Windows provide building occupants with important physiological and psychological benefits but are absent from many indoor spaces. It is argued that most existing attempts at compensating for an absence of windows fall short because they lack either outdoor environmental information or sensory stimulation. A wind-animated digital-tree shadow was used to test this hypothesis. The work concludes that the following strategies are likely to help most to compensate for an absence of windows: (1) establishing a live connection with the outdoors; (2) introducing controllable sensory variation into a space; (3) making such change a source of natural environmental information. It is suggested that these approaches could be helpful used either separately or in combinations but that a live connection with the outdoors that introduces controllable naturally-generated change into a space would likely be most effective. The video files that accompany this thesis show the digital shadow with wind and computer generated movement.

BACKGROUND - The development of Industry 4.0 increases the opportunities to both automate and digitize processes in the manufacturing industry. The steel industry has been around for many years, which means firmly anchored operations and both manual- and automated processes. To make better decisions, identify bottlenecks, and test new functions without having to stop the production, a digital model of the process can be helpful. Furthermore, with the rapid development of technology, digital models can be further developed into digital twins. A digital twin should be able to handle the communication between the physical- and digital world automatically and analyze data to make decisions in the process. RESEARCH QUESTIONS What are the challenges of developing a digital model representing a production line within a global steel manufacturing company? What opportunities could a digital model of a production line entail, and how could Industry 4.0 technologies create opportunities to further develop the digital model into a digital twin? METHODS - In this project, both a literature- and case study have been carried out. During the literature study, techniques that can be used to develop the digital model further have been investigated. During the case study, a digital model of a Quench Line was developed to gather practical experience of what it can mean to create a digital model of a manufacturing process within a steel manufacturing company. The model has been developed in MATLAB/Simulink. RESULTS - The most significant challenges when developing digital flow simulation models identified in this project were data management/access, handling variations, verifying the model, andlack of knowledge linked to digital models in general. The opportunities identified and confirmed in this project were that the model could be used to carry out new logistics planning, bottleneck analyses, and test new machine implementations. To further develop the digital model into a digital twin, Industry 4.0 technologies will be crucial. The technologies that will be useful are the Internet of Things, Artificial Intelligence, Machine Learning, Cloud Computing, and Big Data.

In recent years, the traditional manufacturing industry is challenged worldwide with the astounding growth and advancement so-called Industry 4.0. One of the multiple objectives pursued by the industry with this technological revolution is to achieve a new enhanced standard of safety. In addition, a solution against inaccurate offline robot programming needs to be tackled. The combination of a Digital Shadow (DS) of the robot with visualisation in Mixed Reality (MR) can help to increase safety and eventually, even make the design process faster. In this survey paper, a visualisation system in MR that allows the user to overlay digital tools into a UR10e Physical Robot (PR), thus permitting the PR to interact with digital work objects is proposed. To achieve the synchronisation between the digital and real assets, a DS of the robot has been developed. The integration of the Digital Models (DMs) of tools and work objects allows the user to work with the robot without load, opening the possibility of recreating and testing in real-time experimental industrial processes.

Digital twins have become a large part of new cyber-physical systems as they allow for the simulation of a physical object in the digital world. In addition to the new approaches of digital twins, machines have become more intelligent, allowing them to produce more data than ever before. Within the area of digital twins, there is a need for a less complex approach than a fully optimised digital twin. This approach is more like a digital shadow of the physical object. Therefore, the focus of this thesis is to study machine states and statistical distributions for all sensors in a machine. Where as majority of studies in the literature focuses on generating data from a digital twin, this study focuses on what characteristics a digital twin have. The solution is by defining a term named digital machine template that contains the states and statistical properties of each sensor in a given machine. The primary approach is to create a proof of work application that uses traditional data mining technologies and clustering to analyze how many states there are in a machine and how the sensor data is structured. It all results in a digital machine template with all of the information mentioned above. The results contain all the states a machine might have and the possible statistical distributions of each senor in each state. The digital machine template opens the possibility of using it as a basis for creating a digital twins. It allows the time of development to be shorter than that of a regular digital twin. More research still needs to be done as the less complex approach may lead to missing information or information not being interpreted correctly. It still shows promises as a less complex way of looking at digital twins since it may become necessary due to digital twins becoming even more complex by the day.

Critical infrastructures (CIs) distributing water, oil, gas, electricity, etc., to community residents and businesses, leverage cyber-physical systems (CPSs) to supervise and control the physical processes that these services entail. Over recent decades, these systems have moved to implement more modern IT-resembling solutions using Supervisory Control and Data Acquisition Systems (SCADA) for increased reliability, scalability, and remote connectivity. This change exposes these highly critical systems to new threats and vulnerabilities. One approach to mitigate the risks faced by these systems is to perform analysis on digital representations in the form of digital models or digital shadows of the CPSs. However, this is not a trivial task in practice. These practical issues are explored in this design science research through the development of a guidance process to perform the data collection necessary to create a static digital model of a small-scale power grid CPS in Sweden. The results show that it is possible to gather information on the CPS components through the four approaches: SCADA system exports, documentation information, CLI scripting, and network scanning. While the artefact presented in this report demonstrates these results, challenges still remain such as a lack of SCADA export tools, reaching the SCADA network with scanning tools in a responsible manner, and accessing insights into the complete documentation held by the organisations. The researcher suggests these topics for future research directions.