing. For example, an autonomous car views road segments as resources to make movements and a warehouse robot views storage spaces as resources to fetch and place goods. The operating environment of such CPSs, CPS Network, contains multiple CPS entities that share common environmental resources and interact with each other through usages of these resources. We model physical operations of an ERDCPS as a set of transactions of different types that achieve different goals, and each transaction consists of a sequence of actions. A transaction or an action may require environmental resources for its operations, and the usage of an environmental resource is precise in both time and space. Moreover, a successful execution of a transaction or an action requires exclusive access to certain resources. Transactions from different CPS entities of a CPS Network constitute a schedule. Since environmental resources are shared, transactions in the schedule may have conflicts in using these resources. A schedule must remain consistent to avoid unexpected consequences caused by resource usage conflicts between transactions. A two-phase commit algorithm is proposed to process transactions. In the pre-commit phase, a transaction is scheduled by reserving usage times of required resources, and potential conflicts are detected and resolved using different strategies, such as Win-Lose, Win-Win, and Transaction Preemption. Two general algorithms are presented to process transactions in the pre-commit phase for both centralized and distributed resource management environments. In the commit phase, a transaction is executed using reserved resources. An exception occurs when the real-time resource usage is different from what has been predicted. By doing internal and external check before a scheduled transaction is executed, exceptions can be detected and handled properly. A simulation platform (CPSNET) is developed to simulate the transaction model. The simulation platform simulates a CPS Network, where different CPS entities coordinate resource usages of their transactions through a Communication Network. Depending on the resource management environment, a Resource Server may exist in the CPS Network to manage resource usages of all CPS entities. The simulation platform is highly configurable and configuration of the simulation environment, CPS entities and two-phase commit algorithm are supported. Moreover, various statistical information and operation logs are provided to monitor and evaluate the platform itself and the transaction model. Seven groups of simulation experiments are carried out to verify the simulation platform and the transaction model. Simulation results show that the platform is capable of simulating a large load of CPS entities and transactions, and entities and components perform their functions correctly with respect to the processing of transactions. The two-phase commit algorithm is evaluated, and the results show that, compared with traditional cases where no conflict resolving is applied or a conflicting transaction is directly aborted, the proposed conflict resolving strategies improve the schedule productivity by allowing more transactions to be executed and the scheduling throughput by maintaining a higher concurrency level.

Today, many embedded or cyber-physical systems, e.g., in the automotive domain, comprise several control applications, sharing the same platform. It is well known that such resource sharing leads to complex temporal behaviors that degrades the quality of control, and more importantly, may even jeopardize stability in the worst case, if not properly taken into account. In this thesis, we consider embedded control or cyber-physical systems, where several control applications share the same processing unit. The focus is on the control-scheduling co-design problem, where the controller and scheduling parameters are jointly optimized. The fundamental difference between control applications and traditional embedded applications motivates the need for novel methodologies for the design and optimization of embedded control systems. This thesis is one more step towards correct design and optimization of embedded control systems. Offline and online methodologies for embedded control systems are covered in this thesis. The importance of considering both the expected control performance and stability is discussed and a control-scheduling co-design methodology is proposed to optimize control performance while guaranteeing stability. Orthogonal to this, bandwidth-efficient stabilizing control servers are proposed, which support compositionality, isolation, and resource-efficiency in design and co-design. Finally, we extend the scope of the proposed approach to non-periodic control schemes and address the challenges in sharing the platform with self-triggered controllers. In addition to offline methodologies, a novel online scheduling policy to stabilize control applications is proposed.

Purpose: The purpose of this paper is to identify the opportunities that Industry 4.0 brings within the framework of applying Cyber Physical Systems in an environment of a Smart Factory. This paper shall identify the changes within daily business processes and the impact of these changes on the daily business life. Design/Methodology/Approach: The research is carried out as a case study research. Due to a qualitative approach for this case study interviews are conducted and the results are analyzed and discussed. Findings: Industry 4.0 will change the way we are working today and influence businesses and business processes in many ways. Data handling, processes and efficiency will change and the way we perceive manufacturing will change in a long term view. Further Research: It would be recommended to expand this research by conducting more research in this particular field as well as impacts on the employee should be studied more in detail.

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