A company producing mostly asphalt rollers has a hard time quality assuring their bolted connections. There is an assembly line at the company where the different parts are put together using screwdrivers. These screwdrivers therefore need to be properly calibrated, to meet the high standards on the bolted connections.   The purpose of this research has been to come up with a cost-effective solution for the manufacturing company, so that they can digitally keep track of their screwdrivers and determine the need for calibration. The aim is to achieve full control over the quality of the connected screw-joints.   A lot of the research was focused around Industry 4.0 and IoT (Internet of Things) which are two of the most recognized buzzwords in production industries today. A product development process was used to develop the proposed solution that would help solve the identified problems.   The result of the research and the product development process is an Excel based database where information about screwdrivers are held. The database can determine when there is a need for a screwdriver to be calibrated based on the total amount of performed tightenings for each screwdriver. The total amount of performed tightenings are determined by the total amount of produced asphalt rollers which is retrieved from a production software within the company. The database also stores timestamps for calibration and service intervals, for each screwdriver.   The initial research was focused on new screwdrivers, however, inventorying of the screwdrivers made it clear that most of the screwdrivers in the manufacturing line only had the basic functions. With this information, the focus shifted to include both new and old screwdrivers. The final solution uses existing information from the company to determine when calibration is needed. Most manufacturing companies today still uses old tools, this solution can help them transition into a more digitalized industry. This solution doesn’t require tools to be compatible with a software while still offering the modern functions of newer screwdrivers.

The saturation of markets due to globalization has caused a need for digital evolution of organizations to generate innovative manufacturing practices to assure sustained competitive capabilities. Even though technological capabilities have the impact to generate competitive capabilities strategic implementation is a must for optimal performance. The phenomenon of digital transformation and relating strategic efforts are subject to greatly varying viewpoints which has made it challenging for manufactures to engage with digital transformation. The purpose of the thesis is to decipher the phenomenon digital transformation and to further identify the vital aspects of approaching digital transformation strategies through analysing literature and manufacturing companies. In order to fulfil the purpose of this research project two research questions was formulated: • RQ 1: Which are the crucial aspects of digital transformation? • RQ 2: How should digital transformation strategies be approached? This thesis is a part of digital transformation coordination project which include four industrial partners. The case companies were therefore set before the initiation of this thesis with including work packages. A literature review was performed to generate an understanding of the different viewpoints and to provide the case companies with an academic insight. Empirical findings were established through the gathering of data through observations during project meetings and the through the use of questionnaires. An analysis was conducted by comparing the different datasets. Establishing a frame of reference were vital in understanding the scattered phenomenon of digital transformation. Through identifying the contents of Industry 4.0 subsequent digital transformation and related strategical efforts provided the thesis with a profound theoretical support. The empirical findings provided the thesis with an understanding of how four different manufacturing companies viewed digital transformation. The different state of digital transformations was identified with additions to stating the possibilities and challenges. The crucial aspects of digital transformation were found through analysing the different views and meanings of digital transformation, presenting technology, and organizationally driven digital transformation and finally the fundamental aspects of digital transformation. A sound approach for manufacturers to strategize digital transformation was found through analysing the key factors of digital transformation strategies and the current constraints of digital transformation strategies. Furthermore, a discussion of additional themes which does not apply to the research questions were found to be the cause of digital transformation disparity throughout the case companies and the communication of digital transformation. The crucial aspects of digital transformation are found to be the identification of internal and external company objects that require a holistic, organizational changing continuous process. Which furtherutilizes the potential of novel disruptive technologies to develop novel business practices to generate value and competitive competences. A sound approach towards digital transformation strategies is suggested to be through generating a current state understanding to recognize the appropriate activities that must be performed and understanding the financial aspects of said activities and formulating them in a practical holistic way to assure adequate organizational support. Furthermore, understanding and communicating each strategical phase is vital to assure that the organizational aspects can support the digital transformation.

Lean, with its origin in the Japanese automotive production and Toyota, is broadly seen as the most adopted manufacturing philosophy since several decades. One of the core values of Lean is Continuous Improvements (CI). CI is about the many small, simple and cheap improvements, which everyone is involved in, every day. As digitalization is making its way into the manufacturing environment, a hype around what is called Industry 4.0 (I4.0), also known as the fourth industrial revolution, has been created. In short, I4.0 refers to different technology-driven changes in an organization’s manufacturing systems. However, the true implications of those changes remain dimmed by the single-sided discussion of I4.0’s portrayed conceptual benefits. Moreover, despite the importance of CI for corporate success and the overall relevance of the I4.0 topic, no studies have been found to address their potential interaction. Thus, the purpose of this thesis has been to explore how the conditions for CI will be affected post I4.0 implementation. By focusing on the potential negative impacts on the overall rate of improvement, the purpose has also encompassed the identification of specific success factors to mitigate these negatives.   Due to the explorative nature of the research, a two-iteration Delphi survey containing open-ended questions has been chosen as a means of data collection; targeting experienced Lean and I4.0 personnel within the manufacturing industry. The first iteration survey encouraged participants to identify both positive and negative aspects of I4.0 impact on CI, while the second iteration survey encouraged participants to identify success factors. To make the concept of I4.0 more tangible, the technologies have been condensed into three I4.0 value drivers: Connectivity, Intelligence and Flexible automation. The data processing revealed that 64% of the answers provided for all value drivers were positive. This indicated an overall positive belief in the impacts of I4.0 on the conditions for CI both through enhanced problem-sensitivity, built by Lean values and principles, and through increased problem-solving capabilities. While the results reflected the current I4.0 hype, they also highlighted the difficulty in critically assessing the potential impact from technologies that are not yet widely implemented. Nevertheless, for each value driver the participants have also identified Challenges (18% of answers) and Risks (18% of answers) that can adversely affect CI. Based on the Challenges and Risks, a total of 74 success factors have been compiled and divided into four categories: Purpose, Involvement of people, Competence and Implementation strategy.   This research has contributed to the discussion about the Possibilities, Challenges and Risks of the I4.0 value drivers’ impact on the conditions for CI in the manufacturing environment. Furthermore, with emphasis on the identified Challenges and Risks, the authors have tried to cut through the noise of the ongoing I4.0 hype. As such, this research has introduced an alternative perspective that sets it apart from the overwhelmingly uncritical discussions surrounding I4.0. While the research’s theoretical contribution has been built by the insight into the I4.0’s potential impact on the conditions for CI, its practical contribution has been derived from the identified success factors; factors that can work as guiding principles for I4.0 adopters.

In the context of the paper, a research work is shown to implement a networked decentralized safety architecture that replaces the central architecture. Thus, the safety system fits better into the rest of the automation structure. On the one hand, this is done by a clearer hardware structure, as there is now one safety controller per decentralized unit, which, analogous to the distributed automation system, communicates with the other stations via an Ethernet-based bus system, thus greatly reducing the wiring and commissioning effort. On the other hand, the decentralized processing allows a local shutdown of the safety-relevant components and an escalation of the emergency shutdown to other areas, depending on the emergency stop situation. This means that in the event of a safety-critical situation, the shutdown is reduced to what is necessary from a safety point of view, which increases system availability.

A rising level of industrialization and advances in Industry 4.0 have resulted in Industrial Internet of Things (IIoT) gaining immense significance in today’s industrial automation systems. IIoT promises to achieve improved productivity, reliability, and revenues by connecting time-constrained embedded systems to “the Internet”. New opportunities bring with them challenges, and in particular for industrial networks, massively interconnected IIoT devices communicating in real-time,  require synchronized operation of devices for the ordering of information collected throughout a  network. Thus,   a   time or clock synchronization service that aligns the devices’ clocks in the network to ensure accurate timestamping and orderly event executions, has gained great importance. Achieving adequate clock synchronization in the industrial domain is challenging due to heterogeneous communication networks and exposure to harsh environmental conditions bringing interference to the communication networks. The investigative study based on existing literature and the envisioned architecture of the future industrial automation system unveils that the key requirements for future industrial networks are to have a cost-effective, accurate, scalable, secured, easy to deploy and maintain clock synchronization solution. Today’s industrial automation systems employ clock synchronization solutions from a wide plethora of hardware and software based solutions. The most economical, highly scalable, maintainable software-based clock synchronization means are best candidates for the identified future requirements as their lack in accuracy compared to hardware solutions could be compensated by predictive software strategies.  Thus, the thesis’s overall goal is to enhance the accuracy of software-based clock synchronization in heterogeneous industrial networks using predictable software strategies. The first step towards developing an accurate clock synchronization for heterogeneous industrial networks with real-time requirements is to investigate communication parameters affecting time synchronization accuracy. Towards this goal, we investigated actual industrial network data for packet delay profiles and their impact on clock synchronization performance.  We further analyzed wired and wireless local area networks to identify key network parameters for clock synchronization and proposed an enhanced clock synchronization algorithm CoSiNeT for field IoT devices in industrial networks. CoSiNeT matches well with state-of-the-practice SNTP and state-of-the-art method SPoT in good network conditions in terms of accuracy and precision;  however,  it outperforms them in scenarios with degrading network conditions.

Uppsatsen belyser det lärande som medarbetare upplever till följd av digitaliseringens snabba framfart. Tidigare forskning visar på att medarbetare besitter en kritisk roll vid implementering av teknisk utrustning, till följd av detta krävs det att medarbetare inom tillverkningsindustrin ständigt utvecklar nya kompetenser. I denna uppsats kommer därför medarbetares upplevelser av det lärande som sker till följd av digitaliseringen att undersökas. Uppsatsen riktar sig mot medarbetare inom tillverkningsindustrin. För att få fram ett resultat kommer både bivariat analys samt bivariat regressionsanalys genomföras. Resultatet av analyserna visar att det finns ett svagt samband mellan medarbetare inom tillverkningsindustrins uppskattade lärande till följd av digitaliseringen. Uppsatsens resultat tyder på att digitalisering på arbetsplatsen ökar medarbetares upplevda lärande.

Maintenance management is a relevant issue in modern technical systems due to its financial, safety, and environmental implications. The need to rely on physical assets makes maintenance a necessary evil, which, on the other hand, allows achieving a high quality of end products, or services, and a safety level that is adequate for the regulatory requirements. The advent of the fourth industrial revolution offers meaningful opportunities to improve maintenance management; technologies such as Cyber-Physical Systems, the Internet of Things, and cloud computing enable realizing modern infrastructure to support decisions with advanced analytics. In this thesis, the optimization of maintenance policies is tackled in this renewed technological context. The research methods employed in this thesis include interviewing of subject experts, literature research, and numerical experiments. Mathematical modelling is used to model network effects in complex technical systems, and simulations are used to validate the proposed models and methodologies. The problem of maintenance policies comparison is addressed in one of the publications; using the proposed bi-objective analysis, an effective maintenance policy was identified. Maintenance of complex systems organized in a networked fashion is studied in another project, where maintenance costs and system performances are considered. The proposed model allowed to identify a set of non-dominated (in the Pareto sense) maintenance policies, and an efficient resolution procedure was developed. The possibility to use a digital twin to replicate a Cyber-Physical System for maintenance policies optimization is addressed in another publication. The main hurdles in realizing such a complex infrastructure are analyzed, and managerial implications are presented. Finally, following a qualitative research approach, the opportunities offered by additive manufacturing are identified and presented in a book chapter. The opportunities for both maintenance efficiency gains and new business models are identified and discussed.

Industry 4.0 is the trend towards automation and data exchange in manufacturing technologies and processes, which include cyber-physical systems (CPS), the Internet of Things (IoT), the Industrial Internet of Things (IIOT), cloud computing, cognitive computing, and artificial intelligence.  Industry 4.0 maturity is assessed by evaluating the degree of implementation of each transformation capability and, consequently, in each dimension. Maturity models are used as instruments to recognize and measure the maturity level of a company in a certain domain or a process related to a future goal. The content of each dimension can be derived from qualitative research methods, including bibliographic reviews, case studies analysis, focal groups, and other methodologies of idea generation and decision-making.  This project aims to perform an implementation status and maturity level assessment of Industry 4.0 in European Industries. The project covers an assessment of the level of readiness to accomplish the Industry 4.0 standards and requirements.

Yes / Information systems are critical for companies since they offer quick and easy access to complex and significant data in a structured manner to make informed and effective business decisions. Hence, the objective of this study is to conceptualize and implement an innovative information system in the case study organization. The study identified the requirements for Organizing Vision Theory (OVT) and developed architecture based on Organizational Information Processing Theory (OIPT). This architecture is designed and developed using the Industrial Internet of Things (IIoT) to support a self-organizing vision and enhanced information processing. The study’s contribution lies in developing and executing an integrative architecture of IIoT-driven information systems from the lenses of OVT and OIPT. Further, this study contributes by mapping OVT elements (such as transparency, continuity, and coherence) and OIPT elements (information processing needs and capabilities) to drive value and knowledge through a robust architecture of IIoT-driven information systems. The study also highlights the contribution of IIoT-based information systems to a new knowledge system, facilitating better decision-making by professionals.

The Fourth Industrial Revolution, known as Industry 4.0, has ushered in a new era of technological advancement and disruption across Manufacturing Industries. As organizations embrace digital technologies, artificial intelligence, and automation, the workforce faces profound changes in job roles, skill requirements, and training needs. Several challenges are faced by industries during this Industrial transformation. This research begins by focusing on Industry 4.0 and Industry 5.0, understanding there evolving concept. Through comprehensive literature review, the challenges and practices faced during this Industrial transformation and SDGs are discussed. Following the literature review, survey and interview questions were drafted trying to dug deeper into aspects that the literature could not fully capture. Furthermore, the relation between this Industrial Transformation and SDGs were established. This research contributes to a deeper understanding of the dynamic relationship between technology, the workforce, and sustainable development. This thesis report serves as a valuable resource for policymakers, business leaders, educators, and researchers seeking to navigate the transformative landscape of Industrial Transformation and its implications for a rapidly evolving workforce and sustainabledevelopment. / Den fjärde industriella revolutionen, känd som industry 4.0, har introducerat en ny era av teknologisk framsteg och förändringar inom tillverkningsindustrin. När organisationer omfamnar digitala teknologier, artificiell intelligens och automation står arbetskraften inför djupgående förändringar i arbetsroller, kompetenskrav och utbildningsbehov. Under denna industriella omvandling möter företag flera utmaningar. Denna forskning börjar med att fokusera på industry 4.0 och industry 5.0 och förstå deras utvecklande koncept. Genom en omfattande litteraturgenomgång diskuteras de utmaningar och metoder som möter denna industriella omvandling samt deras koppling till hållbarhetsmålen (sdgs).Efter litteraturgenomgången utformades enkät- och intervjuförfrågningar för att fördjupa förståelsen för aspekter som litteraturen inte kunde fånga helt. Vidare etablerades sambandet mellan denna industriella transformation och hållbarhetsmålen. Denna forskning bidrar till en djupare förståelse av den dynamiska relationen mellan teknologi, arbetskraften och hållbar utveckling.Denna avhandling tjänar som en värdefull resurs för beslutsfattare, företagsledare, utbildare och forskare som söker navigera i det föränderliga landskapet av industriell transformation och dess konsekvenser för en snabbt utvecklande arbetskraft och hållbar utveckling.