Background: The manufacturing industry is diverting away from the one-size-fits-all mass manufacture towards more customized processes. With increasingly individualized consumer preferences and an intense competitive environment, food manufacturers are required to meet specific consumer demands with similar efficiency to those produced massively. Such market requirements are feasible with the technological advancements envisioned by Industry 4.0. The consequences of such are increased flexibility and mass customization in manufacturing which forces the food manufacturer towards its realization. The integration process, however, involves a comprehensive transformation that affects every aspect of the organization. This consequently imposes significant challenges upon the food manufacturing company. Purpose: The study aims to investigate the transformation process ensued by the food manufacturer for Industry 4.0. Consequently, a conceptual framework is developed detailing the application of Industry 4.0 in the food manufacturing industry. Method: An inductive qualitative approach, in combination with a multiple-case study, is pursued to address the formulated questions of research. Based on such, semi-structured interviews were conducted with individuals representing three multinational food manufacturers. Further, a thematic analytical technique was adopted as means to identify similarities and patterns within the obtained data. The collected data was analyzed using thematic analysis through which the researchers came up with the conceptual framework. Conclusion: The results of the research reveal internal and external factors such as labor policies and IT infrastructure to influence the transformation process for Industry 4.0. In due to this, the implementation of the phenomenon occurs phase-wise, globally coordinated and regionally concentrated. This enables the organization to overcome the obstacles faced and, subsequently, ensure the successful deployment of Industry 4.0.

<p>In recent years, the pharmaceutical industry has embarked on an extensive program to modernize its manufacturing resources. Recognizing the limitations of traditional mass manufacturing, the industry is now focused on developing new production systems that can deliver high-quality medicines with enhanced efficiency, flexibility, agility, and reliability. To realize this vision, innovations in three key areas are being pursued: continuous processing, personalized medicine, and Industry 4.0.</p> <p>This thesis contributes towards the industry’s goal by focusing on the development of an advanced system to manufacture solid oral drug products. This system is centered around a pharmaceutical additive manufacturing technology called drop on demand (DoD) printing. This technology is highly effective in making personalized drug products, which allow for customizing dose attributes such as drug loading, release behavior, formulation type, and dosage form, based on patient requirements. To develop the DoD printer into an advanced production system, technologies such as end-to-end continuous processing, real time quality assurance, and automated operation need to be incorporated into it. </p> <p>The studies presented in this thesis implement different aspects of these technologies in the printer. To enable end to end operation, a novel solvent switch process called three phase settling is developed to integrate the DoD system with upstream steps for synthesizing the active ingredient. To facilitate automated processing of formulations with different active ingredients, excipients, and particle concentrations, a model framework is developed to recommend operating conditions for the DoD platform that can deliver on-spec printer operation. To expand the range of personalized dosage forms offered by the system, the manufacturing of a new category of drug products, called mini-tablets, is demonstrated. To provide reconfigurability and quality assurance capabilities in the platform, modular design and process monitoring tools are implemented. To aid optimization and control of drug production processes, a digital twin is developed by combining the models developed for DoD, solvent switch, synthesis, and crystallization operations. </p> <p>The research presented in this thesis lays the foundation for developing the next generation of manufacturing systems for drug products. Incorporation of scalability, autonomous operation, and real time release prediction are critical steps in facilitating the next phase of its development – deployment in real-world manufacturing scenarios.  </p>

This thesis investigates the transformations associated with the development and diffusion of 4.0 technologies, by combining a firm-level perspective with a territorial-level perspective. The aim is to understand whether and to what extent the engagement of firms, in particular technological knowledge-intensive business services, in 4.0 innovation activities is affected by the characteris-tics of the territory, regions, cities, or local production systems, in which they are located. The thesis consists of three chapters. Chapter 1 comprises a systematic literature review of the studies that address Industry 4.0-related issues in industrialized countries from a regional perspective. The selected articles have been systematically collected and then discussed using a qualitative content-based approach. This review allowed for the identification of the main issues discussed and the gaps that exist in the literature and laid the foundation for the empirical analysis conducted in Chapter 2 and Chapter 3, which focus on private technological knowledge-intensive business services (t-KIBS) engaged in the production and/or provision of ICT services. The decision to concentrate on technological knowledge-intensive business services (KIBS) specializing in information and communication technology (ICT) is connected to their significant role in 4.0 transformations as they serve as both producers of these technologies and intermediaries and adapters, facilitating their adoption and implementation. Chapter 2 delves into the examination of the firm level and territorial level factors that influence the spatial distribution of the t-KIBS involved in the provision of 4.0 technologies (4.0 t-KIBS). 4.0 t-KIBS were identified using information extracted from t-KIBS websites, collected through web-scraping techniques. Then, a probit model with sample selection was employed to identify the most important territorial and firm-related factors influencing the decision to develop and/or provide 4.0 technologies. The results show that the probability of mentioning 4.0 technology is positively affected by t-KIBS size and profitability. From a territorial perspective, the main determinants are represented by demand coming from co-located manufacturers and to a lesser extent by urbanization economies. Finally, following the literature on KIBS variety, Chapter 3 explores the heterogeneous nature of the t-KIBS involved in the production and provision of 4.0 technologies. The objective is to gain insights into how these organizations differ across several key dimensions frequently examined in the KIBS variety literature. These dimensions encompass the geographical scope, innovation output, cognitive structure, external collaborations, and client focus. The empirical analysis draws on the same database built for Chapter 2 and on data collected through an original survey of a sample of 500 t-KIBS. The survey allowed for the collection of firm-level information that could not be retrieved from other data sources. The empirical analysis is split into two parts. Using a probit approach, the first part of the analysis explores whether and to what extent the peculiarities of 4.0 t-KIBS vary mainly according to their geographical scope and innovation output. The second part of the analysis employs a matching technique to compare certain attributes of 4.0 t-KIBS with those whose activities are not centred around 4.0 technologies. The main results show that the activities of 4.0 t-KIBS have a broader geographical scope that goes beyond local and regional boundaries. In contrast to established literature on KIBS, this is especially true for those t-KIBS that deliver customized innovations tailored to the needs of customers. From a cognitive perspective, it emerges the tendency of 4.0 t-KIBS to also rely on non-technical knowledge, while in terms of collaborations, they are more likely to collaborate with firms belonging to the same business group. Finally, 4.0 t-KIBS that are regionally anchored (i.e., they have not established an inter-regional network) are more likely to develop services and technologies specifically for public administrations.

Nowadays, interconnectivity is becoming increasingly important. According to industry, the Industrial Internet of Things (IIoT) is the core technology of Industry 4.0. Connectivity between different processes or components in the industry makes one process aware of each other, making systems more intelligent and self-sufficient. This thesis proposes various ways to control and monitor an industrial process with the cloud, explaining step by step the connections between the industrial equipment and the cloud. Furthermore, this thesis's one sub-objective is to make an industrial process, which was previously PLC-based, entirely cloud-based. For the latter work, simulation software is used to create a production line, as there is a lack of equipment. Consequently, it will also test the flexibility of the system to move between the virtual and the real environment, which is another challenge of Industry 4.0 and digitalisation. In the discussion part, the thesis talks about the shift from PLC-based to PC-based systems in the industry, mentioning the limitations and advantages.

Purpose. Real-time Locating Systems (RTLS) are used to identify and locate physical assets in real-time. Essentially, the aim of RTLS is to increase process visibility and thus provide accurate process data concerning for example, lead times, cycle times and inventory control. Today, process visibility is one of the most critical aspects for manufacturing companies in their quest for higher quality and shorter lead times. Since the introduction of Industry 4.0, RTLS has received an upswing in attention in the literature. However, despite the technical advances, enterprises are struggling to fully comprehend the entire impact of RTLS. Further, when integrating RTLS and other IT systems, such as the ERP, business operations can be carried out based on real-time information, providing more value than a standalone RTLS. Enterprise Resource Planning (ERP) system is the core IT system for enterprises. The ERP is in turn divided into several modules: Manufacturing, Warehouse, Human resources, Sales &amp; Distribution, and Finance &amp; Accounting. Evaluating the applicability for each module will provide a holistic view on RTLS and ERP integration that has a wider perspective than previous studies on the topic. Consequently, the purpose of this study was to examine and evaluate the applicability of integrating RTLS with the various ERP modules and present a set of guidelines for RTLS and ERP integration. The guidelines will be created based on the following research questions. RQ1: How can the various ERP modules utilize RTLS data? RQ2: What barriers and enablers are there when integrating RTLS and ERP? Research method. An extensive literature review and interviews with industry experts were conducted. Thematic analysis and thematic narrative analysis were applied to extract relevant information form the literature review and industry expert interviews. Thematic synthesis was applied to synthesize the information received from the result of the thematic analysis and thematic narrative analysis, thence answer the research questions, and create the guidelines. Findings. Applicability was found for all ERP modules and the main barriers identified was lack of mature processes, knowledge, and cost. The guidelines created in the study included five main steps. 1) organizational enablers, 2) IT structure enablers, 3) ERP module applicability, 4) knowledge and understanding, and 5) business case generation. The guidelines were presented in text and as a picture. Contributions. This study has contributed to research by expanding the perspective on RTLS and ERP integration further than previous studies on the topic. The study showed that all ERP modules can utilize the RTLS data to provide value for that particular module. This study contributes to industry by providing guidelines that can be utilized by managers and decision makers in their process of evaluating RTLS implementation Managers and decision makers can use these guidelines to create a fundamental understanding of how RTLS can create value for all ERP modules. This knowledge is a key to create profitable business cases. The guidelines will therefore facilitate enterprises to overcome the initial knowledge barriers and thus, contribute to the acceleration of the RTLS expansion within the industry.

Automated guided vehicles are an integral part of industrial production today. They are moving products to and from shelves in storage warehouses and fetching tools between different workstations in factories. These robots usually follow strict pre-determined paths and are not good at adapting to changes in the environment. Technologies like artificial intelligence and machine learning are currently being implemented in industrial production, a part of what is called Industry 4.0, with the aim of increasing efficiency and automation. Industry 4.0 is also characterized by more connected factory environments, where objects communicate their status, location, and other relevant information to their surroundings. Automated guided vehicles can take advantage of these technologies and can benefit from self-optimizing approaches for better navigation and increased flexibility. Reinforcement learning is used in this project to teach automated guided vehicles to move objects around in an Industry 4.0 warehouse environment. A 10x10 grid world with numerous object destinations, charging stations and agents is created for evaluation purposes. The results show that the agents are able to learn to take efficient routes by balancing the need to finish tasks as fast as possible and recharge their batteries when needed. The agents successfully complete all tasks without running out of battery or colliding with objects in the environment. The result is a demonstration of how reinforcement learning can be applied to automated guided vehicles in Industry 4.0 environments. / Automatiserade styrda fordon är en integrerad del av dagens industriproduktion. De flyttar produkter till och från hyllor i lagerlokaler och hämtar verktyg mellan olika arbetsstationer i fabriker. Dessa robotar följer vanligtvis strikta förutbestämda vägar och är inte bra på att anpassa sig till förändringar i miljön. Teknik som artificiell intelligens och maskininlärning implementeras just nu i industriproduktion, en del av det som kallas Industri 4.0, i syfte om ökad effektivitet och automatisering. Industri 4.0 kännetecknas också av mer uppkopplade fabriksmiljöer, där objekt kommunicerar sin status, plats och annan relevant information till sin omgivning. Automatiserade styrda fordon kan utnyttja de här teknikerna och kan dra nytta av självoptimerande metoder för bättre navigering och ökad flexibilitet. Förstärkningsinlärning används i detta projekt för att lära automatiserade styrda fordon att flytta runt föremål i en Industri 4.0 lagermiljö. En 10x10 stor rut-värld med flertalet destinationer, laddningsstationer och agenter skapas i utvärderingssyfte. Resultaten visar att agenterna kan lära sig att ta effektiva vägar genom att balansera behovet av att slutföra sina uppgifter så fort som möjligt och ladda upp sina batterier när det behövs. Agenterna slutför framgångsrikt sina uppgifter utan att få slut på batteri eller att kollidera med föremål i miljön. Resultatet är en demonstration av hur förstärkningsinlärning kan tillämpas på automatiserade styrda fordon i Industri 4.0-miljöer.

I samband med dålig praktisk implementeringsgrad av den cirkulära metoden återtillverkning, var målet med arbetet att konstruera en modell som kan användas av företag i syfte att implementera återtillverkning. Modellen konstruerades utifrån perspektiven grunder och optimering. Optimering delades in i tre ytterligare perspektiv, där företags-, produkt-, och processperspektivet inkluderades. I processperspektivet inkluderades potentialen för optimering genom industri 4.0 (I4.0), på grund av återtillverkningens idag låga adoption av dessa. Arbetet är avgränsat till implementering av återtillverkning, nämnda perspektiv, samt I4.0 teknologier som identifierats optimera återtillverkningsprocessen. Lösningsmetoden för arbetet har grundat sig på litteratur och åtta genomförda intervjuer med respondenter från akademin samt industrin. Resultatet som framställs utifrån detta bygger på förutsättningar som exempelvis innefattar att fastställa förvärv av returprodukter, säkerställa kommunikation med intressenter, etablera kommunikation med original equipment manufacturer (OEM) och att beslutstagande kan underlättas med RFID, QR-koder, Big data, IoT och AR. Modellens beståndsdelar är samtliga förutsättningar inom respektive perspektiv. / Based on the poor practical implementation rate of the circular method of remanufacturing, the aim of this work was to construct a model that can be used by companies for the purpose of implementing remanufacturing. The model was constructed from the perspectives of basics and optimization. Optimization was divided into three additional perspectives, where the company-, product-, and processperspectives were included. In the process perspective, the potential for optimization through industry 4.0 (I4.0) was included, due to the currently low adoption of these by the remanufacturing industry. The work is limited to the implementation of remanufacturing, the mentioned perspectives, and I4.0 technologies that have been identified to optimize the remanufacturing process. The methodology for retrieving information has been based on literature and eight interviews with respondents from the academy and industry. The results are based on prerequisites that include, for example, establishing acquisition of returned products, ensuring communication with stakeholders, establishing communication with original equipment manufacturers (OEMs) and that decision-making can be favored by the usage of RFID, QR codes, Big data, IoT and AR. The components of the model are based on all the prerequisites within each perspective.

Världens industrier genomgår en stor förändring. Fler delar av industrins processer automatiserar. Detta påverkar bland annat industrins ekonomi samt dess personal. Syftet med denna rapport är att identifiera hur industrirobotar påverkar företagets ekonomi samt hur företagets personal påverkas. För att genomföra detta har dels information inhämtas från äldre akademiska handlingar. Även fältstudier har genomförts. Litteraturstudien genomfördes först för att införskaffa den kunskap som krävs för att kunna jämföras med den empiriska-/fältstudien. Den empiriska studien bestod av två delar. Del ett består av ett frågeformulär, detta frågeformulär skickades ut till både robottillverkare och industrier som använder industrirobotar. Denna del gjordes för att inhämta mycket data till rapporten. Del två består av tre intervjuer med anställda på företag som arbetar med industrirobotar samt en intervju med en doktorand som forskar om industrirobotar. Denna del genomfördes för att få en mer detaljerad beskrivning av frågeställningarna. Del ett och två har sedan diskuteras för att sedan komma fram till slutsatsen att jobben i industrin påverkas mer positivt än man tidigare befarat. Industrirobotarna räddar dels jobb som annars hade försvunnit, dels gör det möjligt att ta hem produktionen till Sverige och därav generera fler jobb. Ytterligare en slutsats som kunnat konstateras är att den primärt avgörande faktorn för investeringar i industrirobotar är att företaget gynnas ekonomiskt samt att den till största del enbart ses som en bonus att de anställdas arbetsmiljö förbättras. / The world's industries are undergoing a major change. More parts of the industry's processes are automated. This affects, among other things, the industry's finances, and its staff. The purpose of this report is to identify how industrial robots affect the company's finances and how the company's personnel are affected. To implement this, information has been obtained from older academic documents and field studies have been carried out. The literature study was first conducted to acquire the knowledge required to be able to be compared with the empirical / field study. The empirical study consisted of two parts. Part one consists of a questionnaire, this questionnaire was sent out to both robot manufacturers and industries that use industrial robots. This part was done to gather a lot of data for the report. Part two consists of three interviews with employees of companies that work with industrial robots and one interview with a researcher at KTH that focus on industrial robots. This part was carried out to get a more detailed description of the issues. Part one and two have then been discussed to then conclude that jobs in the industry are affected more positively than previously feared. The industrial robots save jobs that would otherwise have disappeared and make it possible to bring production home to Sweden and thereby generate more jobs. Another conclusion that has been established is that the primarily decisive factor for investments in industrial robots is that the company benefits financially and that it is for the most part only seen as a bonus that the employees' working environment is improved.

Industrin genomgår sin fjärde industriella revolution, maskiner och hela fabriker kopplar upp sig till molnet och börjar prata med varandra. Detta möjliggör stora resurseffektiviseringar om det utförs på rätt sätt. Utvecklingen av nya metoder för insamling av data medför inte bara möjligheter utan skapar även nya frågor som industrin inte handskats med tidigare. Syftet med arbetet har varit att titta närmare på hur företag och industrin generellt sett ser på omställningen och vilka hinder som de anser är svårast när det kommer till implementering av ny teknik. Men även hur företagen bakom dessa nya tjänster och produkter jobbar med hinder under omställningen. Som grund för rapporten ligger en litteraturstudie där fakta om de tekniska lösningar som finns och en bakgrund till skärande bearbetning presenteras, vilket också varit det område som arbetet begränsats till. Personer har intervjuats för att få en inblick i hur olika företag jobbar med dessa frågor och kunna jämföra med litteraturstudien. Resultatet från arbetet visar att industrin står inför många svåra beslut, samtidigt är alla överens om att digitalisering är den rätta vägen att gå. Det främsta hindret är kompetensfrågan. Hos de som köper digitala tjänster och produkter anser dem i de flesta fall att kompetens som krävs för att kunna implementera tekniken på effektivast sätt saknas. De utvecklande företagen står inför problem med att det många gånger är utmaningar de inte jobbat med tidigare och därför saknar kompetens för själva utvecklingen. Övriga hinder som arbetet påvisat handlar om kostnader, gemensamma standarder och datasäkerhet. / The industry of today is going through its fourth revolution where machines and factories are starting to connect to the cloud and communicate with each other (Internet of Things). If performed correct this enables great resource efficiency. The development of new methods of data collection brings not only possibilities but also raises new questions that the industry hasn't dealt with before. The purpose with this project has been to take a further look into how companies and the industry generally approach the adaptation within digitalization and which difficulties that are seen as most demanding when it comes to the implementing of new methods. Also, how companies behind new services and products work with difficulties during development. The base for this project has been a literature study where facts about some of today's technical solutions are presented, a background to metal cutting which is an area of limitation for this project is presented as well. Interviews with persons have been made to get a picture of how different companies are working with these questions and to compare them with the information received from the literature study. The result of this project shows that the industry stands in front of many difficult decisions but with a common view that digitalization is the right way to go. The most outstanding obstacle is concerning competence and the lack of it. Those who purchase digital products and services consider themselves to lack the right knowledge to implement new technologies in the most efficient way. The developing companies faces challenges when it comes to finding the right competence regarding the development itself since it often is new challenges that they not have encountered before. Further impediments that the project has shown are cost, standards and data security.

In paper mills, the paper machine is followed by a winding machine which cuts paper to intended width and rolls onto cylinders to specified length. Central to this paper is the gathering and synchronizing of data from databases relevant to automation research for the winder. Part of data gathering was automated with Python and the data was analyzed to determine details about the data. Data was found to be stored in different databases and accessible through different interfaces with some variation in formatting of time strings and time zones between data sources. Other issues, likely stemming from different parts of the greater system being implemented at different times, provided by different companies utilizing different technologies. Suggestions toward streamlining of data gathering for ease of future automation and research were given with discussion of this work, the system, theory and future research.