Evolving technology in wireless telecommunication, such as 5G, provides opportunities to utilize wireless communication more in an industrial setting where reliability and predictability are of great concern. More capable Industrial Internet of Things devices (IIoT) are, indeed, a catalyst for Industry 4.0. Still, before the IIoT devices can be deemed capable enough, a method to evaluate the IIoT systems unobtrusively—so that the evaluation does not affect the performance of the systems—must be established. This thesis aims to answer how the performance of a distributed control system can be unobtrusively evaluated, and also determine what the state-of-the-art is in latency measurements in distributed control systems. To answer the question, a novel diagnostics method for time-critical control systems in cloud-fog automation is proposed and extensively evaluated on real-life testbeds that use 5G, WiFi 6, and Ethernet in an edge-computing topology with real control systems. The feasibility of the proposed method was verified by experiments conducted with a diagnostics framework prototype developed in this thesis. In the proposed diagnostics framework, the controller application is monitored by a computing probe based on an extended Berkeley Packet Filter program. Network communication between the controller and control target is evaluated with a multi-channel Ethernet probe and custom-made software that computes several metrics related to the performance of the distributed system. The data from the unobtrusive probes are sent to a time-series database that is used for further analysis and real-time visualization in a graphical interface created with Grafana. The proposed diagnostics method together with the developed prototype can be used as a research infrastructure for future evaluations of distributed control systems.

This thesis aims to investigate a digital, emerging business model, which just enjoys the highest attention in many industrial sectors. The industry 4.0 changes how original equipment manufacturers (OEMs) retain their competitiveness and offer innovative solutions to their customers. Therefore, this master thesis investigates the diverse opportunities of usage-based business models – namely Pay-per-X / Equipment-as-a-Service – from the perspective of a sensor-tech start-up. The company, which can act as a technical enabler for Pay-per-X, is located in Germany and has various markets leading machine and component manufacturers as customers. This projects’ goal is to get an in-depth understanding of the business model and how the company (with their technology) can participate in the market, which is estimated to have a size of 131.2m USD in 2025. Therefore, mainly qualitative research methods have been applied – however, quantitative sections enrich the analysis part of the thesis. Nine expert interviews were conducted, and a calculation tool was developed, which aims to easily convince OEMs of the new business models through modeling a business case, by incorporation of the most relevant parameters. Two use cases were analyzed in the fields of production machines and commercial vehicles. This is followed by a short excursus to a required Pay-per-X cloud software, where requirements were defined based on machine users’ needs. Based on these insights, a positioning strategy for the case company within this field is proposed later-on, which puts emphasis on how the firm can act as a technical enabler for Pay-per-X business models. / Syftet med denna avhandling är att undersöka en ny digital affärsmodell som just nu får stor uppmärksamhet inom många industrisektorer. Industri 4.0 förändrar hur tillverkare av originalutrustning behåller sin konkurrenskraft och erbjuder innovativa lösningar till sina kunder. Därför undersöker denna masteruppsats de olika möjligheterna med användningsbaserade affärsmodeller - nämligen Pay-per-X / Equipment-as-a-Service - ur ett startupföretag inom sensorteknik. Företaget, som kan fungera som en teknisk möjliggörare för Pay-per-X, är beläget i Tyskland och har olika marknadsledande maskin- och komponenttillverkare som kunder. Projektets mål är att få en djupgående förståelse för affärsmodellen och hur företaget (med sin teknik) kan delta på marknaden, som beräknas ha en storlek på 131,2 miljoner US-dollar år 2025. Därför har huvudsakligen kvalitativa forskningsmetoder tillämpats - men kvantitativa avsnitt berikar analysdelen av avhandlingen. Nio expertintervjuer genomfördes och ett beräkningsverktyg utvecklades, som syftar till att enkelt övertyga OEMs om de nya affärsmodellerna genom att modellera ett affärscase, genom att införliva de mest relevanta parametrarna. Två användningsfall analyserades inom områdena produktionsmaskiner och kommersiella fordon. Detta följs av en kort utflykt till en nödvändig Pay-per-X-molnmjukvara, där kraven definierades utifrån maskinanvändarnas behov. På grundval av dessa insikter föreslås senare en positioneringsstrategi för fallföretaget inom detta område, som lägger tonvikten på hur företaget kan fungera som en teknisk möjliggörare för Pay-per-X-affärsmodeller.

Low-power wireless technology is a part and parcel of our daily life, shaping the way in which we behave, interact, and more generally live. The ubiquity of cheap, tiny, battery-powered devices augmented with sensing, actuation, and wireless communication capabilities has given rise to a ``smart" society, where people, machines, and objects are seamlessly interconnected, among themselves and with the environment. Behind the scenes, low-power wireless protocols are what enables and rules all interactions, organising these embedded devices into wireless networks, and orchestrating their communications. The recent years have witnessed a persistent increase in the pervasiveness and impact of low-power wireless. After having spawned a wide spectrum of powerful applications in the consumer domain, low-power wireless solutions are extending their influence over the industrial context, where their adoption as part of feedback control loops is envisioned to revolutionise the production process, paving the way for the Fourth Industrial Revolution. However, as the scale and relevance of low-power wireless systems continue to grow, so do the challenges posed to the communication substrates, required to satisfy ever more strict requirements in terms of reliability, responsiveness, and energy consumption. Harmonising these conflicting demands is far beyond what is enabled by current network stacks and control architectures; the need to timely bridge this gap has spurred a new wave of interest in low-power wireless networking, and directly motivated our work. In this thesis, we take on this challenge with a main conceptual and technical tool: concurrent transmissions (CTX), a technique that, by enforcing nodes to transmit concurrently, has been shown to unlock unprecedented fast, reliable, and energy efficient multi-hop communications in low-power wireless networks, opening new opportunities for protocol design. We first direct our research endeavour towards industrial applications, focusing on the popular IEEE 802.15.4 narrowband PHY layer, and advance the state of the art along two different directions: interference resilience and aperiodic wireless control. We tackle radio-frequency noise by extensively analysing, for the first time, the dependability of CTX under different types, intensities, and distributions of reproducible interference patterns, and by devising techniques to push it further. Specifically, we concentrate on CRYSTAL, a recently proposed communication protocol that relies on CTX to rapidly and dependably collect aperiodic traffic. By integrating channel hopping and noise detection in the protocol operation, we provide a novel communication stack capable of supporting aperiodic transmissions with near-perfect reliability and a per-mille radio duty cycle despite harsh external interference. These results lay the ground towards the exploitation of CTX for aperiodic wireless control; we explore this research direction by co-designing the Wireless Control Bus (WCB), our second contribution. WCB is a clean-slate CTX-based communication stack tailored to event-triggered control (ETC), an aperiodic control strategy holding the capability to significantly improve the efficiency of wireless control systems, but whose real-world impact has been hampered by the lack of appropriate networking support. Operating in conjunction with ETC, WCB timely and dynamically adapts the network operation to the control demands, unlocking an order-of-magnitude reduction in energy costs w.r.t. traditional periodic approaches while retaining the same control performance, therefore unleashing and concretely demonstrating the true ETC potential for the first time. Nevertheless, low-power wireless communications are rapidly evolving, and new radios striking novel trade-offs are emerging. Among these, in the second part of the thesis we focus on ultra-wideband (UWB). By providing hitherto missing networking primitives for multi-hop dissemination and collection over UWB, we shed light on the communication potentialities opened up by the high data throughput, clock precision, and noise resilience offered by this technology. Specifically, as a third contribution, we demonstrate that CTX not only can be successfully exploited for multi-hop UWB communications but, once embodied in a full-fledged system, provide reliability and energy performance akin to narrowband. Furthermore, the higher data rate and clock resolution of UWB chips unlock up to 80% latency reduction w.r.t. narrowband CTX, along with orders-of-magnitude improvements in network-wide time synchronization. These results showcase how UWB CTX could significantly benefit a multitude of applications, notably including low-power wireless control. With WEAVER, our last contribution, we make an additional step towards this direction, by supporting the key functionality of data collection with an ultra-fast convergecast stack for UWB. Challenging the internal mechanics of CTX, WEAVER interleaves data and acknowledgements flows in a single, self-terminating network-wide flood, enabling the concurrent collection of different packets from multiple senders with unprecedented latency, reliability, and energy efficiency. Overall, this thesis pushes forward the applicability and performance of low-power wireless, by contributing techniques and protocols to enhance the dependability, timeliness, energy efficiency, and interference resilience of this technology. Our research is characterized by a strong experimental slant, where the design of the systems we propose meets the reality of testbed experiments and evaluation. Via our open-source implementations, researchers and practitioners can directly use, extend, and build upon our contributions, fostering future work and research on the topic.

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.

This paper is a practical and empirical investigation into the relationship and overlap between the two industrial paradigms of Lean Management and Industry 4.0. This is accomplished with an in-depth case study of a goods receipt to identify Lean wastes and accompanied by a discussion on how these wastes can be eliminated by enhancing the processes and material flows with Industry 4.0 technologies. It was found that efforts to enhance a process with Industry 4.0 Technologies should be preceded by ensuring that the process can be performed in a standardized manner. After that the study recommends improved methods of data collection which enables the effective implementation of other supporting Industry 4.0 Technologies. / Denna uppsats är en praktisk och empirisk utredning av relationen och samspelet mellan de två industriella paradigmen Lean Management och Industri 4.0. Till grund för det för det ligger en utförlig fallstudie av en godsmottagning för att identifiera Lean slöserier och en tillhörande diskussion om hur dessa slöserier kan elimineras genom att förbättra arbetsprocesser och materialflöden med Industri 4.0 och tillhörande teknologier. Ur det uppdagades att åtgärder för göra processer mer effektiva med dessa Industri 4.0 teknologier bör föregås av att processen kan utföras på ett standardiserat vis. När det är säkerställt så är det denna studies rekommendation att fokusera på metoder och verktyg för insamling av data vilket blir den grund som möjliggör implementering av behjälpliga och automatiserande Industri 4.0 teknologier.

This paper is a practical and empirical investigation into the relationship and overlap between the two industrial paradigms of Lean Management and Industry 4.0. This is accomplished with an in-depth case study of a goods receipt to identify Lean wastes and accompanied by a discussion on how these wastes can be eliminated by enhancing the processes and material flows with Industry 4.0 technologies. It was found that efforts to enhance a process with Industry 4.0 Technologies should be preceded by ensuring that the process can be performed in a standardized manner. After that the study recommends improved methods of data collection which enables the effective implementation of other supporting Industry 4.0 Technologies. / Denna uppsats är en praktisk och empirisk utredning av relationen och samspelet mellan de två industriella paradigmen Lean Management och Industri 4.0. Till grund för det för det ligger en utförlig fallstudie av en godsmottagning för att identifiera Lean slöserier och en tillhörande diskussion om hur dessa slöserier kan elimineras genom att förbättra arbetsprocesser och materialflöden med Industri 4.0 och tillhörande teknologier. Ur det uppdagades att åtgärder för göra processer mer effektiva med dessa Industri 4.0 teknologier bör föregås av att processen kan utföras på ett standardiserat vis. När det är säkerställt så är det denna studies rekommendation att fokusera på metoder och verktyg för insamling av data vilket blir den grund som möjliggör implementering av behjälpliga och automatiserande Industri 4.0 teknologier.

More dynamic markets, shorter product life cycles and comprehensive variant management are challenges that dominate today's market. These maxims apply to the automotive sector, which is currently highly exposed to trade wars, changing mobility patterns and the emergence of new technologies and competitors. To meet these challenges, this thesis presents the creation of a digital twin of an existing production line of electric motors using discrete event simulation. Based on a detailed literature research, a step-by-step establishment of the simulation model of the production line using the software Plant Simulation is presented and argued. Finally, different experiments are carried out with the created model to show how a production line can be examined and optimized by means ofsimulation using different parameters. Within the scope of the different experiments regarding the number of workpiece carriers, number of operators as well as buffer sizes, the line was examined concerning the increase of the output. Furthermore, the simulation model was used to make decisions for future investments in additional XXX machines. Four different scenarios were examined and optimized. By examining the different parameters, optimization potentials of XXX% in the first scenario and up to XXX% in the fourth scenario were achieved. Finally, it was proven that the developed simulation model can be used as a tool for optimizing an existing production line and can generate useful investment information. Beyond that, the development of the simulation model can be employed to investigate further business questions at hand for the specific production line in question. / Mer dynamiska marknader, kortare produktlivscykler och omfattande varianthantering är utmaningar som dominerar dagens marknad. Dessa maximer gäller bilindustrin, som för närvarande är mycket utsatt för handelskrig, förändrade rörlighetsmönster och framväxten av ny teknik och nya konkurrenter. För att möta dessa utmaningar innebär denna avhandling skapandet av en digital tvilling av en befintlig produktionslinje av elmotorer med diskret händelsesimulering. Baserat på en detaljerad litteraturforskning presenteras och argumenteras en steg-för-steg-etablering av simuleringsmodellen för produktionslinjen med hjälp av programvaran Plant Simulation. Slutligen utförs olika experiment med den skapade modellen för att visa hur en produktionslinje kan undersökas och optimeras med hjälp av simulering med hjälp av olika parametrar. Inom ramen för de olika experimenten när det gäller antalet arbetsstyckesbärare, antalet operatörer samt buffertstorlekar undersöktes linjen om ökningen av produktionen. Dessutom användes simuleringsmodellen för att fatta beslut för framtida investeringar i ytterligare hårnålsmaskiner. Fyra olika scenarier undersöktes och optimerades. Genom att undersöka de olika parametrarna uppnåddes optimeringspotentialer på XXX % i det första scenariot och upp till XXX % i det fjärde scenariot. Slutligen bevisades det att den utvecklade simuleringsmodellen kan användas som ett verktyg för att optimera en befintlig produktionslinje och kan generera användbar investeringsinformation. Utöver detta kan utvecklingen av simuleringsmodellen användas för att undersöka ytterligare affärsfrågor till hands för den specifika produktionslinjen i fråga.

<div>The coming of the Internet of things (IoT) has enabled manufacturers, teachers, machine operators, makers, and researchers to design and use new workflows, fabricate parts efficiently and effectively, and interact with systems and devices in ways that were not possible before.</div><div>These networked systems have changed the way in which input is received from and data is outputted to humans. Context-awareness and autonomy are characteristics of these devices that result in automated processes, faster production times, and more intuitive interfaces. Direct manipulation is an intuitive and natural human-computer interaction (HCI) that enables its users an easy and fast learning.</div><div>In this thesis, an Internet of things architecture is designed and implemented to enable control and data visualization in machines and devices through immersive interfaces using direct manipulation. The proposed architecture and interfaces are tested and validated approaching three different categories of systems; namely, systems that need to be modified to be IoT ready, systems that are IoT ready, and systems that have not yet been constructed. For the latter case, a custom system has been made to evaluate and test the whole architecture and its implementation. The knowledge acquired in developing this architecture and the design rationale behind the development of immersive interfaces, are summarized and presented as a series of guidelines and recommendations for IoT systems manufacturers to follow to include immersive interfaces in their designs.</div>

The new Industry 4.0 technologies have the potential to increase the operational performance of lean-driven manufacturing organizations, however, there is a lack of guidance on how to select and implement Industry 4.0 technologies which often leads to digital waste. In essence, these organizations want to preserve the value of their current lean manufacturing system, without missing out on improved operational performance potential from exploiting new I4.0 technologies. Furthermore, recent research suggests that there is a complementary effect between lean manufacturing and Industry 4.0 where higher use of both domains in a factory results in higher operational performance. However, in theory, it has not been established what influencing factors lead to the increase in operational performance when the two domains, lean manufacturing and Industry 4.0, are in high concurrent use. The purpose of this study is to identify the influencing factors in the implementation process of Industry 4.0 technologies that facilitate higher Industry 4.0 maturity within factories. In this case study, a qualitative method was used to obtain the empirical data by conducting a series of interviews with individuals working in a multi-national lean-driven manufacturing organization. From a thematic analysis, seven influencing factors were identified that contributed to higher Industry 4.0 maturity: three in the governance structure, two in the selection of Industry 4.0 technologies, and two in the implementation of Industry 4.0 technologies. In the governance structure, a shared digital vision, following a roadmap, and a standardized way of working with digitalization in place facilitated a more successful implementation process. In the selection, a demand-based selection and identification of a business case around the Industry 4.0 technology increased the possibility of the technology selected reaching an implementation stage. Further, in the implementation, having local cross-functional teams and actively developing the employees' knowledge, and providing training in digitalization resulted in more successful implementations. Further, a ripple effect was seen between the influencing factors: having an effective governance structure led to more demand-based selections and thereby more successful implementations that resulted in higher Industry 4.0 maturity. / De nya industri 4.0 teknologierna har potentialen att öka de operativa resultaten inom lean-drivna industriföretag, men det saknas vägledning för hur man väljer och implementerar industri 4.0 teknologier vilket oftast resulterar i digitalt slöseri. Industriföretagen vill bevara värdet av de lean-drivna tillverkningssystemen utan att gå miste om förbättrade resultat med hjälp av industri 4.0. Dessutom tyder den senaste forskningen på att det finns en kompletterande effekt mellan lean produktion och industri 4.0 teknologier, där högre användning av båda domänerna i en fabrik resulterar i bättre operativa resultat. I teorin har det dock inte fastställts vilka de påverkande faktorerna är som leder till ett förbättrat operativt resultat när de två domänerna, lean-produktion och industri 4.0, används i hög grad samtidigt. Syftet med studien är att identifiera vilka de påverkande faktorerna är i implementeringsprocessen av industri 4.0 teknologier som främjar en högre mognadsgrad av industri 4.0 i tillverkningsfabriker. I fallstudien användes en kvalitativ metod för att erhålla empirin genom att utföra en serie av intervjuer med individer som arbetar på ett multinationellt lean-drivet industriföretag. Utifrån en tematisk analys identifierades sju påverkande faktorer som bidrog till en högre mognadsgrad av industri 4.0: tre i styrningsstrukturen, två i valet av industri 4.0 teknologier och två i implementeringen av industri 4.0 teknologier. I styrningsstrukturen återfanns att en delad vision, att följa en roadmap och att ha ett standardiserat arbetssätt för digitalisering främjade en mer framgångsrik implementeringsprocess. Inom valet av teknologier återfanns att ett val baserat på efterfrågan och generering av ett business case för industri 4.0 teknologier ökade möjligheten för den valda teknologin att nå en implementeringsfas. Till sist, i implementeringsfasen visade det sig att lokala tvärfunktionella team och att aktivt utveckla medarbetarnas kunskaper, samt att ge utbildning i digitalisering, resulterade i mer framgångsrika implementeringar. Slutligen sågs en kedjeeffekt mellan de påverkande faktorerna, nämligen att ha en effektiv styrningsstruktur ledde till fler val baserade på efterfrågan och därmed fler framgångsrika implementeringar vilket resulterade i en högre mognadsgrad av industri 4.0.

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.