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.

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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Die Zukunft liegt bereits heute schon im Internet der Dinge, Daten, Dienste und Personen. Informations- und Kommunikationstechnologien (IKT) beeinflussen vermehrt die alltäglichen Abläufe, übernehmen im Ernstfall lebenserhaltende Körperfunktionen, unterstützen Arbeits- und Produktionsprozesse und halten Einzug in unsere Wohnbereiche. Dabei rückt der Gedanke einer anwendungsnahen und integrierten Sicht von Software zunehmend in den Vordergrund und verlangt deshalb interdisziplinäre Ansätze. Eine frühzeitige technische Abstimmung zwischen Soft- und Hardware sowie unterschiedlichen technischen Öko-Systemen wird dabei notwendiger und fordert Politik, Wissenschaft und Wirtschaft in gleichem Maße. Das Innovationsforum open4INNOVATION2012 am 9.Mai bot dazu Praktikern und Akademikern eine Plattform für den interdisziplinären und fachbereichsübergreifenden Austausch zu neuen und anwendungsnahen IKT-Ansätzen. Unter dem Motto regional kooperativ, global innovativ galt es dabei regional politische, wirtschaftliche und wissenschaftliche Kompetenzen zu bündeln, um globale Märkte erfolgreich zu bestreiten. In dem vorliegenden Tagungsband finden Sie die Beiträge des Fachforums, welches ein Hauptformat der Veranstaltung darstellte. Zusätzlich kam es auf dem Innovationsforum open4INNOVATION2012 erstmals zur aktiven Vernetzung sächsischer Forschergruppen, deren wissenschaftlicher Schwerpunkt die Robotik ist. Auf diesem ersten sächsischen Robotertreffen stand vor allem die Arbeit mit humanoiden Robotern im Mittelpunkt.

Complex systems are designed using the model-based design paradigm in which mathematical models of systems are created and checked against specifications. Cyber-physical systems (CPS) are complex systems in which the physical environment is sensed and controlled by computational or cyber elements possibly distributed over communication networks. Various aspects of CPS design such as physical dynamics, software, control, and communication networking must interoperate correctly for correct functioning of the systems. Modeling formalisms, analysis techniques and tools for designing these different aspects have evolved independently, and remain dissimilar and disparate. There is no unifying formalism in which one can model all these aspects equally well. Therefore, model-based design of CPS must make use of a collection of models in several different formalisms and use respective analysis methods and tools together to ensure correct system design. To enable doing this in a formal manner, this thesis develops a framework for multi-model verification of cyber-physical systems based on behavioral semantics. Heterogeneity arising from the different interacting aspects of CPS design must be addressed in order to enable system-level verification. In current practice, there is no principled approach that deals with this modeling heterogeneity within a formal framework. We develop behavioral semantics to address heterogeneity in a general yet formal manner. Our framework makes no assumptions about the specifics of any particular formalism, therefore it readily supports various formalisms, techniques and tools. Models can be analyzed independently in isolation, supporting separation of concerns. Mappings across heterogeneous semantic domains enable associations between analysis results. Interdependencies across different models and specifications can be formally represented as constraints over parameters and verification can be carried out in a semantically consistent manner. Composition of analysis results is supported both hierarchically across different levels of abstraction and structurally into interacting component models at a given level of abstraction. The theoretical concepts developed in the thesis are illustrated using a case study on the hierarchical heterogeneous verification of an automotive intersection collision avoidance system.

The work is motivated by the goal of linking reality and model, and to see if there is an opportunity to develop an inexpensive educational tool for training in cyber-physical systems. This project has investigated the possibilities to build a cheap inverted pendulum with controller and connect this with the modeling language Acumen. Acumen models is used for comparison with the actual prototype. To solve these problems has a 3D printer been used to create hardware, Arduino UNO for control and Raspberry Pi for enable communication with Acumen over WLAN. The result was a cheap inverted pendulum, which can be built for a cost around 750 SEK. Graphs created in Acumen and from data collected from sensors can be analyzed. With a model of the inverted pendulum system, the results show that Acumen can be used in the development of cyber-physical systems. There are differences between model and reality but also similarities. / Arbetet motiveras av målet att knyta samman verklighet och modell, samt att se om det finns möjlighet att utveckla ett billigt utbildningsverktyg för utbildning i cyberfysiska system. Detta projekt har undersökt möjligheter att bygga en billig inverterad pendel med regulator samt koppla samman denna med modelleringsspråket Acumen. I Acumen skapa en modell av systemet och jämföra den med en fysisk prototyp. För att lösa dessa problem har en 3D skrivare använts för att skapa hårdvara. Arduino UNO för styrning och Raspberry Pi för att möjligöra kommunikation med Acumen över WLAN. Resultatet blev en billig inverterad pendel, som kan byggas för en kostnad runt 750 kr. Grafer från Acumen, och från data samlad från sensorer kan analyseras. Med en modell av en inverterad pendel visar resultaten att Acumen kan användas i utveckling av cyberfysiska system. Skillnader finns mellan modell och verklighet men även likheter.

abstract: Despite incremental improvements over decades, academic planning solutions see relatively little use in many industrial domains despite the relevance of planning paradigms to those problems. This work observes four shortfalls of existing academic solutions which contribute to this lack of adoption. To address these shortfalls this work defines model-independent semantics for planning and introduces an extensible planning library. This library is shown to produce feasible results on an existing benchmark domain, overcome the usual modeling limitations of traditional planners, and accommodate domain-dependent knowledge about the problem structure within the planning process. / Dissertation/Thesis / Doctoral Dissertation Computer Science 2016