The umbrella term industry 4.0 stands for the ongoing integration of modern smart technologies in industrial settings. The implementation of the technologies it covers has been an ongoing process for a decade. However, there is a huge variation in companies adaptation of these technologies and progress is slow. This master’s thesis is conducted in collaboration with Cybercom Group and aims to investigate what is keeping the adaptation of Industry 4.0 technologies from taking of. This study was mainly tackled through qualitative interviews with nine different Swedish industry companies. In these interviews their opinions and thoughts on the current state of their factory in contrast to the industry 4.0 vision were discussed. This study reveals that limitations such as high costs on IoT sensors, unsure return of investment, battery constraints on IoT devices, unstable availability on IoT devices connected to the cloud and a general lack of knowledge hampers the adaptation of Industry 4.0 technologies. Finally we provide a price approximation for the monthly cost of streaming data to the three biggest cloud providers (AWS, Microsoft Azure and Google Cloud) for a use case of 8 sensors monitoring a blasting machine. This case shows that the price models of AWS and Google cloud is better suited for smaller cases than Azures while both AWS and Azures price models outperforms Google clouds price model at larger scales.

The new reality is about connectivity. From social media to collaborative tools in work environments, people and their devices are highly intercommunicated. This reality also affects the manufacturing industry, which has been developing standards to keep up with technology and take advantage of it. These technologies are encompassed in what has been called Industry 4.0. Out of all the technologies, apart from artificial intelligence, the main drives of Industry 4.0 are considered by many studies augmented reality (AR) and industrial internet of things (IIoT). This thesis suggests that these drivers have been mostly tested either in an isolated fashion or with limited connectivity. The main objective is to explore the advantages of connecting AR, IIoT, and the main source of information in the manufacturing process: product lifecycle management (PLM) systems. Two sub-objectives are extracted from the main one: to study of value created from real-time role-dependent AR information displaying, and to study how the connection AR-IIoT-PLM can affect developing and deploying times of AR experiences. To achieve the mentioned objectives, a case of study is built, and the combined system implemented on it. Following design and creation methodology, an artefact is created, and conclusions are extracted from the design, implementation, and usage stages. Main results are an improvement in developing and deploying time of AR experiences, along with guidelines to extract as much value as possible from the implementation of a combined system of this sort. This thesis includes a discussion section, where the potential of the system is explained and framed within the near future of manufacturing companies.

Indiana University-Purdue University Indianapolis (IUPUI) / 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: 1. Developing a generic platform for the monitoring energy consumption of industrial equipment using sensors 2. Control the connected equipment using an actuator 3. Integrating hardware, cloud, and application algorithms into the platform 4. Validating the system using an Energy Consumption Forecast scenario A Demo station was created for testing the system. The demo station consists of equip- ment 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.

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.

Industry 4.0 has introduced technologies such as machine learning, Internet of Things (IoT), and cloud computing, which has disrupted markets across different industries. These technologies are prime examples of what has come to be known as disruptive innovations. With the advancement of disruptive innovations, organizations are constantly looking for new ways to satisfy customer needs. Therefore, organizations have begun to investigate alternative business models that differ from the conventional way of selling products/services. Within B2C-markets, the rise of subscription-based services has not gone unnoticed and has turned into a prominent business model among Fortune-500 organizations. Within B2B-practices however, subscription-based business models are mostly unheard of. Therefore, the purpose of this study was to examine how IndustryInternet of Things (IIoT) solution providers successfully can transition to a subscription-based business model when launching IoT-based disruptive innovations in industry 4.0 B2B-markets. This purpose was investigated in a quantitative study by constructing a questionnaire based on an adjusted six-factor Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model. The model was used to stipulate factors influencing buying intention for IoT-technologies. The study was further complemented by qualitative interviews, which aimed to shed more light on buyer's perception of subscription-based business models for IoT-technologies. The respondents consisted of purchasing function employees within the chemical-, food and beverage-, and life sciences industries in Scandinavia and the US. The quantitative results showed that performance expectancy had the most significant impact on buying intention. The qualitative results stipulated themes based on each UTAUT2 factor while also enlightening how interviewees emphasize the importance of not hiding costs and raised concerns regarding the transfer of data ownership when purchasing IoT-technologies. To conclude, the authors stipulated a conceptual framework for the implementation of subscription-based business models when introducing of IoT-technologies within B2B-markets.

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.

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.

The concept of Industrial Internet of Things (IIoT) is the tangible building block for the realisation of the fourth industrial revolution. It should improve productivity, efficiency and reliability of industrial automation systems, leading to revenue growth in industrial scenarios. IIoT needs to encompass various disciplines and technologies to constitute an operable and harmonious system. One essential requirement for a system to exhibit such behaviour is reliable exchange of information. In industrial automation, the information life-cycle starts at the field level, with data collected by sensors, and ends at the enterprise level, where that data is processed into knowledge for business decision making. In IIoT, the process of knowledge discovery is expected to start in the lower layers of the automation hierarchy, and to cover the data exchange between the connected smart objects to perform collaborative tasks. This thesis aims to assist the comprehension of the processes for information exchange in IIoT-enabled industrial automation- in particular, how reliable exchange of information can be performed by communication systems at field level given an underlying wireless sensor technology, and how data analytics can complement the processes of various levels of the automation hierarchy. Furthermore, this work explores how an IIoT monitoring system can be designed and developed. The communication reliability is addressed by proposing a redundancy-based medium access control protocol for mission-critical applications, and analysing its performance regarding real-time and deterministic delivery. The importance of the data and the benefits of data analytics for various levels of the automation hierarchy are examined by suggesting data-driven methods for visualisation, centralised system modelling and distributed data streams modelling. The design and development of an IIoT monitoring system are addressed by proposing a novel three-layer framework that incorporates wireless sensor, fog, and cloud technologies. Moreover, an IIoT testbed system is developed to realise the proposed framework. The outcome of this study suggests that redundancy-based mechanisms improve communication reliability. However, they can also introduce drawbacks, such as poor link utilisation and limited scalability, in the context of IIoT. Data-driven methods result in enhanced readability of visualisation, and reduced necessity of the ground truth in system modelling. The results illustrate that distributed modelling can lower the negative effect of the redundancy-based mechanisms on link utilisation, by reducing the up-link traffic. Mathematical analysis reveals that introducing fog layer in the IIoT framework removes the single point of failure and enhances scalability, while meeting the latency requirements of the monitoring application. Finally, the experiment results show that the IIoT testbed works adequately and can serve for the future development and deployment of IIoT applications. / SMART (Smarta system och tjänster för ett effektivt och innovativt samhälle)

Die Industrie 4.0 führt aktuell zu revolutionären Veränderungen und Herausforderungen im Industriesektor, auf die Unternehmen mit neuen Geschäftsmodellen reagieren müssen. Die Masterarbeit gibt mit Hilfe einer Status-Quo Analyse eine Bestandsaufnahme über die aktuellen digitalen Geschäftsmodelle deutscher Industrieunternehmen. Die Erkenntnisse wurden auf Basis von 71 \'Mini-Cases\' erhoben. Dabei wurden Anbieter, sowie Anwender von Industrie 4.0 Technologien untersucht und in neun Muster kategorisiert. Auf Grundlage dieser Ergebnisse wurde ein inkrementeller Transformationsprozess konzipiert, der zur Entwicklung von digitalen Geschäftsmodellen in der Industrie 4.0 genutzt werden kann.