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The smart factory is at the heart of Industry 4.0 and is the new paradigm for establishing advanced manufacturing systems and realizing modern manufacturing objectives such as mass customization, automation, efficiency, and self-organization all at once. Such manufacturing systems, however, are characterized by dynamic and complex environments where a large number of decisions should be made for smart components such as production machines and the material handling system in a real-time and optimal manner. AI offers key intelligent control approaches in order to realize efficiency, agility, and automation all at once. One of the most challenging problems faced in this regard is uncertainty, meaning that due to the dynamic nature of the smart manufacturing environments, sudden seen or unseen events occur that should be handled in real-time. Due to the complexity and high-dimensionality of smart factories, it is not possible to predict all the possible events or prepare appropriate scenarios to respond. Reinforcement learning is an AI technique that provides the intelligent control processes needed to deal with such uncertainties. Due to the distributed nature of smart factories and the presence of multiple decision-making components, multi-agent reinforcement learning (MARL) should be incorporated instead of single-agent reinforcement learning (SARL), which, due to the complexities involved in the development process, has attracted less attention. In this research, we will review the literature on the applications of MARL to tasks within a smart factory and then demonstrate a mapping connecting smart factory attributes to the equivalent MARL features, based on which we suggest MARL to be one of the most effective approaches for implementing the control mechanism for smart factories.

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This paper proposes a novel algorithm in pixel-based pattern recognition in design layout which offers simplicity, speed and accuracy to recognize any patterns that later can be used to detect problematic pattern in lithography process so they can be removed or improved earlier in design stage.:Abstract 1 Content 3 List of Figure 6 List of Tables 8 List of Abbreviations 9 Chapter 1: Introduction 10 1.1 Motivation 10 1.2 Related Work 11 1.3 Purpose and Research Question 12 1.4 Approach and Methodology 12 1.5 Scope and Limitation 12 1.6 Target group 13 1.7 Outline 13 Chapter 2: Theoretical Background 14 2.1 Problematic Pattern in Computational Lithography 14 2.2 Optical Proximity Effect 16 2.3 Taxonomy of Pattern Recognition 17 2.3.1 Feature Generation 18 2.3.2 Classifier Model 19 2.3.3 System evaluation 20 2.4 Feature Selection Technique 20 2.4.1 Wrapper-Based Methods 21 2.4.2 Average-Based Methods 22 2.4.3 Binary Geometrical Transformation 24 2.4.3.1 Image Interpolation 24 2.4.3.2 Geometric Transformation 26 2.4.3.2.1 Forward Mapping: 26 2.4.3.2.2 Inverse Mapping: 27 2.4.3.3 Thresholding 27 2.5 Machine Learning Algorithm 28 2.5.1 Linear Classifier 29 2.5.2 Linear Discriminant Analysis (LDA) 30 2.5.3 Maximum likelihood 30 2.6 Scoring (Metrics to Measure Classifier Model Quality) 31 2.6.1 Accuracy 32 2.6.2 Sensitivity 32 2.6.3 Specifity 32 2.6.4 Precision 32 Chapter 3: Method 33 3.1 Problem Formulation 33 3.1.1 T2T Pattern 35 3.1.2 Iso-Dense Pattern 36 3.1.3 Hypothetical Hotspot Pattern 37 3.2 Classification System 38 3.2.1 Wrapper and Average-based 38 3.2.2 Binary Geometric Transformation Based 39 3.3 Window-Based Raster Scan 40 3.3.1 Scanning algorithm 40 3.4 Classifier Design 42 3.4.1 Training Phase 43 3.4.2 Discriminant Coefficient Function 44 3.4.3 SigmaDi 45 3.4.4 Maximum Posterior Probability 45 3.4.5 Classifier Model Block 46 3.5 Weka 3.8 47 3.6 Average-based Influence 49 3.7 BGT Based Model 50 Chapter 4: Results 55 4.1 Wrapper and Average-based LDA classifier 55 4.2 BGT Based LDA with SigmaDi Classifier 56 4.3 Estimation Output 57 4.4 Probability Function 58 Chapter 5: Conclusion 59 5.1 Conclusions 59 5.2 Future Research 60 Bibliography 61 Selbstständigkeitserklärung 63

Despite great progress of lab-on-a-chip (LoC) technology platforms in the last 30 years, there is a lack of standardized microfluidic components, real on-chip utomation and progressive functional scalability of the fluidic circuits. Hydrogel-based microfluidic circuits have a high scaling potential and provide on-chip automation, but are complex in system design. An advanced circuit concept for planar microfluidic chip architectures, originating from the early era of the semiconductor-based resistor-transistor-logic (RTL) is presented and the hydrogel-based chemical volume phase transition transistor (CVPT) for logic gate operations is implemented. The circuit concept (CVPT-RTL) is robust and simple in design, feasible with common materials and manufacturing techniques of the LoC technology. Thereby, three major challenges are solved: contamination issues, maintaining the signal compliance for cascadability, and chemical signal inversion. As a central element, a CVPT cascode is introduced. The functionality of the concept is verified by a 24 h test of the NAND gate operation and a self-automated chemofluidic analog-to-digital converter, utilized as interface between bioreactors and extended microfluidic logic circuits. Moreover, the CVPT-RTL cascode demonstrates the expected selfstabilizing performance of the NAND gate. Accompanying simulations of the component behavior based on a network description implemented in Matlab Simscape match with the experimental results.

Piston rings cause significant friction losses within internal combustion engines. Especially the first compression ring, which is pressed onto the liner by high cylinder pressure, contributes significantly to the total friction loss of the piston assembly. The tribological behavior of the oil scraper ring is mainly related to the pretensioning force and can lead to high losses even at low and idle speed. Due to this, there is always a markable risk of wear for the contact surfaces of the piston rings and the cylinder. “Diamond-like carbon” coatings on the surface of the piston rings can prevent wear and are able to reduce friction in the ring-liner-contact. The purpose of this work was to investigate the tribological benefit of this coating-system on the compression and oil scraper ring. Experimental studies were carried out on a fired single-cylinder engine using the Indicated Instantaneous Mean Effective Pressure-method (IIMEP) for the crank angle-resolved detection of the piston assembly’s friction force. To be able to determine the component-related fractions of the friction loss and to quantify the hydrodynamic and asperity related parts locally and time dependent, an EHD/MBS model of the engine was created in AVL EXCITE and a simulative investigation was performed. This simulation was validated by the experimental work and provided detailed information about the individual contact conditions and gap height of each tribological contact of the piston group. The combined approach of measurement and simulation enabled the prediction of tribological aspects and performance in parameter studies on a virtual engine test bed.

In an interdisciplinary project, creative concepts for care robotics were developed. To explore the design space that these open up, we discussed them along the common differentiation of physical (effective) and social-emotional assistance. Trying to rate concepts on these dimensions frequently raised questions regarding the relation between the social-emotional and the physical, and highlighted gaps and a lack of conceptual clarity. We here present our design concepts, report on our discussion, and summarize our insights; in particular we suggest that the social and the physical dimension of care technologies should always be thought of and designed as interrelated.

A new preparation concept of a partially porous solid-state bilayer electrolyte (BE) for high-temperature sodium-ion batteries has been developed. The porous layer provides mechanical strength and is infiltrated with liquid and highly conductive NaAlCl4 salt, while the dense layer prevents short circuits. Both layers consist, at least partially, of Na-β-alumina. The BEs are synthesized by a three-step procedure, including a sol-gel synthesis, the preparation of porous, calcined bulk material, and spin coating to deposit a dense layer. A detailed study is carried out to investigate the effect of polyethylene oxide (PEO) concentration on pore size and crystallization of the bulk material. The microstructure and crystallographic composition are verified for all steps via mercury intrusion, X-ray diffraction, and scanning electron microscopy. The porous bulk material exhibits an unprecedented open porosity for a NaxAlOy bilayer-system of ≤57% with a pore size of ≈200–300 nm and pore volume of ≤0.3 cm3∙g−1. It contains high shares of crystalline α-Al2O3 and Na-β-alumina. The BEs are characterized by impedance spectroscopy, which proved an increase of ionic conductivity with increasing porosity and increasing Na-β-alumina phase content in the bulk material. Ion conductivity of up to 0.10 S∙cm−1 at 300 °C is achieved.

The effect of dental technical tools on the phase composition and roughness of 3/4/5 yttria-stabilized tetragonal zirconia polycrystalline (3y-/4y-/5y-TZP) for application in prosthetic dentistry was investigated. Additionally, the X-ray diffraction methods of Garvie-Nicholson and Rietveld were compared in a dental restoration context. Seven plates from two manufacturers, each fabricated from commercially available zirconia (3/4/5 mol%) for application as dental restorative material, were stressed by different dental technical tools used for grinding and polishing, as well as by chewing simulation and thermocycling. All specimens were examined via laser microscopy (surface roughness) and X-ray diffraction (DIN EN ISO 13356 and the Rietveld method). As a result, the monoclinic phase fraction was halved by grinding for the 3y-TZP and transformed entirely into one of the tetragonal phases by polishing/chewing for all specimens. The tetragonal phase t is preferred for an yttria content of 3 mol% and phase t″ for 5 mol%. Mechanical stress, such as polishing or grinding, does not trigger low-temperature degradation (LTD), but it fosters a phase transformation from monoclinic to tetragonal under certain conditions. This may increase the translucency and deteriorate the mechanical properties to some extent.