Scania is a large international company from Sweden that manufactures commercial vehicles. Scania will implement a new picking technique, Pick and Put to Light (PPL) in its manufacturing industry. The new picking technology is one of the parts that will lead Scania's production towards what is called Industry 4.0. Industry 4.0 is the designation for the fourth generation industrial revolution, characterized by intelligent components that can communicate through the Internet and cloud services. Industry 4.0 is a relatively new concept that was coined in 2011 and is expected to have a major impact on the industry of the future. By introducing techniques associated to Industry 4.0, Scania will remain competitive. The purpose of the study is to investigate whether PPL can raise the quality level of quality level of the error picking rate and make recommendations for improvement. The study examines today's picking technique, Pick by Paper, and compares the results with that of PPL. Error types and how they are affected by new picking techniques are investigated in order to draw conclusions if there are deficiencies. Error types have been documented, motivated and adapted according to the nature of the business. The positive effect of paperless techniques is investigated in the form of energy savings and a comparison has been made to specify how many solar panels would be needed to generate the corresponding amount of energy. The results showed a 40% increase in errors with PPL compared to Pick by Paper. / Scania är ett stort internationellt företag från Sverige som tillverkar kommersiella fordon. Scania ska implementera en ny plockteknik som ska leda Scania mot det som kallas Industri 4.0. Industri 4.0 är beteckningen för den fjärde generationens industriella revolution, som karaktäriseras av intelligenta komponenter som kan kommunicera genom internet och molntjänster. Industri 4.0 är ett förhållandevis nytt begrepp som myntades 2011 och beräknas ha en stor påverkan på framtidens industri. Genom att utvecklas mot Industri 4.0 förblir Scania konkurrenskraftiga. Steget mot Industri 4.0 kommer att ske genom en ny plockteknik som kallas Pick and Put to Light (PPL) som då blir den första delen av verksamheten att sammankopplas med Industri 4.0. Syftet med studien är att undersöka huruvida PPL kan höja kvalitetsnivån hos plockarna och ge rekommendationer. Studien undersöker dagens plockteknik, Pick by Paper, och jämför resultatet med det från PPL. Avvikelsetyper och hur de påverkas av ny plockteknik undersöks i syfte att dra slutsatser om det finns brister. Avvikelsetyper har dokumenterats, motiverats och anpassats utefter verksamhetens art. Den positiva följdeffekten av papperslösa tekniker undersöks i form av energibesparing och en jämförelse har gjorts för att konkretisera hur många solpaneler som skulle behövas för att generera motsvarande mängd energi. Resultatet visade att avvikelserna skulle öka med 40% vid implementering av PPL jämfört med Pick by Paper.

This diploma thesis "MES / MOM Systems in the Industry 4.0 concept" deals with the analysis, design and implementation of these systems. The first focus is on Industry 4.0 analysis, where are describe each part of Industry 4.0. Based on this knowledge, there were specified the changes in the MES / MOM systems. According to the changes and knowledge were designed and implemented the MES / MOM concept. The system communicates with the PLC using its own communicator and represents the data in the application environment. The application implements the Historian module and system modules. The PLC has an MS SQL protocol implemented so that the device can read and write data without the need to communicate with the parent system. This implementation is in line with Industry 4.0’s concept.

Der Einrichtprozess der Wasserstrahlschneidanlage erfolgt überwiegend als manueller Prozess. Die fehlende Automatisierung führt zu einem hohen Zeitverlust und der dauerhaften Anwesenheit einer Fachkraft. Dieser Umstand wird durch eine Steigerung des Automatisierungsgrades angegangen. Die Steigerung wird durch die Integration einer Umfeldsensorik und die Erstellung eines Algorithmus re-alisiert. Dieser erkennt die Halbzeuge im Arbeitsraum, um diese anschließend in ein CAD-Modell zu transformieren.

Wissen über Digitalisierung, Automatisierung und über „smarte“ Technologien sind Schlüssel für einen stabilen und nachhaltigen Erfolg von Klein- und Mittelunternehmen in der Region Salzburg. Die Fachhochschule Salzburg beantragte aus diesem Grund die Initiative Salzburg Smart Factory Bootcamp. Moderne und mobile Industrierobotik, kommunikative Software-Architekturen und OT-Sicherheit bilden die Basis für die Umsetzung aktueller Smart-Factory-Technologien und deren Potentiale in Unternehmen. Ziel des Bootcamps ist die gezielte Weiterqualifizierung mit modernsten Smart-Factory-Technologien von Mitarbeiterinnen und Mitarbeitern der beteiligten Unternehmen. Zusätzlich kann langfristig, auch über die beantragte Projektlaufzeit hinaus, die Zusammenarbeit zwischen Hochschule und Salzburger Unternehmen etabliert und weitergeführt werden.

Innovative possibilities for data collection, networking, and evaluation are unleashing previously untapped potential for industrial production. However, harnessing this potential also requires a change in the way we work. In addition to expanded automation, human-machine cooperation is becoming more important: The machine achieves a reduction in complexity for humans through artificial intelligence. In fractions of a second large amounts of data of high decision quality are analyzed and suggestions are offered. The human being, for this part, usually makes the ultimate decision. He validates the machine’s suggestions and, if necessary, (physically) executes them. Both entities are highly dependent on each other to accomplish the task in the best possible way. Therefore, it seems particularly important to understand to what extent such cooperation can be effective. Current developments in the field of artificial intelligence show that research in this area is particularly focused on neural network approaches. These are considered to be highly powerful but have the disadvantage of lacking transparency. Their inherent computational processes and the respective result reasoning remain opaque to humans. Some researchers assume that human users might therefore reject the system’s suggestions. The research domain of explainable artificial intelligence (XAI) addresses this problem and tries to develop methods to realize systems that are highly efficient and explainable. This work is intended to provide further insights relevant to the defined goal of XAI. For this purpose, artifacts are developed that represent research achievements regarding the systematization, perception, and adoption of artificially intelligent decision support systems from a user perspective. The focus is on socio-technical insights with the aim to better understand which factors are important for effective human-machine cooperation. The elaborations predominantly represent extended grounded research. Thus, the artifacts imply an extension of knowledge in order to develop and/ or test effective XAI methods and techniques based on this knowledge. Industry 4.0, with a focus on maintenance, is used as the context for this development. / Durch innovative Möglichkeiten der Datenerhebung, Vernetzung und Auswertung werden Potenziale für die Produktion freigesetzt, die bisher ungenutzt sind. Dies bedingt jedoch eine Veränderung der Arbeitsweise. Neben einer erweiterten Automatisierung wird die Mensch-Maschinen-Kooperation wichtiger: Die Maschine erreicht durch Künstliche Intelligenz eine Komplexitätsreduktion für den Menschen. In Sekundenbruchteilen werden Vorschläge aus großen Datenmengen von hoher Entscheidungsqualität geboten, während der Mensch i.d.R. die Entscheidung trifft und diese ggf. (physisch) ausführt. Beide Instanzen sind stark voneinander abhängig, um eine bestmögliche Aufgabenbewältigung zu erreichen. Es scheint daher insbesondere wichtig zu verstehen, inwiefern eine solche Kooperation effektiv werden kann. Aktuelle Entwicklungen auf dem Gebiet der Künstlichen Intelligenz zeigen, dass die Forschung hierzu insbesondere auf Ansätze Neuronaler Netze fokussiert ist. Diese gelten als hoch leistungsfähig, haben aber den Nachteil einer fehlenden Nachvollziehbarkeit. Ihre inhärenten Berechnungsvorgänge und die jeweilige Ergebnisfindung bleiben für den Menschen undurchsichtig. Einige Forscher gehen davon aus, dass menschliche Nutzer daher die Systemvorschläge ablehnen könnten. Die Forschungsdomäne erklärbare Künstlichen Intelligenz (XAI) nimmt sich der Problemstellung an und versucht Methoden zu entwickeln, um Systeme zu realisieren die hoch-leistungsfähig und erklärbar sind. Diese Arbeit soll weitere Erkenntnisse für das definierte Ziel der XAI liefern. Dafür werden Artefakte entwickelt, welche Forschungsleistungen hinsichtlich der Systematisierung, Wahrnehmung und Adoption künstlich intelligenter Entscheidungsunterstützungssysteme aus Anwendersicht darstellen. Der Fokus liegt auf sozio-technischen Erkenntnissen. Es soll besser verstanden werden, welche Faktoren für eine effektive Mensch-Maschinen-Kooperation wichtig sind. Die Erarbeitungen repräsentieren überwiegend erweiterte Grundlagenforschung. Damit implizieren die Artefakte eine Erweiterung des Wissens, um darauf aufbauend effektive XAI-Methoden und -Techniken zu entwickeln und/ oder zu erproben. Als Kontext der eigenen Erarbeitung wird die Industrie 4.0 mit Schwerpunkt Instandhaltung genutzt.

Die zunehmende Forderung an automatisierte Produktionsanlagen sich flexibel auf neue Situationen in der Produktion anpassen zu können, fordert innovative Konzepte. Dieser Beitrag stellt ein Retrofit- Konzept vor, welches bereits bei der Erstellung der Anlagen mit integriert werden kann, um somit zukünftig flexibel Teilbereiche austauschen zu können. Hierbei muss in den praxiserprobten Steuerungsablauf nicht direkt eingegriffen werden. Das vorliegende Konzept basiert auf einer Anforderungsanalyse und ist prototypisch umgesetzt.

Der technische Fortschritt hat dazu geführt, dass die Kosten für das automatisierte Drucken von Emblemen, Anhängern sowie allgemein gedruckten Prototypen stark gefallen sind. Dies geschah insbesondere auch vor dem Hintergrund einesWandels der Industrie hin zu einer modernen Industrie 4.0. In dieser Arbeit wird ein neuer Ansatz für das automatische 3D-Drucken eines Logos präsentiert, welches als Pixelgrafik vorliegt. Die vorgeschlagene Prozesskette erzeugt hierbei final den G-code zum Drucken. Dabei sind seitens des Users wenige Eingaben erforderlich.

Title:  Purchasing 4.0: An Exploratory Multiple Case Study on the Purchasing Process Reshaped by Industry 4.0 in the Automotive Industry Authors: Simon Gottge, Torben Menzel Background: Rapidly transforming technologies and changing customer expectations trigger the fourth industrial revolution. This development, often referred to as ‘Industry 4.0’, is characterized by autonomously communicating and interacting technologies throughout the supply chain. Simultaneously, the importance of efficient purchasing processes in the automotive sector keeps growing as outsourcing and globalization tendencies increase. While Industry 4.0 publications are on the rise, little research is carried out on the impact on related supply chain functions, especially purchasing, calling for scientific investigations. Purpose: The purpose of this thesis is to explore the influence of Industry 4.0 on purchasing at automotive manufacturers and further derive a visionary model of the reshaped purchasing process within the adjusted Purchasing 4.0 context. Method: The deductive research is carried out as exploratory multiple case study. In three cases, qualitative data from four dyads is analyzed. Interviews hereby were conducted with 23 participants representing different perspectives, also including case-independent experts. Findings & conclusion: Considering the influence of Industry 4.0 on purchasing, the research reveals, that new technologies and changes in manufacturing, integration and business context will impact the purchasing scope, collaboration, structure, and infrastructure. These changes include new components and different suppliers, a cross-functional and deeper supplier integration as well as collaboration platforms, holistic networks and assisting IT-systems. In the reshaped purchasing process, strategic sub processes will become highly integrated and technology supported, leading to a co-creation of specification, explorative supplier selection, parameter-based quotations and negotiations, and autonomous re-negotiations of changes. The operative purchasing process on the other hand is strongly shaped by real-time data usage, creating interactive call-offs, real-time tracking, proactive trouble shooting and holistic supplier evaluations. Keywords: Purchasing; Industry 4.0; Purchasing 4.0; Purchasing Process; Automotive

Zunächst wird ein Überblick über berufliche Herausforderungen für Menschen in der modernen Produktentwicklung (-> Industrie 4.0) gegeben. Anschließend wird ein allgemeines Rahmenmodell beschrieben, in dem (nicht nur) psychologische Faktoren dargestellt werden, die menschliches Fühlen, Denken und Handeln beeinflussen. Im dritten Abschnitt wird ein Blick über den Tellerrand geworfen: In der Luftfahrt sind sogenannte Crew Resource Management Seminare für Besatzungen von Verkehrsflugzeugen gesetzlich verpflichtender Teil der Personalentwicklung und Weiterbildung. Es wird der Frage nachgegangen, in wieweit Zielsetzung und Inhalte dieser Seminare auf das Setting und die Bedürfnisse eines in der modernen Produktentwicklung tätigen Menschen übertragen werden können. Diese Überlegungen münden in den Ansatz des sogenannten Personal Resource Management, der den in der Produktentwicklung tätigen Menschen dabei unterstützen kann, sich der ihm zur Verfügung stehenden Ressourcen bewusst zu werden und Wege zu finden, diese Ressourcen in einem komplexen Umfeld zielorientiert abzurufen und ntsprechende Leistungen zu erbringen und gesund zu bleiben.

Com o advento da Internet às indústrias, um novo cenário industrial conhecido como Indústria 4.0 ou Internet Industrial entra na agenda de pesquisa com potencial de ser entendido como uma nova revolução industrial. Impactos são tidos como certos no projeto, manufatura e na função do produto. Produtos inteligentes, dotados de identificação individualizada e cuja introdução envolve a geração, armazenamento, recuperação e uso de dados sobre os mesmos, estarão completamente integrados aos recursos de produção, levando ao estabelecimento dos cyber-physical production systems - CPPS, ou sistemas de produção físico-cibernéticos. A transição para o cenário industrial descrito demanda por qualificação dos profissionais envolvidos, por meio de estratégias adequadas de promoção do aprendizado. A demanda por estratégias adequadas de promoção do aprendizado remete a outro tema atual na agenda de pesquisa, que é relacionado ao momento de transição da educação profissional de engenheiros na direção da introdução de inovações focadas em maior exposição dos alunos a atividades práticas, o mais próximo possível da realidade das indústrias. Dentre as inovações as Fábricas de Aprendizagem, conceito que de forma sucinta é definido a partir das duas palavras do termo, fábrica e aprendizagem, e que trata de instalações dotadas de elementos de ambos, destacam-se ao endereçar problemas de falta de habilidades práticas entre engenheiros recém formados, com eficácia comprovada e documentação de casos bem-sucedidos de implantação na América do Norte e Europa. Lacunas foram por esta dissertação de mestrado consideradas além das já abordadas demanda por qualificação de profissionais envolvidos com a Indústria 4.0, e do cenário de introdução de inovações na formação de engenheiros. Foram também consideradas a demanda por análise conjunta da literatura relacionada a abordagem sistêmica para desenvolvimento de Fábricas de Aprendizagem, e de classificação das mesmas, assim como chamada por documentação de casos práticos de implantação. Esta dissertação de mestrado se insere, então, nas duas agendas de pesquisa mencionadas, ao realizar um estudo de caso de implantação de uma Fábrica de Aprendizagem, uma das inovações na formação de engenheiros, dedicada ao novo cenário industrial da Indústria 4.0. Três questões de pesquisa foram consideradas e estabeleceram um roteiro de classificação, descrição do processo de implantação e proposição de recomendações, roteiro este tomado como base para o estudo. Partindo de uma revisão de literatura focada na exposição de características industriais se tornando realidade nas indústrias e no histórico de inovações na formação de engenheiros que deu origem ao conceito de Fábricas de Aprendizagem, foram estabelecidos os padrões de referência para a condução da pesquisa. O estudo de caso fez uso de três fontes de dados (entrevistas, análise de documentos e observação de eventos) e traz como resultados a exposição da classificação alcançada e a descrição do processo de implantação, em comparação aos padrões resultantes da revisão de literatura, complementados por recomendações direcionadas à aderência aos mesmos. Como resultados adicionais podem também serem citados a proposta de análise conjunta dos requisitos envolvidos com a abordagem sistêmica de implantação identificada na literatura, assim como o questionário de pesquisa derivado do mesmo. A expectativa é de que os resultados contribuam com gestores, docentes e pesquisadores de instituições de ensino perseguindo inovações na formação de engenheiros e que estejam voltados para o desenvolvimento e implantação de instalações de Fábricas de Aprendizagem derivadas e/ou adaptadas a partir do modelo original. / From the advent of Internet in the shop floor, a new industrial scenario known as Industry 4.0 or Industrial Internet enters in the research agenda with potential to be taken as a new industrial revolution. Impacts are taken for granted in the project, manufacturing and function of the products. Intelligent products, gifted with individual identification and whose introduction involves the generation, storage, retrieval and use of data about themselves, will be completely integrated to the manufacturing resources, leading to the establishment of the Cyber Physical Production Systems- CPPS. The transition for the described industrial scenario demands qualification of the involved professionals, by means of suitable strategies of learning promotion. The demand for suitable strategies to promote learning refers to another current topic in the research agenda, which is related to the moment of transition of professional education of engineers towards the introduction of innovations focused on greater exposure of students to practical activities, the closest the reality of industries. Among the innovations, the Learning Factories, a concept that is succinctly defined from the two words of the term, factory and learning, and which deals with facilities with elements of both, stand out in addressing problems of lack of practical skills between newly trained engineers, with proven efficacy and documentation of successful deployment cases in North America and Europe. Gaps were by this master\'s dissertation considered beyond to the already discussed demand for qualification of professionals involved with Industry 4.0, and of the scenario of introduction of innovations in the training of engineers. It also considered the demand for joint analysis of the literature related to the systematic approach to development of Learning Factories, and their classification, as well as the call for documentation of practical cases of implantation. This dissertation is then part of the two research agendas mentioned above, when conducting a case study of the implantation of a Learning Factory, one of the innovations in the training of engineers, dedicated to the new industrial scenario of Industry 4.0. Three research questions were considered and they established a script of classification, description of the implantation process and proposal of recommendations, script that was taken as basis for the study. Starting from a literature review focused on the exposition of the industrial characteristics that are becoming a reality in the industries and the history of innovations in the training of engineers that gave rise to the concept of Learning Factories, the reference standards for conducting the research were established. The case study made use of three data sources (interviews, documents analysis and events observation) and brings as results the exposure of the classification achieved and the description of the implantation process, in comparison to the standards resulting from the literature review, complemented by recommendations leading towards to adherence to them. As additional results, the proposal of joint analysis of the requirements involved with the systemic approach of implantation identified in the literature, as well as the research questionnaire derived from it, can also be cited. The expectation is that the results contribute to managers, teachers and researchers from educational institutions pursuing innovations in the training of engineers and that are also focused on the development and implantation of facilities of Learning Factories derived and / or adapted from the original model.