Digitaliseringen inom industrin medför ett antal utmaningar där manuella tillståndskontroller övergår till digitaliserade mätningar. Utmaningarna som uppstår med det nya arbetssättet är vilken data som ska samlas in samt hur den genererade data ska analyseras. Syftet med detta examensarbete är att förslå åtgärder för att effektivisera och implementera Industri 4.0 (Smart Maintenance) genom prediktivt underhåll på Scania. Således uppnås en mer kostnadseffektiv verksamhet samtidigt som det bidrar till att skapa ett hållbarare företag. Detta genom att utnyttja komponenters fulla livslängd och inte utföra onödigt underhåll. Det prediktiva underhållet kommer medföra en högre tillgänglighet och tillförlitlighet inom maskinparken på Scanias cylinderhuvudlinje. För att implementera underhållsstrategin i examensarbetet så används en mjukvara som skapats av styrsystems leverantör FANUC. Mjukvaran är ett mätverktyg som heter Servo Viewer och kan mäta maskinens status genom att avläsa procentsatsen utav den totala mängden vridmoment som bildas samt positionsfel under maskinens körning. Ett arbetssätt för att automatisera analysering av data som hämtas ifrån Servo Viewer är att mätningarna samlas i databasen MT-LINKi för att sedan kunna analyseras av ett program FANUC AI Servo Monitor. Den slutsats som kan dras av arbetet är att det går att använda FANUC Servo Viewer till att avläsa maskinens kondition och därmed prediktera när underhåll behöver utföras eftersom det går att avläsa avvikande faktorer under mätningarna. Vid dessa faktorer går det att sätta triggers som kommer larma i systemet när maskinen överstiger dem. De komponenter som mjukvaran kommer varna systemet för är alla komponenter som har en påverkande faktor på fleroperationsmaskinen. Dessa komponenter kan vara allt från kulskruvar, linjärstyrning, pulsgivare, remmar, servomotorer och servokort. Men arbetet är inte ett färdigt koncept i sig, det behövs fler mätningar över tid för att kunna skapa ett tydligare normalläge samt identifiera felutvecklingskurvor för att ställa in triggers i mjukvaran. Eftersom analys och insamling av mätdata blev mer tidkrävande än planerat så har ej utvärderingen av MT-LINKi samt AI Servo Monitor utförts och en vidare beskrivning av arbetet har lämnats. / Digitalization in the manufacturing industry involves many challenges due to moving from manual controls towards digitalized condition monitoring. The challenges that occur with the new way of working is what data should be collected and how it should be analyzed. This thesis aims to streamline the industry and implement Industry 4.0 and Smart Maintenance through predictive maintenance in Scania. In this way a more cost-effective business is achieved at the same time as it contributes to creating a more sustainable company. The predictive maintenance will lead to a higher availability and reliability within the machine park at Scania´s cylinder head line. To be able to implement the maintenance strategy a software created by FANUC, the system supplier, is used. The software is a measuring tool called Servo Viewer and it can analyze the status of the machine by measuring the percentage of the total amount of torque that is available and the position error while the machine is running. The thesis also aims to investigate how to automatize the measurements within a database called MT-LINKi and later be analyzed by a software called AI Servo Monitor. The conclusion that can be drawn from the thesis is that it is possible to use FANUC Servo Viewer to measure the condition of the machine and therefore being able to predict when the maintenance needs to be performed as it is possible to read deviating factors during the measurements. With these factors it is possible to set triggers that will alarm the system when the machine exceeds them. Some of the components that will be possible to monitor condition for, are ball screws, linear control, encoders, belts, servomotors and servo cards. However the work isn’t not a complete concept in itself, more measurements are needed to be performed over time to create a normal situation and identify error development graphs to set the triggers in the software. As analysis and collection of measurement data became more time consuming than planned, the evaluation of MT-LINKi and AI Servo Monitor has not been performed and a further description of the work has been provided.

Yes / The developments brought by Industry 4.0 have spread to various components in a supply chain, where logistics is of utmost importance due to the intermediate role of logistics service providers (LSPs) operating among different actors. Despite such a vital role, the extant literature lacks from the extensive analysis of Industry 4.0 implementations in the logistics industry, particularly for LSPs. Accordingly, this study sets out to investigate, comprehensively, Industry 4.0 projections in logistics and their reflections on LSPs by adopting a multidimensional approach. In this respect, the key themes influenced by Industry 4.0 developments are initially determined through a structured survey conducted in the Turkish logistics industry. Then, in the same industry, both the probabilities and the impacts of Industry 4.0-focused thematic statements are examined through an integrative interview survey, which also incorporates ‘why-type’ of questions. Consequently, this study offers academic implications in terms of demonstrating possible changes in the logistics industry from the operational, financial, and human resources aspects. Additionally, the findings serve as a reference for logistics professionals while fostering their competitive Industry 4.0 initiatives and facilitating their strategic decisions.

Library conference presentation / Today, academic libraries are not only providing access to books and space to users, but they also offer a digital environment that enables patrons to use the library without visiting them physically. Like living organisms, libraries are influenced by external pressures to constantly evolve, including, changing information technology environment and greater dependence on web-based services. Some large academic libraries, for example, use automated robots in combination with RFID technology and data from the library’s bibliographic and holdings records to retrieve from storage and deliver books that have been requested by users. Whilst this application of technology is newer for libraries, it is not cutting-edge for the industry. However, it is an example of how libraries are already making use of the processes that are arising out of developments, which are increasingly part of the new industrial revolution. It seems reasonable to expect that in the future, as we will see increasing use of Industry 4.0 style technologies and processes applied to the execution of routine library work and services for patrons. The new requirement for universities is to be able to track the skills demands within the industry and move quickly to make sure that students leave their education ready to add real value to business internationally. Since academic libraries are part of a university set-up, they exist to serve the goals of its organization. Therefore, every library programme must and should support universities total programme

Die europäische Fertigungsindustrie steht vor großen Veränderungen, die durch die zunehmende Nachfrage der Kunden nach maßgeschneiderten und/oder intelligenten Produkten, Industrie 4.0 Lösungen und Öffnung der Produktionsketten für Newcomer getrieben werden sowie durch die Veränderung hin zu Wertschöpfungsketten, in denen die Rollen von Lieferanten, Herstellern und Einzelhändlern verschwimmen. Diese sich dynamisch wandelnde Umwelt erfordert eine Anpassungsfähigkeit der Mitarbeiter, Fertigungswerkzeuge und Prozesse. Neue IKT-basierte Lösungen erleichtern einen Paradigmenwechsel, der Fabrikarbeiter als zukünftige "Wissensarbeiter" in den intelligenten Fabriken sieht, welcher nicht nur durch die Einführung neuer Technologien in die Fabriken gelingen kann. Arbeitsabläufe müssen umgestaltet werden und neue Ansätze zur kontinuierlichen Weiterentwicklung sind erforderlich. Bei der Verschiebung der Arbeitsaufgaben hin zur Wissensarbeit müssen bei der Anpassung der Arbeitsumgebungen zunehmend die Unterschiede bei den kognitiven Fähigkeiten berücksichtigt werden. Das hier vorgestellte Forschungsprojekt Factory2Fit zielt darauf ab, die menschlich zentrierte Fertigung auf ein neues Niveau zu bringen, indem den Mitarbeitern eine führende Rolle bei der Anpassung und Entwicklung ihrer eigenen Aufgaben zukommt. Das Hauptziel des Projektes ist es, adaptive Automatisierungslösungen zu entwickeln und zu pilotieren, die den Arbeitsablauf verbessern, den Arbeitnehmer dabei unterstützen, seine Kompetenzen zu entwickeln und die Mitarbeiter dazu befähigen, Wissen zu teilen und sich an der Gestaltung ihrer eigenen Arbeit zu beteiligen. Das Projekt Factory2Fit wird von Horizon 2020 (H2020/2014-2020), dem Programm für Forschung und Innovation der Europäischen Union, unter der Zuwendungsvereinbarung Nr. 723277 gefördert.

<p>Истраживање у докторској дисертацији односи се на примену организационих и технолошких концепата у прерађивачком сектору, са акцентом на њихов допринос савременим трендовима производње, дефинисаним у оквиру Индустрије 4.0. Основни циљ истраживања је да се развије концептуални модел за евалуацију организационих и технолошких концепата у прерађивачком сектору, а након тога да се модел емпиријски примени са циљем утврђивања специфичних концепата који, посматрано из перспективе савремених производних трендова, имају највећи значај за компаније. За сврхе овог истраживања коришћене су методе за вишекритеријумско одлучивање. Развијени модел може се користити у будућим истраживањима, док се резултати могу користити за стратешку оријентацију компанија које су заинтересоване да се прилагоде и да послују у складу са савременим трендовима производње.</p> / <p>Istraživanje u doktorskoj disertaciji odnosi se na primenu organizacionih i tehnoloških koncepata u prerađivačkom sektoru, sa akcentom na njihov doprinos savremenim trendovima proizvodnje, definisanim u okviru Industrije 4.0. Osnovni cilj istraživanja je da se razvije konceptualni model za evaluaciju organizacionih i tehnoloških koncepata u prerađivačkom sektoru, a nakon toga da se model empirijski primeni sa ciljem utvrđivanja specifičnih koncepata koji, posmatrano iz perspektive savremenih proizvodnih trendova, imaju najveći značaj za kompanije. Za svrhe ovog istraživanja korišćene su metode za višekriterijumsko odlučivanje. Razvijeni model može se koristiti u budućim istraživanjima, dok se rezultati mogu koristiti za stratešku orijentaciju kompanija koje su zainteresovane da se prilagode i da posluju u skladu sa savremenim trendovima proizvodnje.</p> / <p>This research is related to the use of organizational and technological<br />concepts in manufacturing companies, highlighting their contribution to the<br />production principles of Industry 4.0. The main purpose of this research is to<br />develop a model for evaluation of organizational and technological concepts<br />in the manufacturing sector from the perspective of Industry 4.0.<br />Consequently, the model was used to determine which organizational and<br />technological concepts are contributing the most to the production principles<br />of Industry 4.0. The developed model could be used in future research, while<br />the results presented in this research could serve for strategic orientation of<br />manufacturers.</p>

Digitalization is finding it’s way into production and machine-building. Autonomous, sefoptimizing and highly interconnected units will determine the functionality of machines and production facilities. Communication and automation layout will fundamentally change, data will be more and more the base for new business modells. Innovation is determining pneumatics and handling technology. The innovation topics performance improvement, modular and mechatronic design of systems, sustainability and efficiency are keeping pneumatics and vacuum technology on the pathway of success. But is the technology field also prepared for the tremendous challenges caused by the digitalization? This paper is focusing on the significance of digitalization for fluid technology, especially for pneumatics and vacuum technology. The new concepts of digitalization and autonomization are based on the Internet of Things with open Communication of cyber-physical systems. These cyber-physical systems are able to react autonoumously. Cyber-physical systems can collect, interpret and analys data and transfer it into valuable information. Based on these data, cyberphysical systems will provide services to all participants of the smart factory. There will be a digital image inside the factory cloud, which is the base of new business models. Systems of pneumatics, vacuum technology and hydraulics will play a core role in this world. They are placed directly at the interface to the real technical process, they have direct contact with the workpieces, they are collecting multitude of sensor data and are evaulating it, they have functionality like Condition Monitoring and Energy Efficiency optimization on board and are able to communicate with the world of automation. This paper will show, that the innovation trends of the last years are supporting the way towards digitalization and Industrial Internet of Things. There are already a lot of different approaches to establish vacuum and pneumatic systems as adequate elements of the digitalized world. It will also be shown, that fluid technology still is facing tremendous challenges It will be not sufficient to equip the systems with more functionality and better communication. It will be essential, that from the interpretation and correlation of data will be derived valuable services with real customer benefit. This should happen under control of the vendors of smart field devices in fluid technology. Then it will be possible to turn this new kind of value generation also into new business models.

工業4.0自從被工業大國的德國提出後，不僅啟發製造業生產觀念的改變，更促進業者積極落實，並且如火如荼地在美、日、中國等製造業國家蔓延發展，美國提出”工業互聯網”、”中國提出”中國製造2025”、而台灣也提出”生產力4.0計畫”。因此，製造業生產之源的設備供應商更需積極投入工業4.0的發展。有鑑於此，設備供應商業者如何為其製造業客戶發展工業4.0，進而建立推動的策略與模式，進而利於設備供應商整體績效的提昇，即是本研究的主軸。 本研究不僅針對工業4.0進行文獻探討，並從個案公司營運現況、產業結構、工業4.0狀況等三方向進行分析，以其萃取其重要的關鍵要素，而期益於個案公司為其客戶推動工業4.0與推動策略與模式的建立，並利於設備供應商產業推動工業4.0研究領域之發展。

Location Based Services (LBS) are a relatively recent multidisciplinary field which brings together many aspects of the fields of hardware design, digital signal processing (DSP), digital image processing (DIP), algorithm design in mathematics, and systematic implementation. LBS provide indirect location information from a variety of sensors and present these in an understandable and intuitive way to users by employing theories of data science and deep learning. Indoor positioning, which is one of the sub-applications of LBS, has become increasingly important with the development of sensor techniques and smart algorithms. The aim of this thesis is to explore the utilisation of indoor positioning algorithms under complex Non-Line of sight (LOS) environments in order to meet the requirements of both commercial and civil indoor localisation services. This thesis presents specific designs and implementations of solutions for indoor positioning systems from signal processing to positioning algorithms. Recently, with the advent of the protocol for the Bluetooth 4.0 technique, which is also called Bluetooth Low Energy (BLE), researchers have increasingly begun to focus on developing received signal strength (RSS) based indoor localisation systems, as BLE based indoor positioning systems boast the advantages of lower cost and easier deployment condition. At the meantime, information providers of indoor positioning systems are not limited by RSS based sensors. Accelerometer and magnetic field sensors may also being applied for providing positioning information by referring to the users' motion and orientation. With regards to this, both indoor localisation accuracy and positioning system stability can be increased by using hybrid positioning information sources in which these sensors are utilised in tandem. Whereas both RSS based sensors, such as BLE sensors, and other positioning information providers are limited by the fact that positioning information cannot be observed or acquired directly, which can be summarised into the Hidden Markov Mode (HMM). This work conducts a basic survey of indoor positioning systems, which include localisation platforms, using different hardware and different positioning algorithms based on these positioning platforms. By comparing the advantages of different hardware platforms and their corresponding algorithms, a Received Signal Strength Indicator (RSSI) based positioning technique using BLE is selected as the main carrier of the proposed positioning systems in this research. The transmission characteristics of BLE signals are then introduced, and the basic theory of indoor transmission modes is detailed. Two filters, the smooth filter and the wavelet filter are utilised to de-noise the RSSI sequence in order to increase localisation accuracy. The theory behind these two filter types is introduced, and a set of experiments are conducted to compare the performance of these filters. The utilisation of two positioning systems is then introduced. A novel, off-set centroid core localisation algorithm is proposed firstly and the second one is a modified Monte Carlo localisation (MCL) algorithm based system. The first positioning algorithm utilises BLE as a positioning information provider and is implemented with a weighted framework for increasing localisation accuracy and system stability. The MCL algorithm is tailor-made in order to locate users' position in an indoor environment using BLE and data received by sensors locating user position in an indoor environment. The key features in these systems are summarised in the following: the capacity of BLE to compute user position and achieve good adaptability in different environmental conditions, and the compatibility of implementing different information sources into these systems is very high. The contributions of this thesis are as follows: Two different filters were tailor-made for de-nosing the RSSI sequence. By applying these two filters, the localisation error caused by small scale fading is reduced significantly. In addition, the implementation for the two proposed are described. By using the proposed centroid core positioning algorithm in combination with a weighted framework, localisation inaccuracy is no greater than 5 metres under most complex indoor environmental conditions. Furthermore, MCL is modified and tailored for use with BLE and other sensor readings in order to compute user positioning in complex indoor environments. By using sensor readings from BLE beacons and other sensors, the stability and accuracy of the MCL based indoor position system is increased further.

Vi lever i ett samhälle som ständigt digitaliseras och det påverkas oss alla i olika stor utsträckning. För tillverkande organisationer innebär detta ett paradigmskifte i form av en övergång från Industri 3.0 till Industri 4.0. Industri 4.0 berikar produktionen med digitala sammankopplingar, automatiserade lösningar, big data och artificiell intelligens (AI). Digitala tvillingar utgör en viktig del av Industri 4.0 och beskrivs som lösningen på många av dagens problem. Att hantera övergången och skapa digitala tvillingar har visat sig vara en utmaning för många av dagens tillverkande organisationer. Hur den praktiska tillämpningen kan ske har inte behandlats i någon större utsträckning i tidigare forskning. Denna studie har för avsikt att fylla detta forskningsgap och således skapades studiens forskningsfråga: ”Hur kan en tillverkande organisation skapa, implementera och integrera en digital tvilling över materialflödet för att utveckla ett effektivare arbetssätt?” För att besvara forskningsfrågan genomfördes en fallstudie på BAE Systems Hägglunds, Örnsköldsvik. Organisationen har en tillverkning som till största del utgörs av kundspecifika produkter som ofta tillverkas i korta serier. Studien utgick från beprövade metoder och verktyg gällande kartläggning. Kartläggningen genomfördes med hjälp av intervjuer, observationer och samtal med medarbetarna vid organisationen. Genom tidigare forskning, intervjuer och observationer skapades en processmodell över hur en tillverkande organisation kan gå till väga för att skapa en digital tvilling övermaterialflödet för att därefter implementera och integrera den i sin befintliga verksamhet. Resultatet av studien visar att det krävs teknisk kunskap och praktisk erfarenhet för att skapa, implementera och integrera en digital tvilling över materialflödet för att utveckla ett effektivare arbetssätt. Inledningsvis så visar studien att det krävs en förståelse för nuläget. Därutöver krävs det en samsyn gällande vad en digital tvilling är för organisationen samt vilken funktion den ska fylla. Vidare visar studien att det krävs en datainsamlingsmetod som återger korrekt information i realtid. Studien visar även att information och utbildning i den digitala tekniken kan vara avgörande faktorer för att lyckas med implementeringen och integreringen. Slutligen bidrar studien med praktiska rekommendationer på hur en tillverkande organisation kan skapa, implementera och integrera en digital tvilling i sin befintliga verksamhet. Dessa presenteras i processmodellen som studien ämnar bidra med.

Research about the kind of information that gives roles in manufacturing companies the ability to make better decisions in their everyday work is a complex area. Much exploration is left to do for the scientists. Much information has been made available in conjunction with the IT era. But it turns out that development is not a par with the knowledge about how companies will utilize it in the best possible way. It can be seen that companies have a gap between what actually happens in terms of investments in information and communication technology and the knowledge about it. The information flow could be used as a competitive advantage if the problem of this gap could be mapped. Where companies can easily target information in the right time, location and form. The purpose of this study is to examine the information requirements at the production level in a case study company, Mastec. The report will empirically review the need through a capacity study with subsequent interviews with both case study companies and another company to achieve greater generalization. The capacity study is the proven method Productivity Potential Assessment (PPA) by Peter Almström and Anders Kinnander. The study’s strength is that it measures productivity at several different levels. To estimate a potential, the parameters are compared with Mastec’s own goals and six reference companies from previous PPA studies. After identifying a productivity potential, questions about information needs related to potential areas are addressed. The combination of a qualitative and quantitative study provides the basis for a fundamental case analysis where a critical situation is studied. Generally, the result shows a complex cluster of information needs that have similarities with both operational character and strategic character. The result of the first question ended in a matrix that was developed using theory of operational and strategic decisions. The information requirement in the matrix was categorized into information about material, 5S activities, quality, stock status, location, real-time information, instructions, external information and overall picture. In further analysis of question one and the following root cause analysis to question two, the critical situation was set to setup time. The information requirement at setup time times can be summarized into a number of points: what is the current plan; which articles are to be run; changes in the plan; measurement personnel are not available; time is spent searching for tools; time is spent looking for fixtures; time is spent searching for documents; low incentives; there are no codes for all stops; the preparation work is inadequate due to difficult planning; silent information; inadequate instructions (to see explanation for these points, see section 4.5).