Nowadays Virtual Reality (VR) and Human Robot Collaboration (HRC) are becoming more and more important in Industry as well as science. This investigation studies the applications of these two technologies in the ergonomic field by developing a system able to visualise and present ergonomics evaluation results in real time assembly tasks in a VR Environment, and also, evaluating the advantages of Human Robot Collaboration by studying in Virtual Reality a specific operation carried at Volvo Global Trucks Operation´s factory in Skövde. Regarding the first part of this investigation an innovative system was developed able to show ergonomic feedbacks in real time, as well as make ergonomic evaluations of the whole workload inside of a VR environment. This system can be useful for future research in the Virtual Ergonomics field regarding matters related to ergonomic learning rate of the workers when performing assembly tasks, design of ergonomic workstations, effect of different types assembly instructions in VR and a wide variety of different applications. The assembly operation with and without robot was created in IPS to use its VR functionality in order to test the assembly task in real users with natural movements of the body. The posture data of the users performing the tasks in Virtual Reality was collected. The users performed the task without the collaborative robot and then, with the collaborative robot. Their posture data was collected by using a Motion Capture equipment called Smart Textiles (developed at the University of Skövde) and the two different ergonomic evaluations (Using Smart Textiles’ criteria) of the two different task compared. The results show that when the robot implemented in this specific assembly task, the posture of the workers (specially the posture of the arms) has a great improvement if it is compared to the same task without the robot.

The use of micro controllers in automotive application have exploded during the last half century. What was initially a set of mechanical systems that formed a vehicle have now become a collection of computers on wheels. The reason is quite obvious: micro controllers use several inputs to optimize the performance of systems; for example an engine control or an active safety system.The different inputs and outputs to these electronic units (electronic control unit, ECU) are of interest to other such units thereby justifying the need of inter-ECU communications. The Controller Area Network (CAN) bus has been developed to facilitate this communication. It is a message based protocol and is very resilient. It is however relatively slow and limited in terms of security. Security is assured only by trying to keep the message identification tags confidential and the bus physically separated to other network. A couple of decades ago our society embraced the Information Technology (IT) revolution. It allowed people to have extensive access to information. From a technology point of view, IT is based on the use of the Internet, which has been initially designed by the US military for robust applications. It is fast and its security is sufficiently high that we use it to communicate with our banks where we keep all our life savings.The aim of this thesis has been to combine these technologies such that a vehicle with a CAN bus could offer services (just like a bank does) over the Internet. The goal then is to transform a CAN bus to become a service provider over the Internet. The services are the broadcasted CAN messages made available to authorized interested parties and can post information and actuations to the ECUs connected to the CAN bus. A vehicle in that case becomes a cyber physical system. To make this transformation possible, we use the open source Arrowhead Framework, which is based on a Service Oriented Architecture (SOA). The available services are made known via a Service Registry and Orchestration service prosumers. Concretely, the work in this thesis project has been to develop (i.e., to design and implement) a CAN service prosumer that is Arrowhead Framework compliant. It has been successfully tested with another service prosumer, which is an Arrowhead Framework compliant data logger. The driving motivation for the thesis project are construction equipment machines, such as wheel loaders and excavators, which are vehicles with booms or arms. The aspiration is that they not only drive autonomously but also dig autonomously. This ambition shall require large amount of data to be exchanged, something that a CAN bus cannot handle.

The world of industrial manufacturing has changed a lot during the past decades. It has gone from a labour-intensive process of manual control of machines to a fully connected and automated process. The next big leap in industrial manufacturing is known as industry 4.0 or smart manufacturing. With industry 4.0 comes increased integration between IT systems and the factory floor. This change has proven challenging to implement into existing factories many with the intended lifespan of several decades. One of the single most important parameters to measure is the operating hours of each machine. This information can help companies better utilize their resources and save huge amounts of money.  The goal is to develop a solution which can track the operating hours of the machines using image analysis and the signal lights already mounted on the machines. Using methods commonly used for traffic light recognition in autonomous cars, a system with an accuracy of over 99% during the specified conditions, has been developed. It is believed that if more diverse video data becomes available a system, with high reliability that generalizes well, could be developed using similar methodology. / Industriell tillverkning har förändrats mycket under de senaste decennierna. Det har gått från en process som krävt mycket manuellt arbete till en process som är nästan helt uppkopplad och automatiserad. Nästa stora steg inom industriell tillverkning går under benämningen industri 4.0 eller smart tillverkning. Med industri 4.0 kommer en ökad integration mellan IT-system och fabriksgolvet. Denna förändring har visat sig vara särskilt svår att implementera i redan existerande fabriker som kan ha en förväntad livstid på flera årtionden. En av de viktigaste parametrarna att mäta inom industriell tillverkning är varje maskins operativa timmar. Denna information kan hjälpa företag att bättre utnyttja tillgängliga resurser och därigenom spara stora summor pengar. Målet är att utveckla en lösning som, med hjälp av bildanalys och de signalljus som maskinerna kommer utrustade med, kan mäta maskinernas operativa timmar. Med hjälp av metoder som vanligen används för trafikljusigenkänning i autonoma fordon har ett system med en träffsäkerhet på över 99% under de förutsättningar som presenteras i rapporten utvecklats. Om mer video med större variation blir tillgänglig är det mycket troligt att det går att utveckla ett system som har hög pålitlighet i de flesta produktionsmiljöer.

Atualmente vive-se uma transformação digital na indústria, que está sendo referenciada como uma nova revolução e conhecida como a quarta revolução industrial. Essa nova revolução foi precedida por três anteriores, sendo que a primeira foi baseada no carvão como fonte de energia, impulsionando, assim, as máquinas a vapor e transformando o trabalho artesanal em automatizado; posteriormente, houve a segunda revolução industrial, baseada em conceitos de eletricidade para atingir a produção em massa; já a terceira revolução industrial baseou-se em sistemas eletrônicos e computacionais, tendo como o seu maior expoente os sistemas Supervisory Control and Data Aquisition (SCADA), que foram utilizados para aprimoramento e eficiência da linha de produção. Hoje, vive-se no limiar da quarta revolução industrial, que se apoia fortemente nas tecnologias habilitadoras, tais como: Internet of Things (IoT), machine learning, big data analytics, cyber-physical systems (CPS), machine-to-machine (M2M) e cloud computing. Essas tecnologias, trabalhando cooperativamente, são utilizadas para promover a transformação digital descrita nas visões ao redor do mundo, entre as quais se destacam: Industry 4.0, Industrial Internet Consortium e Manufatura Avançada. A presente pesquisa visa caracterizar as tecnologias habilitadoras, as visões da transformação digital e o cenário Brasil para esta nova realidade. O objetivo central é a definição de uma plataforma de transformação digital aplicada ao cenário da indústria de Utilities. Para a identificação do setor industrial, optou-se pela aplicação de um questionário direcionado às indústrias da região metropolitana de Campinas. Esse questionário serviu para traçar o nível de conhecimento, aderência e perfil profissional desejado pelas empresas relacionadas com a transformação digital. Na análise do questionário para o grupo estudado, verificou-se desconhecimento estratégico sobre a transformação digital e resistência para aplicação dos novos conceitos na cadeia de suprimentos existente. Para suprir esta necessidade e como prova de conceito foi proposta uma plataforma para transformação digital para a questão da água, com o objetivo de alcançar uma gestão eficiente dos recursos atrelada ao uso racional da água. Para a definição da plataforma foi realizado o levantamento de todo o processo de uma planta de tratamento de água, implantada nos moldes da terceira revolução industrial, de modo a melhorar o processo aplicando-se os conceitos da transformação digital na nova plataforma definida. Como resultado, o estudo de caso contribuiu para o projeto PURA-USP juntamente com o projeto SafeCity, do convênio Huawei-USP no âmbito do conceito de cidades inteligentes, integrando a transformação digital na gestão eficiente dos recursos hídricos no campus USP da capital. Adicionalmente, inseriu-se a capacitação técnica também no projeto Huawei-USP, denominada Centro de Internet do Futuro, habilitando e capacitando os profissionais para as novas tecnologias. / Nowadays, there´s a digital transformation in the industry, which is being referred to as a new revolution, known as the fourth industrial revolution. This new revolution was preceded by three previous ones, the first one was based on coal as a way of source energy, boosting the steam engines and turning the manual labor into automated; posteriorly the second industrial revolution was based on electricity concepts to achieve mass production; and the third industrial revolution, which was based on electronics and computer systems, having as its greatest exponent the systems Supervisory Control and Data Acquisition (SCADA) and programmable logic controllers (PLC), which were used for improvement and production line efficiency. Today we are on the bound of the fourth industrial revolution, which strongly supports itself at enabling technologies, such as: Internet of Things (IoT), big data analytics, cyber-physical systems (CPS), machine-to-machine (M2M) and cloud computing. These technologies are working cooperatively used to promote digital transformation described in the sights around the world, between them are: Industry 4.0, Industrial Internet Consortium and Advanced Manufacturing. This research aims to characterize the enabling technologies, the visions of the digital transformation and Brazil scenario for this new reality. The main objective is the definition of a digital transformation platform applied in the industry scenario. To identify the industry it was chosen the application of a questionnaire targeting the industries at the metropolitan region of Campinas. This questionnaire was used to trace the level of knowledge, adherence and professional profile required of companies related to digital transformation. In the questionnaire analysis for the group in the scope there was strategic unfamiliarity about the digital transformation and resistance to application of new concepts in the existing supply chain. To meet this need and as a proof of concept, a platform for digital transformation for the water issue was proposed with the objective of achieve an efficient management of resources linked to the rational use of water. For the platform definition was performed a survey of the whole process of a water treatment plant that was implemented along the lines of the third industrial revolution and improved the process by applying the concepts of digital transformation in the new set platform. The case study aimed to contribute to the PURA-USP project, integrating the digital transformation in the efficient management of water resources on campus USP capital. Additionally, technical training was also included in the Huawei-USP project, denominated the Future Internet Center, enabling and training professionals for new technologies.

The powerful digitization and development of technologies is a fact. As a result, companies are facing the fourth industrial revolution in history; Industry 4.0. To remain competitive, it is important for companies to assimilate Industry 4.0 and its technologies, especially within manufacturing. Industry 4.0 offers numerous opportunities, but the implementation also comes with some challenges that should be taken into account for a successful transition. The aim of this study is to create an understanding of what Industry 4.0 can offer for companies and their manufacturing processes, and which challenges and opportunities that may be involved. This study has been based on research of the phenomenon Industry 4.0 as well as data collection from semi-structured interviews with employees of an industrial manufacturing enterprise. The result of the study can be divided in to 4 separate conclusions that should be taken into account when implementing Industry 4.0. First of all, the company must have a customized strategy to embrace the implementation into their existing structure. Secondly, it is important that all employees are informed and involved about the new procedures to increase understanding as well as motivation. Thirdly, it is important that existing techniques and digital tools within the company are adapted for a transition to Industry 4.0, and they must also have a common standard to facilitate for data management. Finally, if these three areas listed above are taken into account, the implementation of Industry 4.0, can provide real-time information and understanding that contribute to a better overview of the manufacturing, the quality, the efficiency, the work tempo, as well as any problems and downtime. Industry 4.0 also allows for businesses to create a more flexible production and give a good insight and control over the business, including better decision. On top of that, it also cuts the energy consumption as well as many other expenses. Overall, Industry 4.0 offers companies an opportunity to potentially become leading in the global market.

Introduction Industry 4.0 is rapidly approaching the manufacturing industry and are generating multiple challenges for the companies to overcome. Simultaneously, the customer demand is changing towards customisation and the industry requires new technology within the production system development to remain competitive. Therefore, the purpose of this thesis is to develop a framework and assess the maturity towards Industry 4.0 and to provide guidance for further advancement. The following two research questions were defined and answered to guide the authors: ~        RQ1: What dimensions should be considered when assessing the maturity of Industry 4.0? ~        RQ2: How could the maturity assessment of Industry 4.0 be performed?    Methodology A literature review was performed to attain previous results within the area of creating and performing maturity assessment. Further, a multiple case study was performed at a selection of case companies where semi-structured interviews, workshop and observations were used to collect empirical data. The analysis has been performed through a cross case analysis for evaluating patterns between the frame of reference and empirical findings. Frame of Reference The literature review increased the authors understanding of how a maturity assessment model functions and which parameters that creates the foundation. The review mainly focused on what set of dimensions and how many levels that can be used in relation to assess a production system. Empirical Findings The empirical findings provide an overview of the current state of production within each case company. Aspects regarding a transition towards Industry 4.0 is elaborated based on process, technology and people aspects. Analysis and Discussion The synthesis between Frame of Reference and Empirical findings contribute with important dimensions to consider when assessing the maturity model. This thesis has decided to conclude the dimensions into three headings consisting of process, technology and people.  A second contribution is a framework for a maturity assessment towards Industry 4.0, where five levels are defined for each dimension. A concluded picture visualises the case companies’ mean maturity level within each dimension of process, technology and people. Conclusions and Recommendations Provided by the maturity assessment, an initiative towards Industry 4.0 exist within the case companies, although major challenges of defining the concept of Industry 4.0 and a lack of competence is highlighted. Future recommendations are to perform a similar study with more depth into the investigations within each case company to validate the maturity assessment towards Industry 4.0 within each case company.

A Indústria 4.0 surge com o objetivo de desenvolver fábricas inteligentes, com alto grau de autonomia e flexibilidade, através da adoção de tecnologias digitais de forma integrada nas empresas e suas cadeias de valor. Ao mesmo tempo, a Indústria 4.0 promove benefícios que vão além da performance operacional, como o desenvolvimento de novas ofertas e novos modelos de negócios para as empresas. A Indústria 4.0 é originada na Alemanha, país com alta performance tecnológica, e rapidamente inspira outras iniciativas no mundo inteiro, inclusive em países emergentes como o Brasil. Estes países possuem maiores barreiras para a adoção das tecnologias relacionadas ao conceito, principalmente devido à atual situação tecnológica dos seus parques industriais. Embora a Indústria 4.0 seja um tema crescente na literatura, ainda existem grandes lacunas de estudo sobre a adoção de tecnologias relacionadas ao conceito no contexto de países emergentes, principalmente por se tratar de uma iniciativa recente. Logo, o objetivo desta dissertação é estudar o conceito da Indústria 4.0 no Brasil, de forma a entender quais são os benefícios do conceito para a performance industrial e as tecnologias habilitadoras. O trabalho tem uma abordagem quantitativa, com análises estatísticas aplicadas em dados de pesquisas surveys conduzidas em nível nacional. Os principais resultados obtidos foram: (i) identificação da relação entre as tecnologias e os benefícios esperados do conceito, (ii) identificação de disparidades entre a percepção industrial brasileira e a literatura sobre os benefícios da Indústria 4.0, (iii) identificação da abrangência do conceito da Indústria 4.0, compreendendo elementos que transcendem a manufatura avançada, e (iv) identificação de tecnologias habilitadoras para a implantação do conceito. Sob a perspectiva acadêmica, esta dissertação traz importantes contribuições para o entendimento do conceito e das tecnologias da Indústria 4.0, assim como o impacto destas na performance industrial. Do ponto de vista prático, os resultados auxiliam na compreensão de um tema de alta relevância empresarial, contribuindo com perspectivas para a diretriz estratégica das empresas à Indústria 4.0. / Industry 4.0 arises with the goal to develop smart factories, with advanced autonomy and flexibility, through the adoption of digital technologies in an integrated manner in companies and in their value chains. The Industry 4.0enables benefits beyond operational performance, as the development of new offerings and new business models for companies. Industry 4.0 was developed in Germany, a country with high technological performance, and quickly inspires other initiatives in the whole world, in developed and emergent countries such as Brazil. These countries face major barriers for the adoption of technologies related to the concept, mainly due to the current technological level of their industrial sites. Even though Industry 4.0 is a growing field in literature, there are still considerable gaps of studies about the adoption of technologies related to the concept in the context of emergent countries, mostly due to its novelty. Therefore, this dissertation aims to study the concept of Industry 4.0 in Brazil, in order to understand its benefits for industrial performance and its enabling technologies. This study has a quantitative approach, with statistical analysis of data from national surveys. The main outcomes obtained were: (i) the identification of a relation between technologies and the expected benefits of the concept, (ii) the identification of disparities between Brazilian industrial perception and the literature about Industry 4.0 benefits, (iii) the identification of a wide scope of Industry 4.0 concept, comprising elements that transcends smart manufacturing, and (iv) the identification of enabling technologies for the implementation of the concept. Under academic perspective, this dissertation brings important contributions to understand the Industry 4.0 concept and technologies, and its impact on industrial performance. As practical contributions, the results contribute for the understandings of a high relevant theme for companies, contributing with perspectives for their strategical orientation towards Industry 4.0.

Current industrial companies are highly pressured by growing competitiveness and globalization, while striving for increased production effectiveness. Meanwhile, flustered markets and amplified customer demands are causing manufacturers to shift strategy. Hence, international companies are challenged to pursue changes, in order to continue being competitive on global markets. Consequently, a new industrial revolution has taken place, introduced as Industry 4.0. This new concept incorporates organizational improvement and digitalization of current information and data flows. Accomplished by data from embedded systems through connected machines, devices and humans into a combined interface. Thus, companies are given possibilities to improve current production systems, simultaneously saving operational costs and minimizing insufficient production development. Smart Factories, being the foundation of Industry 4.0 results in making more accurate and precise operational decisions from abilities to test industrial changes in a virtual world before real-life implementation. However, in order to assure these functions as intended, enormous amount of data must be collected, analysed and evaluated. The indicated data will aid companies to make more self-aware and automated decisions, resulting in increased effectiveness in production. Thus, the concept will clearly change how operational decisions are made today. Nowadays, Discrete Event Simulation is a commonly applied tool founded on specific data requirements as operational changes can be tested in virtual settings. Accordingly, it is believed that simulation can aid companies that are striving for implementing Industry 4.0. As a result, data requirements between Discrete Event Simulation and Industry 4.0 needs to be established, while detecting the current data gap in operational context. Hence, the purpose of this thesis is to analyse the data requirements of Discrete Event Simulation and Industry 4.0 for improving operational decisions of production systems. In order to justify the purpose, the following research questions has been stated:   RQ1: What are the data challenges in existing production systems? RQ2: What data is required for implementing Industry 4.0 in production systems? RQ3: How can data requirements from Discrete Event Simulation benefit operational decisions when implementing Industry 4.0?   The research questions were answered by conducting a case study, in collaboration with Scania CV AB. The case study performed observations, interviews and other relevant data collection to accomplish the purpose. In parallel, a literature review focusing on data requirements for operational decisions was compared to the empirical findings. The analysis identified the current data gap in existing production systems, in correlation to Industry 4.0, affecting the accuracy of operational decisions. In addition, it was shown that simulation can undoubtedly give positive outcome for adaptation of Industry 4.0, and a clear insight on data requirements.

Atualmente vive-se uma transformação digital na indústria, que está sendo referenciada como uma nova revolução e conhecida como a quarta revolução industrial. Essa nova revolução foi precedida por três anteriores, sendo que a primeira foi baseada no carvão como fonte de energia, impulsionando, assim, as máquinas a vapor e transformando o trabalho artesanal em automatizado; posteriormente, houve a segunda revolução industrial, baseada em conceitos de eletricidade para atingir a produção em massa; já a terceira revolução industrial baseou-se em sistemas eletrônicos e computacionais, tendo como o seu maior expoente os sistemas Supervisory Control and Data Aquisition (SCADA), que foram utilizados para aprimoramento e eficiência da linha de produção. Hoje, vive-se no limiar da quarta revolução industrial, que se apoia fortemente nas tecnologias habilitadoras, tais como: Internet of Things (IoT), machine learning, big data analytics, cyber-physical systems (CPS), machine-to-machine (M2M) e cloud computing. Essas tecnologias, trabalhando cooperativamente, são utilizadas para promover a transformação digital descrita nas visões ao redor do mundo, entre as quais se destacam: Industry 4.0, Industrial Internet Consortium e Manufatura Avançada. A presente pesquisa visa caracterizar as tecnologias habilitadoras, as visões da transformação digital e o cenário Brasil para esta nova realidade. O objetivo central é a definição de uma plataforma de transformação digital aplicada ao cenário da indústria de Utilities. Para a identificação do setor industrial, optou-se pela aplicação de um questionário direcionado às indústrias da região metropolitana de Campinas. Esse questionário serviu para traçar o nível de conhecimento, aderência e perfil profissional desejado pelas empresas relacionadas com a transformação digital. Na análise do questionário para o grupo estudado, verificou-se desconhecimento estratégico sobre a transformação digital e resistência para aplicação dos novos conceitos na cadeia de suprimentos existente. Para suprir esta necessidade e como prova de conceito foi proposta uma plataforma para transformação digital para a questão da água, com o objetivo de alcançar uma gestão eficiente dos recursos atrelada ao uso racional da água. Para a definição da plataforma foi realizado o levantamento de todo o processo de uma planta de tratamento de água, implantada nos moldes da terceira revolução industrial, de modo a melhorar o processo aplicando-se os conceitos da transformação digital na nova plataforma definida. Como resultado, o estudo de caso contribuiu para o projeto PURA-USP juntamente com o projeto SafeCity, do convênio Huawei-USP no âmbito do conceito de cidades inteligentes, integrando a transformação digital na gestão eficiente dos recursos hídricos no campus USP da capital. Adicionalmente, inseriu-se a capacitação técnica também no projeto Huawei-USP, denominada Centro de Internet do Futuro, habilitando e capacitando os profissionais para as novas tecnologias. / Nowadays, there´s a digital transformation in the industry, which is being referred to as a new revolution, known as the fourth industrial revolution. This new revolution was preceded by three previous ones, the first one was based on coal as a way of source energy, boosting the steam engines and turning the manual labor into automated; posteriorly the second industrial revolution was based on electricity concepts to achieve mass production; and the third industrial revolution, which was based on electronics and computer systems, having as its greatest exponent the systems Supervisory Control and Data Acquisition (SCADA) and programmable logic controllers (PLC), which were used for improvement and production line efficiency. Today we are on the bound of the fourth industrial revolution, which strongly supports itself at enabling technologies, such as: Internet of Things (IoT), big data analytics, cyber-physical systems (CPS), machine-to-machine (M2M) and cloud computing. These technologies are working cooperatively used to promote digital transformation described in the sights around the world, between them are: Industry 4.0, Industrial Internet Consortium and Advanced Manufacturing. This research aims to characterize the enabling technologies, the visions of the digital transformation and Brazil scenario for this new reality. The main objective is the definition of a digital transformation platform applied in the industry scenario. To identify the industry it was chosen the application of a questionnaire targeting the industries at the metropolitan region of Campinas. This questionnaire was used to trace the level of knowledge, adherence and professional profile required of companies related to digital transformation. In the questionnaire analysis for the group in the scope there was strategic unfamiliarity about the digital transformation and resistance to application of new concepts in the existing supply chain. To meet this need and as a proof of concept, a platform for digital transformation for the water issue was proposed with the objective of achieve an efficient management of resources linked to the rational use of water. For the platform definition was performed a survey of the whole process of a water treatment plant that was implemented along the lines of the third industrial revolution and improved the process by applying the concepts of digital transformation in the new set platform. The case study aimed to contribute to the PURA-USP project, integrating the digital transformation in the efficient management of water resources on campus USP capital. Additionally, technical training was also included in the Huawei-USP project, denominated the Future Internet Center, enabling and training professionals for new technologies.

Ever since the first industrial revolution industries have had the goal to increase their production. With new technology such as CPS, AI and IoT industries today are going through the fourth industrial revolution denoted as industry 4.0. The new technology not only revolutionises production, but also maintenance, making predictive maintenance possible. Predictive maintenance seeks to predict when failure would occur, instead of having scheduled maintenance or maintenance after failure already occurred. In this report a convolutional neural network (CNN) will analyse data from an ultrasound machine scanning a weld joint. The data from the ultrasound machine will be transformed by the short time Fourier transform in order to create an image for the CNN. Since the data from the ultrasound is not complete, simulated data will be created and investigated as another option for training the network. The results are promising, however the lack of data makes it hard to show any concrete proof.