With the rise of Industry 4.0 and the 4:th industrial revolution withthe Internet of Things, infrastructures have become more prevalent to connect and monitor many different systems within an industrial set-ting. With many candidates for this IoT infrastructure, there is a need to evaluate the different candidates to determine the different strengthsand weaknesses of the infrastructure.This thesis investigates the use of the Eclipse Arrowhead framework in the application of scalable infrastructure used for predictive mainte-nance. This investigation is conducted by converting an existing pre-dictive maintenance implementation that is using Amazon Web Services as the IoT infrastructure into a predictive maintenance implementationusing the Eclipse Arrowhead framework as the infrastructure.This design science artifact which results from this thesis shows that the Eclipse Arrowhead framework is suitable for a scalable infrastruc-ture though some shortcomings of the framework were found during the implementation. And though it is a suitable infrastructure, the usage ofthe framework should depend on the specific needs of the infrastructureand should not be used as a “one size fits all” solution.

Industrial automation is critical in today's industry. The majority of new scientific and technological advancements are either enabling technologies or industrial automation application areas. In the past, the two main forms of control systems were distributed control systems (DCS) and programmable logic controllers (PLCs). PLCs have been referred as the "brain" of production systems because they provide the capacity to meet interoperability, reconfigurability, and portability criteria. Today's industrial automation systems rely heavily on control software to ensure that the automation process runs smoothly and efficiently. Furthermore, requirements like flexibility, adaptability, and robustness add to the control software's complexity. As a result, new approaches to building control software are required. The International Electrotechnical Commission attempted to meet these new and impending demands with the new IEC 61499 family of standards for distributed automation systems. The IEC 61499 standard specifies a high-level system design language for distributed data and control. With the advancement of these technologies like edge/fog computing and IIoT, how the control software in future smart factory managed is discussed here. This study aims to do a systematic literature review on PLC, software containers, edge/fog computing and IIoT for future industrial use. The objective is to identify the correspondence between the functional block (IEC 61499) and the container technology such as Docker. The impact of edge computing and the internet of things in industrial automation is also analysed. Since the aim is to do a comparative study, a qualitative explorative study is done, with the purpose to gather rich insight about the field. The analysis of the study mainly focused on four major areas such as deployment, run time, performance and security of these technologies. The result shows that containerisation or container based solutions is the basis for future automation as it outperforms virtual machines in terms of deployment, run time, performance and security.

Establishing secured communication among the different entities in an industrial environment is a major concern. Especially with the introduction of the Industrial Internet of Things (IIoT), industries have been susceptible to cyber threats, which makes security a critical requirement for the industries. Prevailing industrial communication standards were proven to meet the security needs to some extent, but the major issue which was yet to be addressed was interoperability. To achieve interoperability, Open Platform Communication Unified Architecture (OPC UA) was introduced as a communication protocol. OPC UA helped bridge the gap between Information Technology (IT) and Operational Technology (OT) security needs, but this also gives rise to new attack opportunities for the intruder. In this thesis, we have analysed the security challenges in OPC UA and the impact of two different cyberattacks on the OPC UA. First, we have implemented an OPC UA Network with the help of Raspberry Pis and open62541, an open-source implementation of the OPC UA client and server. Following this, to evaluate the performance of the network, we performed three cybersecurity attacks, Packet Sniffing, Man in the Middle Attack (MITM) and Denial of Service attack. We assessed the impact these attacks have on the OPC UA network. We have also discussed the detection mechanism for the same attacks. This analysis has helped us recognize the threats faced by OPC UA in an IIoT environment with respect to message flooding, packet sniffing and man in the middle attack and the countermeasures to this attack have been discussed / Att etablera en säker kommunikation mellan de olika enheterna i en industriell miljö är en stor utmaning. Speciellt efter introduktionen av Industrial Internet of Things (IIoT) har industrier varit mottagliga för cyberhot vilket gör cybersäkerhet en prioritet. Rådande industriella kommunikationsstandarder har visats att till viss del uppfylla säkerhets- behoven, men en av de största problemen var bristen på interoperabilitet. För att uppnå interoperabiliteten skapades Open Platform Communication Unified Architecture (OPC UA) som kommun- ikationsprotokoll. OPC UA hjälper till att överbrygga gapet mellan säkerhetsbehoven av information- steknologi (IT) och Operational Technology (OT), men detta ger också upphov till nya attackmöjligheter för inkräktare. I detta examensarbete har vi analyserat säkerhetsutmaningarna i OPC UA och effekten av två olika cyberattacker på OPC UA. Först har vi implementerat ett OPC UA Network med hjälp av Raspberry Pis och open62541 som är en öppen källkodsimplementering av OPC UA klient och server. Efter detta utförde vi tre cybersäkerhetsattacker för att utvärdera nätverkets prestanda, packet sniffing, Man in the Middle Attack (MITM) och Denial of Service attack. Vi bedömde vilken effekt dessa attacker har på OPC UA-nätverket. Vi har också diskuterat detektionsmekanismen för samma attacker. Denna analys har hjälpt oss att känna igen de hot som OPC UA står inför i en IIoT-miljö med avseende på dataflöde, packet sniffing och Man in the Middle attack och även försvar mot dessa attacker har diskuterats.

AstraZeneca är ett medicinskt företag lokaliserat i Södertälje som har cirka 900 luftfilterboxar hos sin anläggning i Gärtuna. Dessa filterboxar kan vara opraktiska att hålla koll på eftersom de är utspridda uppe på vindarna, samt att det behövs bra framförhållning vid filterbyten eftersom vissa filter innehåller farliga ämnen. Filterboxar är utrustade med analoga tryckmätare vilket innebär att det kan bli omständigt för personalen att övervaka filtrets tryckfall. Målet med det här examensarbetet är att hitta en digital lösning som underlättar övervakningen av tryckfall över filter i realtid, samt informerar via sms eller mejl när det är dags att planera in filterbyte. Visionen är att det ska bli enklare att få en bild över luftfiltrets underhållsmässiga skick. Genom att jämföra olika produkter och delta i regelbundna möten med IT kunnig personal valdes en lämplig produkt. Projektet har arbetat metodiskt och strukturerat genom att följa projektmodellen projekt case där verktygen GANTT-schema, SWOT-analys, FMEA och maxiriskmetoden har använts. Projektet resulterade i användningen av digitala differentialtryckgivare som mäter tryckfallet över filter. Differentialtryckgivaren samlar data som sedan skickas via radiofrekvens till en Ethernet gateway som är trådad in till AstraZenecas segregerade nätverk så kallat FAB-net. Därefter förs datan från ethernet gatewayen till mjukvara. I mjukvaran kommer AstraZenecas filtergrupp kunna se över tryckfall hos de olika filtrena i filterboxarna. Detta kommer underlätta personalens arbete och eventuellt spara AstraZeneca tid och pengar. / AstraZeneca is a medical company located in Södertälje that has around 900 air filter boxes at its facility in Gärtuna. These filter boxes can be impractical to keep track of as they are scattered up in the attics and good foresight is needed for multiple filter changes as some filters contain harmful substances. Filter boxes are equipped with analog pressure gauges, which means that there is a lot of walking for the staff in order to monitor the filter's pressure drop. The goal of this thesis is to find a digital solution that can facilitate the monitoring of pressure drops across filters in real time and that also informs by text message or email when it is time to schedule a filter change. The vision is that it will be easier to get a digital image of the maintenance condition of the air filter. By comparing different products and participating in regular meetings with AstraZeneca's IT personnel, a suitable product was chosen. The project has worked methodically and structured by following the project model project case where tools such as GANTT chart, SWOT analysis, FMEA and maxirisk method have been used. The project resulted in the use of digital differential pressure sensors that measure the pressure drop across filters. The differential pressure sensor collects data which is then sent by radio frequency to an ethernet gateway which is wired into AstraZeneca's segregated network called FAB-net. The data is then transferred from the ethernet gateway to the software. AstraZeneca's filter group will be able to review the pressure drop of the various filters within the software, which will facilitate their way of working and potentially save AstraZeneca time and money.

Establishing secured communication among the different entities in an industrial environment is a major concern. Especially with the introduction of the Industrial Internet of Things (IIoT), industries have been susceptible to cyber threats, which makes security a critical requirement for the industries. Prevailing industrial communication standards were proven to meet the security needs to some extent, but the major issue which was yet to be addressed was interoperability. To achieve interoperability, Open Platform Communication Unified Architecture (OPC UA) was introduced as a communication protocol. OPC UA helped bridge the gap between Information Technology (IT) and Operational Technology (OT) security needs, but this also gives rise to new attack opportunities for the intruder. In this thesis, we have analysed the security challenges in OPC UA and the impact of two different cyberattacks on the OPCUA. First, we have implemented an OPC UA Network with the help of Raspberry Pis and open62541, an open-source implementation of the OPC UA client and server. Following this, to evaluate the performance of the network, we performed three cybersecurity attacks, Packet Sniffing, Man in the Middle Attack (MITM) and Denial of Service attack. We assessed the impact these attacks have on the OPC UA network. We have also discussed the detection mechanism for the same attacks. This analysis has helped us recognize the threats faced by OPC UA in an IIoT environment with respect to message flooding, packet sniffing and man in the middle attack and the countermeasures to this attack have been discussed. / Att etablera en säker kommunikation mellan de olika enheterna i en industriell miljö är en stor utmaning. Speciellt efter introduktionen av Industrial Internet of Things (IIoT) har industrier varit mottagliga för cyberhot vilket gör cybersäkerhet en prioritet. Rådande industriella kommunikationsstandarder har visats att till viss del uppfylla säkerhets- behoven, men en av de största problemen var bristen på interoperabilitet. För att uppnå interoperabiliteten skapades Open Platform Communication Unified Architecture (OPC UA) som kommun- ikationsprotokoll. OPC UA hjälper till att överbrygga gapet mellan säkerhetsbehoven av information- steknologi (IT) och Operational Technology (OT), men detta ger också upphov till nya attackmöjligheter för inkräktare. I detta examensarbete har vi analyserat säkerhetsutmaningarna i OPC UA och effekten av två olika cyberattacker på OPC UA. Först har vi implementerat ett OPC UA Network med hjälp av Raspberry Pis och open62541 som är en öppen källkodsimplementering av OPC UA klient och server. Efter detta utförde vi tre cybersäkerhetsattacker för att utvärdera nätverkets prestanda, packet sniffing, Man in the Middle Attack (MITM) och Denial of Service attack. Vi bedömde vilken effekt dessa attacker har på OPC UA-nätverket. Vi har också diskuterat detektionsmekanismen för samma attacker. Denna analys har hjälpt oss att känna igen de hot som OPC UA står inför i en IIoT-miljö med avseende på dataflöde, packet sniffing och Man in the Middle attack och även försvar mot dessa attacker har diskuterats.

<p><strong>The Energy Monitoring Framework</strong>, designed and developed by IAC, IUPUI, aims to provide a cloud-based solution that combines business analytics with sensors for real-time energy management at the plant level using wireless sensor network technology.</p> <p>The project provides a platform where users can analyze the functioning of a plant using sensor data. The data would also help users to explore the energy usage trends and identify any energy leaks due to malfunctions or other environmental factors in their plant. Additionally, the users could check the machinery status in their plant and have the capability to control the equipment remotely.</p> <p>The main objectives of the project include the following:</p> <ul> <li>Set up a wireless network using sensors and smart implants with a base station/ controller.</li> <li>Deploy and connect the smart implants and sensors with the equipment in the plant that needs to be analyzed or controlled to improve their energy efficiency.</li> <li>Set up a generalized interface to collect and process the sensor data values and store the data in a database.</li> <li>Design and develop a generic database compatible with various companies irrespective of the type and size.</li> <li> Design and develop a web application with a generalized structure. Hence the database can be deployed at multiple companies with minimum customization. The web app should provide the users with a platform to interact with the data to analyze the sensor data and initiate commands to control the equipment.</li> </ul> <p>The General Structure of the project constitutes the following components:</p> <ul> <li>A wireless sensor network with a base station.</li> <li>An Edge PC, that interfaces with the sensor network to collect the sensor data and sends it out to the cloud server. The system also interfaces with the sensor network to send out command signals to control the switches/ actuators.</li> <li>A cloud that hosts a database and an API to collect and store information.</li> <li>A web application hosted in the cloud to provide an interactive platform for users to analyze the data.</li> </ul> <p>The project was demonstrated in:</p> <ul> <li>Lecture Hall (https://iac-lecture-hall.engr.iupui.edu/LectureHallFlask/).</li> <li>Test Bed (https://iac-testbed.engr.iupui.edu/testbedflask/).</li> <li>A company in Indiana.</li> </ul> <p>The above examples used sensors such as current sensors, temperature sensors, carbon dioxide sensors, and pressure sensors to set up the sensor network. The equipment was controlled using compactable switch nodes with the chosen sensor network protocol. The energy consumption details of each piece of equipment were measured over a few days. The data was validated, and the system worked as expected and helped the user to monitor, analyze and control the connected equipment remotely.</p> <p><br></p>

<div><div><div><p>This project aims to develop a cloud-based platform that integrates sensors with business intelligence for real-time energy management at the plant level. It provides facility managers, an energy management platform that allows them to monitor equipment and plant-level energy consumption remotely, receive a warning, identify energy loss due to malfunction, present options with quantifiable effects for decision-making, and take actions, and assess the outcomes. The objectives consist of:</p><ol><li><p>Developing a generic platform for the monitoring energy consumption of industrial equipment using sensors</p></li><li><p>Control the connected equipment using an actuator</p></li><li><p>Integrating hardware, cloud, and application algorithms into the platform</p></li><li><p>Validating the system using an Energy Consumption Forecast scenario</p></li></ol><p>A Demo station was created for testing the system. The demo station consists of equipment such as air compressor, motor and light bulb. The current usage of these equipment is measured using current sensors. Apart from current sensors, temperature sensor, pres- sure sensor and CO2 sensor were also used. Current consumption of these equipment was measured over a couple of days. The control system was tested randomly by turning on equipment at random times. Turning on the equipment resulted in current consumption which ensured that the system is running. Thus, the system worked as expected and user could monitor and control the connected equipment remotely.</p></div></div></div>

Commissioning of a machine is still representing a very challenging operation and most steps are still executed manually by commissioning engineers. A future goal is to support the commissioning engineers and further automate the entire integration process of a newly installed system with a minimum of manual effort. This use case is known as plug-and-produce (PnP). In this contribution a concept of the Industrial Internet of Things is presented to improve the commissioning task for a pneumatic handling system. The system is based on a service-oriented architecture. Within this context, information models are developed to meet the requirements of PnP to provide relevant information via virtual representations, e.g. the asset administration shell, of the components to the commissioning process. Finally, a draft of the entire PnP process is shown, providing a general understanding of Industrial Internet of Things fluid power systems.

Technological advances (e.g., high speed communication, artificial intelligence) and affordable computing and sensor hardware have become a key driver of developments like “Industry 4.0” or the “Industrial Internet of Things” (IIoT). Large numbers of machines and products are equipped with sensors to constantly monitor their condition, log usage data or trigger control processes. IIoT has been largely adopted by OEMs in various industries (such as automotive, machinery industry, or healthcare and medical), turning their product into cyber-physical systems. However, the resulting potential is not yet accessible to component manufacturers. Overall, horizontal integration of the value chain is still in its infancy. Specifically, IIoT for fluid powers just started in recent years with first research projects and commercial solutions. This work presents a reference architecture for cyber-physical fluid power systems which depicts how horizontal integration can be achieved and which potentials thus can be released. The architecture is validated in an industrial use case. Furthermore, the paper at hand discusses which components of the architecture should be addressed by which actor in the fluid power ecosystem in order to leverage opportunities from the IIoT.

The manufacturing industry is competitive and is constantly striving to improve OEE. In the transition to smart production, digital technologies such as IIoT are highlighted as important. IIoT platforms enable real-time monitoring. In this sense, digital technologies such as IIoT are expected to improve OEE by enabling the analysis of real-time data and production availability.  A qualitative study with an abductive approach has been conducted. The empirical material has been collected through a case study of a heavy-duty vehicle industry and the theoretical framework is based on a literature study. Lastly, a thematic analysis has been used for the derivation of appropriate themes for analysis. The study concluded that challenges and enablers related to the implementation of IIoT to improve OEE can be divided into technical and cultural factors. Technical challenges and enablers mainly consider the achievement of interoperability, compatibility, and cyber security, while cultural factors revolve around digital acceptance, competence, encouragement of digital curiosity, and creating knowledge and understanding towards OEE. Lastly, conclusions can be drawn that implementation of IIoT has a positive effect on OEE since it ensures consistent and accurate data, which lies a solid foundation for production decisions. Also, digitalization of production enhances lean practices which are considered a key element for improving OEE.