We are today facing an industrial revolution called Industry 4.0. Earlier in the human history, we have seen multiple industrial revolutions, but only after they actually happened. This is the first time we can see that an industrial revolution is on its way. Witht his knowledge, we have the chance to prepare for this large‐scaled technological change that we are standing in front of. Because of the impact that earlier industrial revolutions had on organizations, we can assume that Industry 4.0, as well, will impact and change work, tasks and the organizations themselves; especially when it comes to new high‐tech knowledge and skills that need to be learnt. Implementation, change, and high‐tech learning, together with a constantly running production can be stressful for anyone involved. For this reason, the purpose of this study is to come up with solutions on how you can facilitate the implementation of Industry 4.0, for employees and in an organizational point of view. We do this by conducting a literature study as well as interviewing organizations within the Swedish manufacturing industry. The structure of the analysis is built upon Lewin’s Three‐stage Model of Change. Here, we discuss and present solutions according to the stage in which they fit during the change process. Additionally, we investigate the concept of gamification as a tool to facilitate change. From our research, we conclude that motivation and engagement are keys in a technological change project such as Industry 4.0. Involvement, transparency and clarity are important aspects to make employees engaged throughout the project. Additionally, we present practical solutions for how organizations can educate their employees within Industry 4.0 techniques, as well as increase their motivation and engagement. / Vi står idag inför en industriell revolution som kallas Industri 4.0. Tidigare i historien har vi sett industriella revolutioner först efter att de inträffat. Det är nu första gången vi kanse att en industriell revolution är på väg. Med denna kunskap har vi idag en möjlighet att förbereda oss för den teknologiska utveckling som vi står inför. På grund av de tidigare industriella revolutionerna och den stora påverkan som de har haft på organisationer, kan vi anta att Industri 4.0 också kommer förändra jobb, uppgifter och organisationer – framför allt när det kommer till den nya teknologiska kunskap som nya maskiner och system kommer kräva av de som använder dem. Implementering, förändring och en hög nivå av teknologiskt lärande, samtidigt som produktionen fortfarande kommer snurra dygnet runt, kan vara stressigt för vem som helst. Därför syftar detta examensarbete till att ta fram lösningar för hur man kan förenkla implementationen av Industri 4.0, ur ett medarbetarperspektiv och för organisationen som helhet. Vi gör detta genom en litteraturstudie och genom intervjuer med organisationer inom den svenska tillverkningsindustrin. Strukturen på analysen bygger på Lewins trestegsmodell för förändring. Här diskuterar och presenterar vi lösningar enligt vilket steg de passar in i under förändringsprocessen. Vidare utvärderar vi gamification som ett verktyg för att underlätta förändringen. Detta arbete kommer fram till att det viktigaste för att genomföra ett förändringsarbete i denna omfattning är motivation och engagemang från både anställda och ledning. Involvering, transparens och tydlighet är viktiga delar för att göra anställda engagerade genom hela projektet. Vidare presenterar vi lösningar för hur man kan utbilda sina anställda inom Industri 4.0‐tekniker, och även för hur man kan öka motivation och engagemang.

The 3rd Advanced Manufacturing Student Conference (AMSC23) continues its mission to foster skills in Research Methods within Engineering Sciences. Organized jointly by Chemnitz University of Technology and the Fraunhofer Institute for Machine Tools and Forming Technology, AMSC23 offers a platform for students to engage with cutting-edge research in advanced manufacturing. The conference covers diverse areas, including Additive Manufacturing, Cyber-Physical Systems, Industry 4.0, Human-Machine Interaction, and Sustainable Manufacturing. Abstracts highlight advancements in Additive Manufacturing, explore integration of Blockchain in Smart Manufacturing, discuss Industry 4.0's impact on sustainability, and delve into Human-Machine Collaboration. Machine Learning, AI applications, and advancements in Printed Functionalities are also addressed. Sustainability themes encompass circular economy principles and the sustainable aspects of additive manufacturing. Virtual and Augmented Reality's role in enhancing manufacturing processes is also examined. With a focus on knowledge exchange, AMSC23 serves as a valuable platform for the next generation of manufacturing professionals.:# Foreword # Scientific Committee & Board of Reviewers # Additive Manufacturing – Technology and Application - Use of Infrared Thermography for Fault Detection in Welding: Challenges and Potential (M. Ahmed) - Dental Implant Construction: The Advantages of Selective Laser Melting (SLM) Technology (S. Ali) - A Review of Monitoring in WAAM (M. Altobelli) - Additive Manufacturing in Aerospace: Advancements, Applications, and Impacts (U. Ayub) - Methods of Multi-Material Printing (S. Barve) - Resonant Ultrasound Spectroscopy a Non-Destructive Approach for Defect Detection in Additively Manufactured Parts (N. Chavan) - Manufacturing Methods to Fabricate Aerospace Structures Focusing on Wings (A. Correa Rivera) - A Review on Laser Powder Bed Fusion Process: Defects and Their Influencing Factors (Y. Gosankararaman) - 3D Printing in Microgravity: Evaluating the Feasibility of In-Space Manufacturing for Long-Duration Space Exploration (B. Jadhav) - Powders Used for Powder-Based Fusion Additive Manufacturing (V. Jadhav) - Overview of Wire Arc Additive Manufacturing: Process Classification with Pros and Cons, Applications in the Transportation Industry and Challenges (S. Kattookaren) - Exploring the Potentials of Computed Axial Lithography (T. Khot) - Additive Manufacturing for Biomedical Devices (A. Nematli) - A Review on Wire Arc Additive Manufacturing of Nickel‑Based Components (F. Ottakath) - A Review on Additive Manufacturing in Healthcare Industry (F. Parmaksiz) - 3D Manufacturing of 3D Printed Circuit Boards (P. Puranik) - A Review on Powder-Based Direct Energy Deposition: Defects and Influencing Parameters (M. Seshadri) - Progress towards In Situ Resource Utilization of Extraterrestrial Regolith for Off-Earth Manufacturing and Additive Manufacturing Technologies used Therein (K. Timilsina) - A Review on Additive Manufacturing Technologies in Aviation (S. Ücün) - Traditional and Additive Manufacturing Approaches for Metal Matrix Composites: A Comprehensive Review (N. Venkatesha) - Hybrid Production Technologies In Additive Manufacturing (A. Vezhaparambil Rappai) # Advances in the Field of Cyber-Physical Systems - A Review on Integration of Blockchain Technology in Edge-Computing Applications in Smart Manufacturing (R. Ayyappan) - Cyber-Physical Systems advancements and applications in Smart Manufacturing and Industry 4.0 (A. Esmaeili Bigdeli) # Digitalisation of Industrial Production (Industry 4.0) - Predictive Maintenance Strategy in Industry 4.0 Using Machine Learning (A. Alyasin) - Car to X Communication (G. Aydın) - Correlation and Impact of Industry 4.0 on Sustainability Development (S. Dashpute) - A Review of Prerequisites of Industry 4.0 in Manufacturing and in Different Applications (N. Farbood) - Methods of Production Data Acquisition and Their Application in Industry (M. Mahtab) - Evolution and Advancements in Coordinate Measuring Machines within the Industry 4.0 Context (P. Phadnis) # Hybrid Societies – Human-Machine-Environment Interaction - A Review on Tire Pressure Monitoring Systems and Their Manufacturing Methods (A. Hosseini) - Voice-Enable Digital Assistant in Manufacturing (T. Kuklina) # Machine Learning and AI in Advanced Manufacturing - Application of Machine Learning Algorithms in Machining of Metal Matrix Composite (MMC) Materials: A Review (P. Giri) - Automatic Parking Assist System (A. Hadizadeh) - Artificial Intelligence for Zero Defect Manufacturing: Potential and Insights for Smart Manufacturing (M. Khan) - Artificial Intelligence Aided Manufacturing: Applications of Neural Network in Advanced Manufacturing (N. Opasanon) # Printed Functionalities and Integration of Adaptronic Systems - Printed Functionalities and Integration of Adaptronic Systems (S. Ahmed) - Memristor Devices: Challenges and Development Prospects (S. Banasaz Nouri) # Robotics, Mechatronics and Manufacturing Automation - Human-Robot Collaboration in Assembly Processes: Investigating Methods and Strategies for Effective Collaboration between Humans and Robots in Assembly Tasks (H. Chopadawala) - Thermal Optimization of Heatpipes: Materials, Structure and Operational Parameters Controlled by LabView as an Interface (E. Nikkhah) - Flexible Manufacturing Systems and the Fourth Industrial Revolution: Concepts, Design Framework, and Challenges (V. Pai) # Smart Manufacturing, Management and Life Cycle Assessment - Traceability, Indispensable Element of Global Production (P. Almanza Rodríguez) - Exploring New Technologies in Procurement (N. Kakuste) - Economic Perspective of Supporting Structure in Additive Manufacturing Field (B. Toz) - On Some Issues of Development of Sustainable Manufacturing (V. Zorenko) # Sustainable and Environmentally Friendly Manufacturing - Circular Economy: Benefits and Limitations (T. Abhang) - A Review on Sustainability Advantages of Additive Manufacturing (M. Etemad Moghadam) - Implications of Industry 4.0 Technologies on Sustainability (M. Kohli) - Energy Optimization Methods for Sustainable Manufacturing (M. Ibrahim Mohamed) - Exploring Sustainable Manufacturing Using Circular Economy (S. Shahrokni) - Adaption of Circular Economy in the Supply Chain (D. Soundankar) - A Review of the Impacts of Thermal Spraying Technologies and Electrocatalysts in Green H2 Production (S. Tchinou) - Review of Resin Injection Repair of Composites (A. Zaki) # Virtual and Augmented Reality Tools in Manufacturing - Augmented Reality in Manufacturing Industries (S. Kappil Muralidasan) - Augmented Reality: Improving Productivity and Reducing Failure for New Workers and New Tasks (G. Sanchez Garcia) - Applications of Virtual Reality in Manufacturing (V. Sivakumar)

Unternehmen werden gegenwärtig mit den Themen der Nachhaltigkeit und der fortschreitenden Industrie 4.0 vor immer komplexere Herausforderungen gestellt. Ein Bestandteil der neuen Basistechnologien stellen cyber-physische Systeme (CPS) dar, die bereits gegenwärtig und zukünftig mit den Zielen der nachhaltigen Entwicklung in Einklang gebracht werden müssen. Die vorliegende Arbeit geht den Forschungsfragen nach, wie CPS definiert, charakterisiert und unter Einbezug nachhaltiger Kriterien bewertet werden können. Dazu wurden verschiedene, betriebswirtschaftliche Instrumentarien ausgewählt und systematisiert, die folgend im eigens entwickelten und angewandten „Vorgehensmodell zur Prüfung und Eignung von Bewertungsinstrumenten für CPS unter Einbezug der Nachhaltigkeit“ überprüft wurden. Die Untersuchung ergab, dass der Bedarf an Bewertungsansätzen von CPS in Kombination mit der Thematik der Nachhaltigkeit besteht und mit existenten, betriebswirtschaftlichen Methoden größtenteils bewältigt werden kann. Die zugrunde liegende Masterarbeit wurde an der Professur Unternehmensrechnung und Controlling (Technische Universität Chemnitz) durch Prof. Dr. Prof. h. c. Uwe Götze sowie Kristina Höse (M.Sc.) betreut. / Companies are currently facing increasingly complex challenges with the issues of sustainability and the advancing Industry 4.0. One component of the new enabling technologies are cyber-physical systems (CPS), which already currently and in the future need to be aligned with sustainable development goals. This thesis addresses the research questions of how CPS can be defined, characterized and evaluated with respect to sustainable criteria. For this purpose, various business management tools were selected and systematized, which were subsequently reviewed in the specially developed and applied 'Procedure Model for the Examination and Suitability of Assessment Tools for CPS with the Inclusion of Sustainability'. The investigation showed that the need for evaluation approaches of CPS in combination with the topic of sustainability exists and can be handled with existing, business management methods to a large extent.

Currently manufacturers in the European Surface Mount Technology (SMT) industry seeproduction changeover, machine downtime and process optimization as their biggestchallenges. They also see a need for collecting data and sharing information betweenmachines, people and systems involved in the manufacturing process. Internet of Things (IoT)technology provides an opportunity to make this happen. This research project gives answers tothe question of what the potentials and challenges of IoT implementation are in European SMTmanufacturing. First, key IoT concepts are introduced. Then, through interviews with expertsworking in SMT manufacturing, the current standpoint of the SMT industry is defined. The studypinpoints obstacles in SMT IoT implementation and proposes a solution. Firstly, local datacollection and sharing needs to be achieved through the use of standardized IoT protocols andAPIs. Secondly, because SMT manufacturers do not trust that sensitive data will remain securein the Cloud, a separation of proprietary data and statistical data is needed in order take a stepfurther and collect Big Data in a Cloud service. This will allow for new services to be offered byequipment manufacturers. / I dagsläget upplever tillverkare inom den europeiska ytmonteringsindustrin för elektronikproduktionsomställningar, nedtid för maskiner och processoptimering som sina störstautmaningar. De ser även ett behov av att samla data och dela information mellan maskiner,människor och system som som är delaktiga i tillverkningsprocessen.Sakernas internet, även kallat Internet of Things (IoT), erbjuder teknik som kan göra dettamöjligt. Det här forskningsprojektet besvarar frågan om vilken potential som finns samt vilkautmaningar en implementation av sakernas internet inom europeisk ytmonteringstillverkning avelektronik innebär. Till att börja med introduceras nyckelkoncept inom sakernas internet. Sedandefinieras utgångsläget i elektroniktillverkningsindustrin genom intervjuer med experter.Studien belyser de hinder som ligger i vägen för implementation och föreslår en lösning. Dettainnebär först och främst att datainsamling och delning av data måste uppnås genomanvändning av standardiserade protokoll för sakernas internet ochapplikationsprogrammeringsgränssnitt (APIer). På grund av att elektroniktillverkare inte litar påatt känslig data förblir säker i molnet måste proprietär data separeras från statistisk data. Dettaför att möjliggöra nästa steg som är insamling av så kallad Big Data i en molntjänst. Dettamöjliggör i sin tur för tillverkaren av produktionsmaskiner att erbjuda nya tjänster.

Den globala industrin har under det senaste decenniet genomgått en enorm digital transformation, där tillämpandet av digitala och smarta verktyg inom företag aldrig har varit mer påtagligt. Under november 2011 presenterades begreppet Industrial 4.0 i en artikel skriven av den Tyska regeringen som beskriver en teknikintensiv strategi för år 2020 och omfattar vad idag betraktas som den fjärde industriella revolutionen. Industri 4.0 utgörs till stor del av integrationsprocessen mellan teknik och övrig verksamhet inom ett tillverkningsföretag, vilket i sin tur ger upphov till teknik såsom; automation, förstärkt verklighet, simuleringar, intelligenta tillverkningsprocesser samt övriga processindustriella IT-verktyg och -system. Flertal forskningsstudier hävdar att Industri 4.0-teknologier har potential att revolutionera sättet företag idag tillverkar produkter, men i och med att begreppet är relativt nytt, abstrakt samt består av väldigt komplexa tekniker och komponenter, är införandet av dessa inom en tillverkningsmiljö för närvarande en stor utmaning för tillverkande företag. Denna studie syftar alltså till att belysa de utmaningar och hinder som större tillverkande företag möter vid implementering av digital och smart teknik, samt åtgärder för att motverka dessa. Målet med studien är att leverera ett användbart resultat både för aktiva företag inom tillverkningsindustrin i form av stöd vid analys och diskussion av eventuella implementeringsstrategier och -satsningar inom Industri 4.0, men också ge övriga intressenter en uppfattning kring ämnet med tanke på att det, som sagt, är ett abstrakt system. En litteraturstudie genomfördes både för att få en överblick kring ämnet Industri 4.0 och hur det har behandlats i tidigare examensarbeten, avhandlingar samt forskningsstudier, men även för att identifiera tidigare identifierade hinder. Därefter genomfördes fältstudier på två tillverkande företag, Scania och Atlas Copco, samt teknikkonsultföretaget Knightec. Syftet med detta var framförallt att få en mer påtaglig och verklighetsförankrad uppfattning av Industri 4.0 men även verifiera att informationen i den teoretiska delen är relevant i praktiken för en tillverkande verksamhet. Studien påvisade därtill att identifierade utmaningar och hinder återfinns bland flertal organisatoriska områden inom ett tillverkande företag, varav de mest framgående aspekterna omfattade strategi, ledarskap, kunder, kultur, anställda, juridik samt teknik. Resultatet avslöjade vidare att tillverkande företag präglas av bristfälliga planer och strategier för att identifiera samt implementera nya tekniska lösningar, konflikter bland de anställda, svårigheter att integrera kundsystem enhetligt inom produktionen, avsaknad av lämplig teknisk kompetens, juridiska problem vad gäller hantering av data samt svårigheter att integrera nya och gamla teknologier. / The global industry has during the last decade undergone a considerable digital transformation, whereas the application of digital and smart technology within companies has never been more of a relevant field. During November of 2011, the term Industrial 4.0 was presented in an article written by the German government to describe a technology intensive strategy for the year 2020 and signifies what today is defined as the fourth industrial revolution. Industry 4.0 largely consists of the integration process between technology and remaining operations within a manufacturing company, which enables the development of technologies such as; automation, augmented reality, simulations, intelligent manufacturing processes and other process industrial IT-tools and systems. Several research studies has suggested that Industry 4.0 technologies has the potential to revolutionize the way companies today manufacture products, however, since the concept is relatively new, abstract and consists of various complex technologies and components, the implementation process of these within a manufacturing environment is one largest challenges that manufacturing companies are facing. This study therefore aims to highlight the challenges and difficulties that large manufacturing companies are facing when implementing digital and smart technology, as well as provide solutions regarding how they can be overcome. The overall goal is to deliver useful results both for active companies within the manufacturing industry in regards to serving as support when analyzing and discussing possible implementation strategies as well investments related to Industry 4.0, but also to provide surrounding stakeholders with a perception of the subject. At the commencement of the project, a literature study was performed to develop an overview of how Industry 4.0 has been discussed in previous theses and research studies as well as to find previously identified difficulties regarding the implementation process. Finally, a field study was performed at Scania and Atlas Copco and at the technology consulting firm Knightec. The main purpose was to gain a more realistic perspective regarding how digitalization and Industry 4.0 systems are applied and to verify that the information from our theoretical study is relevant and applicable within an actual manufacturing company. The study furthermore revealed that the identified difficulties and challenges can be found within multiple organizational areas of a manufacturing company, whereas the most distinct aspects consisted of strategy, leadership, customers, culture, employees, legal governance as well as technology. The results showed that companies were characterized by an overall lack of strategy to implement new technologies, conflicts with employees during implementation, difficulties to integrate customer orders with production, lack of technical skills in staff, legal issues regarding data storage and difficulties integrating new and old technologies.

<p>Program anomaly detection — modeling normal program executions to detect deviations at runtime as cues for possible exploits — has become a popular approach for software security. To leverage high performance modeling and complete tracing, existing techniques however focus on subsets of applications, e.g., on system calls or calls to predefined libraries. Due to limited scope, it is insufficient to detect subtle control-oriented and data-oriented attacks that introduces new illegal call relationships at the application level. Also such techniques are hard to apply on devices that lack a clear separation between OS and the application layer. This dissertation advances the design and implementation of program anomaly detection techniques by providing application context for library and system calls making it powerful for detecting advanced attacks targeted at manipulating intra- and inter-procedural control-flow and decision variables. </p> <p><br></p> <p>This dissertation has two main parts. The first part describes a statically initialized generic calling context program anomaly detection technique LANCET based on Hidden Markov Modeling to provide security against control-oriented attacks at program runtime. It also establishes an efficient execution tracing mechanism facilitated through source code instrumentation of applications. The second part describes a program anomaly detection framework EDISON to provide security against data-oriented attacks using graph representation learning and language models for intra and inter-procedural behavioral modeling respectively.</p> <p><br> This dissertation makes three high-level contributions. First, the concise descriptions demonstrates the design, implementation and extensive evaluation of an aggregation-based anomaly detection technique using fine-grained generic calling context-sensitive modeling that allows for scaling the detection over entire applications. Second, the precise descriptions show the design, implementation, and extensive evaluation of a detection technique that maps runtime traces to the program’s control-flow graph and leverages graphical feature representation to learn dynamic program behavior. Finally, this dissertation provides details and experience for designing program anomaly detection frameworks from high-level concepts, design, to low-level implementation techniques.</p>

The Advanced Manufacturing Student Conference (AMSC) represents an educational format designed to foster the acquisition and application of skills related to Research Methods in Engineering Sciences. Participating students are required to write and submit a conference paper and are given the opportunity to present their findings at the conference. The AMSC provides a tremendous opportunity for participants to practice critical skills associated with scientific publication. Conference Proceedings of the conference will benefit readers by providing updates on critical topics and recent progress in the advanced manufacturing engineering and technologies and, at the same time, will aid the transfer of valuable knowledge to the next generation of academics and practitioners. *** The first AMSC Conference Proceeding (AMSC21) addressed the following topics: Advances in “classical” Manufacturing Technologies, Technology and Application of Additive Manufacturing, Digitalization of Industrial Production (Industry 4.0), Advances in the field of Cyber-Physical Systems, Virtual and Augmented Reality Technologies throughout the entire product Life Cycle, Human-machine-environment interaction and Management and life cycle assessment.:- Advances in “classical” Manufacturing Technologies - Technology and Application of Additive Manufacturing - Digitalization of Industrial Production (Industry 4.0) - Advances in the field of Cyber-Physical Systems - Virtual and Augmented Reality Technologies throughout the entire product Life Cycle - Human-machine-environment interaction - Management and life cycle assessment

The conference proceedings contain the abstracts of the 2nd edition of the Advanced Manufacturing Student Conference (AMSC). The second edition of the conference (AMSC22) was again jointly organised by the Faculty of Mechanical Engineering at Chemnitz University of Technology and the Fraunhofer Institute for Machine Tools and Forming Technology. The AMSC is an educational format designed to promote the acquisition and application of skills related to Research Methods in Engineering Sciences. Participating students are required to write and submit a conference paper and are given the opportunity to present their findings during the conference. The conference itself is intended to serve as a platform for networking at an early career stage. Thus, the AMSC22 provides a tremendous opportunity for participants to practice critical skills associated with scientific publication. The conference proceedings provide a broad overview of the field of advanced manufacturing.:# Foreword # Scientific Committee & Board of Reviewers # Session 1 - A study of the contribution of Additive Manufacturing towards Environmental Sustainability - An analysis about the role of Inkjet devices in Additive Manufacturing - The impact of selected process parameters on dimensional accuracy of fused deposition modeling manufactured parts - Part Cooling Techniques in Additive Manufacturing Process - Effects of Cooling Techniques in WAAM - A Review on Wear Resistance of High-Entropy Alloy Coatings - Importance of Augmented Reality in Automotive Industry - Additive Manufacturing in Aerospace Industry - An Overview of 3D Printing in the Healthcare Industry # Session 2 - Comparison of Additive Manufacturing and Traditional Manufacturing - An analysis on multi-material printing using methods of Additive Manufacturing - A Review on Use of Life Cycle Assessment in Decision-Making - A review of feasibility of diffusion bonding in additive manufacturing and its applications - The Life Cycle Engineering Analysis of Additive Manufacturing Technology - Enterprise Resource Planning - An Industry 4.0 Technology for Operational Efficiency - A review of process and application limits in the field of powder based Additive Manufacturing technologies - 3D Printing processes, materials in Industry 4.0 - A review on efficiency and productivity analysis of human-machine interaction in industry 4.0 # Session 3 - A review of Ultrasonic Additive Manufacturing Technology and Application - The effectiveness of combining rolling deformation with Wire–Arc Additive Manufacturing - A Review of Quality-Related Cost Accounting or Appraisal Methods Using the Example of Additive Manufacturing - Implementing visualization techniques to show the intended motion of Automated Guided Vehicles (AGVs) on the real environment: A review - Discussion on Additive Manufacturing Technology from an Environmental Perspective - Overview of cognitive manufacturing technology in production industries - A review on high velocity oxygen fuel thermal spraying in respective applications - Recognition of Additive section through Diffusion Bonding - Review of lattice structure defects in components manufactured by powder bed fusion process # Session 4 - Biomaterials used for Prosthetic/Implant 3d Printing - Comparison of Conventional and Additive Manufacturing Techniques from an Economic Perspective - Life Cycle Assessment on Natural Fiber Composites - A Review on Design Optimization for Additive Manufacturing - Industry 4.0: Impact on Environmental Sustainability - Review of cyber physical system integrated with augmented reality in various aspects of additive manufacturing - A review of scenarios in selection of milk Packaging by environmental impacts - Review of the integration of Life Cycle Assessment, Environmental Risk Assessment, and Ecosystem Services Assessment about human activities and environmental impact - A review on how Da Vinci surgical system is changing the health care # Session 5 - Integration of Digital twin in manufacturing industries, principal concept, and comparison - An overview of Powder-bed Fusion based Manufacturing process - A review on integration of carbon fiber materials in automotive industry - Review of generating the technologies of organic composite phase change materials in energy storage - Integration of Lean Manufacturing Principles and Industry 4.0 - Pultrusion of carbon/epoxy composites for aerospace applications - new developments and modelling studies - A Review on Stitching Methods for the Inkjet Nozzles - A Review of Digital Twin and its Potential Role in Technical System Development and Operations - Customization using additive manufacturing in industry 4.0 # Session 6 - Effect of Al2O3 particles and mustard oil as lubrication on machining process and a review - A Process-Oriented Review of Supply Chain Management in Automobile Industry - Environmental Impact Assessment on Recycling of Lithium-ion Battery - Methods and Applications of Multi-Material Additive Manufacturing - Fundamental analysis of 3D printing in Dentistry - A review of production methods of Carbon Nanotubes - A review of the environmental compatibility of superconductors - Pros and Cons of applying Fourth Industrial Revolution in a Production Plant: A Review - Intelligence Amplification as a cutting-edge forecasting method: investigation of AI applications, their impacts on our society and their path toward hybrid intelligent systems # Session 7 - Quality Engineering Challenges in Additive Manufacturing - Additive Manufacturing Techniques of 3D Model Hollowing Objects - Implementing Cyber-Physical Systems in Autonomous Micro/Nano Assembly Operations - Producing edge welded bellows seals by using laser welding - An Overview of Additive Manufacturing in the Automotive Industry: study cases and viability - A Review of Digital Twin in Manufacturing

Den fjärde industriella revolutionen, även kallad Industri 4.0, drivs av ett antal teknologier som medför digitalisering och automatisering av industriella processer. Konceptet innebär en applicering av dataanalys med avancerade analytiska verktyg på stora mängder data, vilka påstås ge stora möjligheter för kvalitetsförbättringar. För att en sådan övergång ska ske är förmågan att hantera data avgörande. Trots det uppvisar många företag idag bristande användning av data för att ta beslut. Frågan är hur företag kan göra för att hantera data och utföra en transformation till Industri 4.0. För att studera det här ämnet har det här examensarbetet utförts som en fallstudie på en stansprocess hos Scania Ferruform. Genom en litteraturstudie, kvantitativ datainsamling samt observationer och intervjuer undersökte examensarbetet den nuvarande användning av data i processen. Därefter undersöktes data med statistiska verktyg för att visa på hur data kan hanteras i en process för att erhålla större kunskap om orsaker till avvikelser. Examensarbetet utredde till sist hur fortsatt arbete med datahantering kan utföras för att uppnå målet Industri 4.0.Analysverktyg har använts för att analysera över 39 000 datapunkter. Resultatet visar på att det finns utvecklingsmöjligheter vad gäller insamling, kvalitet och användning av data. Ett ramverk presenteras för hur företaget bör hantera data för att kunna utvinna ny kunskap från deras processer samt hur Ferruform fortsatt kan arbeta mot Industri 4.0.Slutligen ges rekommendationer om fortsatta studier. Resultatet av examensarbetet blir ett stöd för Ferruform i deras arbete mot mer dugliga processer och den tekniska utveckling företaget eftersträvar. / The fourth industrial revolution, also called Industry 4.0 is powered by several technologies which result in digitalization and automatization of industrial processes. The concept includes the application of big data and advanced analytics, which are said to provide great opportunities for quality improvements. For such a transition to take place, the ability to handle data is crucial. Despite this, many companies today show a lack of use of data to drive decision-making. The question is how companies can manage data and ultimately transition towards Industry 4.0. To research this topic this thesis has been carried out as a case study of a punching process at Scania Ferruform. Through a literature review, quantitative data collection, as well as observations and interviews, the thesis examined the current use of data in the process. Subsequently, data were examined with statistical tools to illustrate how data can be managed in a process to attain increased knowledge about causes of deviations. Lastly, the thesis explored future work towards Industry 4.0. Analysis tools have been used to analyse over 39 000 data points. The result of the study shows that there are opportunities for development in terms of collection, quality and use of data. A framework of how Ferruform should manage data in order to extract new knowledge from its processes is presented. Furthermore, an action plan is presented for a transition towards Industry 4.0. Finally, recommendations are given for further studies. The result of the thesis will be helpful for Ferruform in its transition towards more efficient processes and the technical development of which the company strives towards.

Объект исследования – кибер-физические системы, подверженные различным инцидентам, отказам и сбоям в своей работе. Цель работы – разработка модели машинного обучения для определения корневых причин сбоев в производственной системе, а также исследование возможности использования машинного обучения для определения причин будущих сбоев. Методы исследования: сбор, анализ и синтез данных, сравнение, обобщение, классификация, аналогия, эксперимент, измерение, описание. Результаты работы: разработана и обучена модель машинного обучения для анализа корневых причин инцидентов производственной установки методом классификации на выбранном наборе «сырых» данных небольшого объема с последующей проверкой качества ее работы на тестовых данных. Область применения – обучение модели корневым причинам инцидентов (отказов, сбоев) производственных систем на имеющихся данных с последующим оперативным обнаружением причин аномальной работы систем в тандеме с работой алгоритма по автоматическому обнаружению и прогнозированию аномалий. / The object of research is cyber-physical systems that are susceptible to various incidents, failures and malfunctions in their operation. The goal of the work is to develop a machine learning model to determine the root causes of failures in a production system, as well as to explore the possibility of using machine learning to determine the causes of future failures. Research methods: collection, analysis and synthesis of data, comparison, generalization, classification, analogy, experiment, measurement, description. Results of the work: a machine learning model was developed and trained to analyze the root causes of incidents in a production facility using the classification method on a selected set of small-volume “raw” data, followed by checking the quality of its work on test data. Scope of application: training a model for the root causes of incidents (failures, failures) of production systems using available data, followed by prompt detection of the causes of abnormal operation of systems in tandem with the work of the algorithm for automatic detection and prediction of anomalies.