Modellierungskonzept zur integrierten Planung und Simulation von Produktionsszenarien entwickelt am Beispiel der CFK-Serienfertigung

The industrialization of CFRP production demands for new planning and engineering tools in order to develop more efficient production processes and higher automated production systems. This thesis presents a new concept for digital production engineering in the context of digital factory, which is focused on the integrated planning and simulation of complex production scenarios. As approach of model-driven engineering, a domain-specifc modeling language and a factory data model are developed in order to generate models of material flow simulation. Thereby, major challenges of digital CFRP production engineering are different technology readiness levels, complex routings of tools and materials as well as the consideration of rework and autoclave processes. These challenges motivated the development of an eight level modeling concept called GRAMOSA, which integrates the management of alternative production scenarios and focusses on an integrated production and logistics planning

Risk-Optimized Design of Production Systems by Use of GRAMOSA

Today production and logistic systems are getting more complex. This is a problem which the planning and design of such systems have to deal with. One main issue of production system development in series production is the planning of production processes and systems under uncertainty. New and existing production technologies are often not fully adoptable to new products. This is why some of the main characteristics, like, for example, cost, time, or quality, are not definable at the beginning. Only value ranges and probabilities can be estimated. However, the adaptation process is controllable, which means that the adaptation results are depending on the existing development budget and its resources. This paper presents an approach for the optimized allocation of development resources regarding the adaptation risks of production technologies and processes. The modeling concept GRAMOSA is used for integrated modeling and discrete event-based simulation of the aspired production system. To this end a domain-specific modeling language (DSML) is applied. The further risk-based analysis of the simulation results and the optimized allocation of the development budget are done by use of mathematical optimization

Application of Stochastic Regression for the Configuration of Microrotary Swaging Processes

In micromanufacturing, a precise adjustment of manufacturing, handling, and quality control processes constitutes an essential factor for success. The continuing miniaturization of workpieces and production devices results in ever decreasing tolerances, whereas machines and processes become increasingly more specialized. Thereby, the so-called size effects render the direct application of knowledge from the area of macromanufacturing impossible. In this context, this paper describes the application of the μ-ProPlAn method for the configuration of an infeed rotary swaging process for microcomponents. At this, the cause-effect relationships between relevant process parameters are analyzed using stochastic regression models, in order to determine cost-efficient process configurations for the manufacturing of bulk and tubular microcomponents

Robust production planning in fashion apparel industry under demand uncertainty via conditional value at risk

Published version of an article in the journal: Mathematical Problems in Engineering. Also available from the publisher at: http://dx.doi.org/10.1155/2014/901861This paper presents a mathematical model for robust production planning. The model helps fashion apparel suppliers in making decisions concerning allocation of production orders to different production plants characterized by different lead times and production costs, and in proper time scheduling and sequencing of these production orders. The model aims at optimizing these decisions concerning objectives of minimal production costs and minimal tardiness. It considers several factors such as the stochastic nature of customer demand, differences in production and transport costs and transport times between production plants in different regions. Finally, the model is applied to a case study. The results of numerical computations are presented. The implications of the model results on different fashion related product types and delivery strategies, as well as the model's limitations and potentials for expansion, are discussed. Results indicate that the production planning model using conditional value at risk (CVaR) as the risk measure performs robustly and provides flexibility in decision analysis between different scenarios. © 2014 Abderrahim Ait-Alla et al

Auf dem Bibliothekartag im Braunhemd, in der Bibliotheksleitung unauffällig? Kirchner und die UB München im Nationalsozialismus

Die historische Erforschung wissenschaftlicher Bibliothekare während der Zeit des Nationalsozialismus setzte vergleichsweise spät ein und ist bisher noch nicht abschließend erfolgt. Im vorliegenden Beitrag wird das bibliothekarische Handeln Dr. Joachim Kirchners (1890–1978) untersucht, der sich 1933 als Redner auf dem Bibliothekartag in Darmstadt vehement für »Bücherverbrennungen marxistischer, kommunistischer und jüdischer Autoren« aussprach, jedoch später als Direktor der Universitätsbibliothek München (1941–1945) in Einzelfällen für Verfolgte des NS-Regimes eintrat sowie durch umfangreiche Auslagerungen große Teile des Bibliotheksbestandes vor der drohenden Vernichtung im Bombenkrieg bewahrte. Am Beispiel Kirchners wird der Handlungsspielraum ausgelotet, der sich zwischen 1933 und 1945 im bibliothekarischen Berufsalltag ergab.Research on scientific librarians during the time of National Socialism has been started late and did not come yet to an end. This article deals with the behaviour of Joachim Kirchner (1890–1978), an important librarian of his time. On the one hand he gave an enthusiastic speech at the Library Conference in Darmstadt in 1933 supporting the burning of books written by Marxists, Communists and Jews. On the other hand as director of the Library of the University of Munich (1941–1945) he supported persons prosecuted by the Nazi regime working in the library. In addition he preserved many books from the bombardment by removing them from the city of Munich to the countryside. Joachim Kirchner is an outstanding example how inconsistent a librarian could act in different situations during the Third Reich

Modeling Concept for the Integrated Planning and Simulation of Production Scenarios - Developed by using the example of CFRP Series Production

The industrialization of CFRP production demands for new planning and engineering tools in order to develop more efficient production processes and higher automated production systems. This thesis presents a new concept for digital production engineering in the context of digital factory, which is focused on the integrated planning and simulation of complex production scenarios. As approach of model-driven engineering, a domain-specifc modeling language and a factory data model are developed in order to generate models of material flow simulation. Thereby, major challenges of digital CFRP production engineering are different technology readiness levels, complex routings of tools and materials as well as the consideration of rework and autoclave processes. These challenges motivated the development of an eight level modeling concept called GRAMOSA, which integrates the management of alternative production scenarios and focusses on an integrated production and logistics planning

Text Mining for Supply Chain Risk Management in the Apparel Industry

Text mining tools are now widely used for the efficient management of information and resources in business, academic and research organizations. This paper provides a comprehensive overview of research articles on the application of text mining techniques in the field of Supply Chain Risk Management and the apparel industry. Research articles published between 2000 and 2020, were obtained from various journals through two online databases, i.e., SCOPUS and IEEE Xplore. Through a systematic approach following PRISMA guidelines, 370 research papers were screened, filtered and finally classified into three main areas: Supply Chain Risk Management and outsourcing in the apparel industry, application of text mining in Supply Chain Risk Management and application of text mining in the apparel industry. In this study, we have identified a comprehensive list of various available data sources for text mining, methodologies and risks associated with outsourcing in the apparel industry. We classify the gaps in expanding the application of text mining in the apparel industry’s Supply Chain Risk Management. Extracting useful information from online newspapers through text mining could vividly enhance the ability to monitor supply chain risks and provide the ability to link data to provide decision makers with the right information at the right time

Energy-efficient eKanban system with autonomous sensor modules for level measurement and reinforcement learning for measurement interval adaptation

Trotz der Fortschritte der Digitalisierung in der Industrie finden bei der Bestandserfassung immer noch manuelle Trigger Einsatz, da bestehende Lösungen zur Automatisierung des Prozesses mit hohen Kosten und Integrationsaufwand verbunden sind. In diesem Beitrag wird ein Ansatz für die Lösung dieses Problems dargestellt, welcher kostengünstige, autonome Sensormodule für die Füllstandsmessung zur Grundlage hat. Die Messung erfolgt hierbei nicht in festgelegten Intervallen, sondern wird auf Basis der Entnahmeintervalle der zu messenden Ladungsträger sowie der aktuellen Auftragslage von einem Reinforcement Learning Ansatz dynamisch und intelligent getriggert. Die ersten Hardware-Prototypen für die Messung der Entnahmeintervalle sowie für die Sensormodule werden ebenfalls im Beitrag vorgestellt.Despite the progress of digitalization in industry, manual triggers are still used for inventory measurement, as existing solutions for automating the process are associated with high costs and integration efforts. This paper presents an approach for solving this problem, which is based on cost-effective, autonomous sensor modules for fill level measurement. The measurement is not performed at fixed intervals, but is triggered dynamically and intelligently by a reinforcement learning approach based on the intervals in which contents are taken from the relevant load carriers and the current order situation. The first hardware prototypes for measuring the access to load carriers for content removal and for the sensor modules are also presented in the article

Integrated domain model for operative offshore installation planning

Purpose: This article aims to identify common structural elements in the descriptions of both approaches, enabling the application of model transformations. Methodology: Several models of both types will be compared, combining relevant concepts, i.e., entities, attributes and relationships into a generalized model. In a second step, elements crucial to either type of model are identified. For the remaining elements, interdependencies and redundancies will be identified to enable a model reduction. Findings: While the structure and notation of both approaches are different, both describe the same fundamental concepts and relationships. The article provides a data model of these common concepts for the operational planning of offshore activities, including weather restrictions and forecasts. Originality: In current literature, there exist no approaches to combine mathematical optimization with event-discrete simulations in the context of offshore wind farm installations. To harness the advantages of both approaches in an integrated methodology, a model of common concepts is required, which does not exist at this time