The aim of the master thesis is to emphasize the importance of process alignment in The Fourth Industrial Revolution. By mapping of current descriptive maturity models and their application within digitalization, the thesis offers a new process maturity model for the phenomenon referred to as Industry 4.0 (i4.0). The model is based on the theoretical form of previous models, as well as on implementation of newly introduced trends. The contribution of the thesis rests upon the specific solution. The suggested Process Improvement Scheme presents applicable way for improvement of digital process preparedness in project-oriented service organizations and determines main value factors which lead to higher quality of employee processes. In the same time, the master thesis suggest a new utilization of i4.0 principles focused predominantly on manufacturing processes, and therefore includes areas which will need to be addressed in the near future for smooth process transition into i4.0 era.

This thesis deals with the importance of chemical industry in the creation of jobs in the Czech Republic between 2008-2015. The Thesis is divided into four chapters. First chapter is devoted to general development of chemical industry, with emphasis on the labour market. Second chapter is concerned with educational institutions within chemical industry. Third chapter examines selected chemical companies and their cooperation with educational institutions. The last chapter focuses on the future of the chemical industry of the Czech Republic with an emphasis on development of the labor market due to ongoing technological changes. The analyse of comprehensive development of the chemical industry is made on the basis of historical-statistical method. In the sections describing the possible development are used mostly specialized studies.

Purpose: To investigate possible connections between an Industrial Internet of Things (IIoT) system, such as Predix, and data driven Lean practises. The aim is to examine if an IIoT platform can improve existing practises of Lean, and if so, which Lean tools are most likely influenced and how this is.Design/Methodology: The paper follows a phenomenon-based research approach. The methodology contains of a mix of primary and secondary data. The primary data was obtained through “almost unstructured” interviews with experts, while the secondary data comprises of a comprehensive review of existing literature. Moreover, a model was developed to investigate the connections between the concepts of IIoT and Lean.Findings: Findings derived from expert interviews at General Electric (GE) in Uppsala have led to the conclusion that Predix fulfils the necessary requirements to be considered an IIoT platform. However, the positive effects of the platform on the selected Lean tools could not be found. Only in one instance improved Predix the effectiveness of a Lean tool. Overall, data analytic efforts are performed and let to better in-process control. However, these efforts were independent from the Lean efforts carried out. There was no increase in data collection or analytics due to the Lean initiative and Predix is not utilised for data collection, storage, or analysis. It appears that the pharmaceutical industry is fairly slow in adapting new technologies. Firstly, the high regulatory requirements inherent within the pharmaceutical industry limit the application of cutting edge technology by demanding strict in-process control and process documentation. Secondly, the sheer size of GE itself slows down the adoption of new technology. Lastly, the pragmatic approach of the top management to align the digital strategies of the various industries and thereof resulting allocation of resources to other more technologically demanding businesses hinders the use of Predix at GE in Uppsala.

The goal of the thesis is to provide investors and established businesses insights into the evolving concept of Internet of Things in the context of a business opportunity. First, the thesis provides comprehensive overview of the IoT concept, its historical development and relevant concepts similar to IoT including its definition and explanation. Second, the thesis discusses IoT as a disruptive technology with implications for general business strategy, current business models, value chains and competitive landscape. Third, it describes overwhelming opportunities for IoT application in various business fields and processes bringing added value to its stakeholders. Visionary concepts and applicable use cases are identified. Finally, the thesis analyses IoT market perception from both customer and business perspective based on quantitative and qualitative data researched. The research is focused mainly on customer awareness and value perception of IoT products as well as major drivers and challenges of the IoT market from business players' perspective. Such analytical insights identify major patterns and dynamism of the IoT market.

Com a chegada da era da computação ubíqua, o número de dispositivos com poder computacional vêm crescendo de forma acelerada. A conexão desses dispositivos em uma rede de comunicação traz novas possibilidades e serve como base para o conceito chamado Internet das Coisas (Internet of Things - IoT). Uma das aplicações desse conceito é no domínio industrial e está impulsionando uma nova revolução industrial, a chamada Indústria 4.0. Esta pesquisa apresenta uma abordagem de integração de componentes de forma automatizada, no contexto da Indústria 4.0, utilizando ontologias para representar os elementos do sistema e um middleware IoT para servir de meio de integração. Essa abordagem utiliza conceitos propostos em trabalhos relacionados, com características inovadoras na criação de sistemas IoT. Dentre estas está a integração automatizada a partir de modelos semânticos, que possibilita que usuários modelem sistemas em alto nível. A partir desse modelo, as interfaces de comunicação são criadas automaticamente, trazendo uma garantia de consistência sintática nas chamadas de métodos ou funções. Além disso, a pesquisa proposta traz a possibilidade de usar esse mesmo modelo semântico para apresentar as informações ao usuário final. Como resultados deste trabalho podem ser ressaltados o desenvolvimento de uma ontologia para modelar esses elementos industriais e também o de uma extensão para um middleware IoT a fim de poder-se trabalhar com esses modelos de forma automatizada. / With the advent of the ubiquitous computing era, the number of devices with computing power is growing rapidly. The connection of these devices onto a communication network brings new possibilities and serves as the basis for the concept called the Internet of Things (IoT). One of the applications of this concept is in the industrial domain where it is driving a new industrial revolution, usually designated as “Industry 4.0”. This research study presents a automated integration approach in the context of Industry 4.0, using ontologies to represent elements of the system and an IoT middleware to provide a means for its integration. This approach uses concepts proposed in related works with innovative features regarding the creation of IoT systems. Among these features, an automated integration based on semantic models is proposed, which enables users to model their systems at a high level. From this model, communication interfaces are created automatically, bringing a guarantee of syntactic consistency in calling methods or functions. Another advantage that this work brings is the possibility of using this same semantic model to present information to the end user. As result of this work, an ontology was developed to model industrial elements, and an extension for an IoT middleware was developed to enable to work with these models.

With the fourth industrial revolution, new technologies and business opportunities arise, enabling previously unknown performance improvement possibilities within the manufacturing industry and its supply chains. The main actor within Industry 4.0; Internet of things (IoT) promises benefits across the entire logistics value chain by increasing supply chain connectivity and visibility. However, IoT is still in its initial stages in the manufacturing industry and respective supply chain environment, leaving uncertainty about possible application areas and impacts. The purpose of this study is therefore to investigate the role IoT-technologies have in enabling supply chain visibility and connectivity, and the impact on supply chain performance. To answer the proposed research questions, the study followed an abductive, cross-sectional research design. Empirical, qualitative data was collected through a combination of document studies and interviews with an automotive Original Equipment Manufacturer (OEM) and several third-party visibility vendors. The analysis of the collected data resulted in an outline describing ten information fields representing the information demands within a connected end-to-end supply chain, how IoT-technologies can be used to satisfy these demands and the general impact of increased visibility on the supply chain performance. To further ease the implementation decisions of IoT solutions for manufacturing OEM’s, additional research regarding the implementation process of an IoT system is needed.

Connecting factories to the internet and enable the possibilities for these to autonomously talk to each other is called the Industrial Internet of Things(IIoT) and is mentioned as Industry 4.0 in the terms of the industrial revolutions. The machines are collecting data through very many different sensors and need to share these values with each other and the cloud. This will make a large load to the cloud and the internet, and the latency will be large. To evaluate how the workload and the latency can be reduced and still get the same result as using the cloud, two different systems are implemented. One which uses cloud and one which using edge computing. Edge computing is when the processing of the data is decentralized to the edge of the network. This thesis aims to find out ”When is it more favorable to use an edge solution and when is it to prefer a cloud solution”. The first system is implemented with an edge platform, Crosser, the second system is implemented with a cloud platform, Azure. Both implementations are giving the same outputs but the differences is where the data is processed. The systems are measured in latency, bandwidth, and CPU usage. The result of the measurements shows that the Crosser system has less latency, using smaller bandwidth but is needing more computational power of the device which is on the edge of the network. The conclusion of the results is that it depends on the demands of the system. Is the demands that it should have low latency and not using much bandwidth Crosser is to prefer. But if a very heavy machine learning algorithm is going to be executed in the system and the latency and bandwidth size is not a problem then the Cloud Reference System is to prefer.

This thesis focuses on the implementation of Industry 4.0 in medical technical industry (med tech). The aim of the thesis is to get a sufficient evaluation on the Industry 4.0 implementation in a German medical technology enterprise, and also to find suggestions for improving the implementation. Two main research questions are studied in this thesis: “What is the maturity level of Industry 4.0 in a German med tech enterprise with comparison to automotive enterprises?” and “How to overcome barriers and improve the Industry 4.0 level in the med tech enterprise?” The thesis uses qualitative analysis with case study as the main research method. Automotive industry is used as reference and supporting the comparative case study. A historical review and a survey with open and closed questions are used for the data collection and analysis. Compared with automotive enterprises, the med tech enterprise is limited in the aspect of smart factory/production with Industry 4.0 implementation by various special regulations, but nevertheless there is much space and potential to develop Industry 4.0 in other aspects like smart business, smart product, and smart customers, as well as some new business modes.

The diploma thesis deals with the concept of automation of business administrative processes in the context of robotic process automation (RPA) and industry 4.0 with a focus on business information systems. The theoretical part focuses on defining the basic concepts related to the topic of this thesis, such as the information society, digitization and automation. An essential part is the analysis of current trends and possibilities of business process automation. To analyze these trends, a systematic literature review was conducted, the aim of which was to examine the current state of knowledge on the topic of industry 4.0 with a focus on current trends, future developments and other possible directions of this concept, especially in digitization and business administrative process automation. The aim of this diploma thesis is to design a solution for automation of selected administrative processes using RPA software Integromat in conjunction with the internal corporate business information system in the company ANTEE s.r.o. The design of the automation solution is based on the analysis of the current state of processes (AS-IS) and further outlines possible ways to use Integromat for their automation (TO-BE state), while also taking into account the necessary prerequisites for proper operation of...

This work deals with problematics if industrial robotic arms, with theirs constructions, controling and with theirs role in Industry 4.0. Work describes the process of development and realization of the industrial robotic arm model by 3D printing. Besides construction fo model, work deals with firmware, software and inversion kinematics crucial to controling. Model of robotic arm will be used as learning tool.