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Simulation for Digital Manufacturing a Simulation-Based Development Method for Smart Production Concepts of Manufacturing Cont Simulation for Digital Manufacturing A Simulation-based Development Method for Smart Production Concepts of Manufacturing Control Systems in Automotive Industries Dissertation zur Erlangung des Grades des Doktors der Ingenieurwissenschaften der Naturwissenschaftlich-Technischen Fakultät der Universität des Saarlandes von Inga Thiel Saarbrücken 2018 Simulation-based Development Method for Smart Production Concepts of Manufacturing Control Systems in Automotive Industries Tag des Kolloquiums: 02.04.2019 Dekan: Prof. Dr. rer. nat. Guido Kickelbick Berichterstatter: Prof. Dr.-Ing. Michael Vielhaber Prof. Dr.-Ing. Martin Eigner Vorsitz: Prof. Dr.-Ing. Rainer Müller Akad. Mitarbeiter Dr.-Ing. Emanuele Grasso II Simulation-based Development Method for Smart Production Concepts of Manufacturing Control Systems in Automotive Industries Abstract Digitalisation has been among the most-often discussed developments of our modern society for decades and it increasingly stretches to manufacturing. Industrial processes merge with information technologies, accelerated by rapidly increasing amount of data and newly developed smart algorithms. This thesis focuses on demands of digital manufacturing and a neutral evaluation of smart algorithms. Digitalisation is a vast field. Various solutions have been suggested lately and establish further continuously. Companies feel increasingly pressured to amend their structures to smart and agile factories. These wide-spanning refurbishments often lack concrete objectives and clear target figures for successful implementation. This limits the clarity for comparing different solutions. Deriving from a discussion on purposes of digitalisation, simulation and calculation models have been established to evaluate and rate the most valuable approaches. A test and development system is established, which is suitable to compare different smart production IT solutions. Based on this practical case, a concrete evaluation is described. An exemplary production line is evaluated to find requirements for improved flexibility. After a critical discussion about the suitability of the suggested solution, assistance systems and mathematical models are introduced with which development and optimisation of smart production structures can be implemented in a given manufacturing system. Zusammenfassung Digitalisierung gehört seit Jahrzehnten zu den am häufigsten diskutierten Entwicklungen unserer heutigen Gesellschaft und erstreckt sich zunehmend auch auf die Produktion. Industrielle Prozesse verbinden sich mit Informationstechnik, beschleunigt durch rasant steigende Datenmengen und neu entwickelte, smarte Algorithmen. Diese Arbeit fokussiert sich auf die Anforderungen digitaler Fertigung und eine neutrale Bewertung smarter Algorithmen. Digitalisierung ist ein breites Feld. Verschiedene Lösungen wurden zuletzt vorgeschlagen und entwickeln sich kontinuierlich weiter. Unternehmen stehen zunehmend unter Druck, ihre Strukturen zu smarten und agilen Fabriken zu entwickeln. Diese weitreichenden Erneuerungen lassen oft konkrete Ziele und klare Zielvorgaben für eine erfolgreiche Implementierung vermissen. Dies reduziert die Klarheit im direkten Vergleich verschiedener Lösungen. Ausgehend von einer Diskussion über den Zweck der Digitalisierung, wurden Simulations- und Berechnungsmodelle entwickelt um vielversprechende Anwendungen zu bewerten und zu klassifizieren. Ein Test- und Entwicklungssystem wurde eingerichtet, um verschiedene smarte IT-Lösungen im Produktionsumfeld vergleichen zu können. Nach einer kritischen Diskussion, in wie fern die vorgeschlagene Lösung geeignet ist, werden Assistenzsysteme und mathematische Modelle vorgestellt, die die Entwicklung und Optimierung smarter Produktionsstrukturen für ein gegebenes Fertigungssystem unterstützt. III Simulation-based Development Method for Smart Production Concepts of Manufacturing Control Systems in Automotive Industries Preamble Numerous publications on digitalisation and Industry 4.0 helped to generate the core topic for this thesis: How can a user find the most valuable strategy, component and solution within a vast choice of proposals that suits best to a particular situation and to a given system. Producing industries are among the most important sectors in German economy. A major share of the prosperity in developed countries stems from this sector. When the appearance in this field changes, it has to align to successful new strategies. Any risks to this important sector could endanger the economic system. Therefore, it is highly recommended to follow new approaches on smart factories. This thesis is a first starting point for a value discussion on objectives, benefits, but also risks of digitalisation. Targets should be based on concrete figures, ready to use for calculation and simulation. After these objectives of digitalisation were fixed, it took a lot of consideration and development on modelling as well as on digitalisation approaches. An assistance system to support development of smart manufacturing digital production was established. It is up to production planer, operation staff and manufacturing equipment supplier to decide how much of intelligent automation should be implemented in the factory. This thesis offers a suggestion for target discussion and a suitable model to implement big data analytics or artificial intelligence to keep ahead of a quickly changing, global market that demands new and individual products and quick response on volatile environment. IV Simulation-based Development Method for Smart Production Concepts of Manufacturing Control Systems in Automotive Industries Acknowledgements First and foremost, I would like to acknowledge and thank Prof. Michael Vielhaber of Saarland University for his continuous support in a vivid project. Critical review on content, format and style brought thoughts in a straight line. Honest words and serious questioning unveiled ambiguous or unclear paths in my argumentation and in project proceeding. Patient aid and solidary encouraged to proceed until a final paper is eventually finished. This let consequently to a thesis, which I could eventually appreciate. For all guidance, help and respect, I am most thankful. I would like to express my gratitude to Prof. Eigner for his support for finalising the thesis and examine the colloquium. My very special thanks are for Dr. Johann Schnagl for his help and motivation throughout the whole project, for encouraging me to start and finish my work. Highly valuable discussions provided me with plenty of innovative ideas and critical thoughts on technical development and formation of the project. Advice and support from Dr. Alexander Lindworsky helped to finalise the thesis. Fundamental assistance from Marc Regitz especially in modelling the simulation put the exemplary system on solid grounds. This work started with a focus on digitalisation and quickly spread to necessarily related areas of research, which forced me to interpret diverse topics, starting with production IT and simulation over to economics, human labour requirements and artificial intelligence. Discussions with friends and colleagues empowered me to progress in various fields of science. I would not want to miss any of these thoughts and words that helped to forge this complete view on an increasingly exciting, but also demanding topic. Many thanks also to my family and friends for their stabilising support and for thus forcing me to eventually finish my work. Refreshing assistance and strengthening will and abilities on a personal base brought me back on track many times and helped to proceed. V Simulation-based Development Method for Smart Production Concepts of Manufacturing Control Systems in Automotive Industries List of Content Abstract .................................................................................................................................III Zusammenfassung ................................................................................................................III Preamble .............................................................................................................................. IV Acknowledgements ............................................................................................................... V List of Content ...................................................................................................................... VI List of Abbreviation ............................................................................................................... IX List of Figures ....................................................................................................................... XI List of Tables ....................................................................................................................... XII List of Equations ................................................................................................................. XIII List of Symbols ................................................................................................................... XIV 1. Introduction .................................................................................................................... 1 1.1 Initial Situation ......................................................................................................... 1 1.2 Motivation ................................................................................................................ 2 1.3 Objectives ..............................................................................................................
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