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no / We report on the organization and outcome of the fourth blind test of crystal structure prediction, an international collaborative project organized to evaluate the present state in computational methods of predicting the crystal structures of small organic molecules. There were 14 research groups which took part, using a variety of methods to generate and rank the most likely crystal structures for four target systems: three single-component crystal structures and a 1:1 cocrystal. Participants were challenged to predict the crystal structures of the four systems, given only their molecular diagrams, while the recently determined but as-yet unpublished crystal structures were withheld by an independent referee. Three predictions were allowed for each system. The results demonstrate a dramatic improvement in rates of success over previous blind tests; in total, there were 13 successful predictions and, for each of the four targets, at least two groups correctly predicted the observed crystal structure. The successes include one participating group who correctly predicted all four crystal structures as their first ranked choice, albeit at a considerable computational expense. The results reflect important improvements in modelling methods and suggest that, at least for the small and fairly rigid types of molecules included in this blind test, such calculations can be constructively applied to help understand crystallization and polymorphism of organic molecules.

The topic of this thesis is the process analysis of the production company. The main goal is to describe, model and asses the recent status of processes. The additional goal is the measurements and recommendations proposal based on the evaluations. The process management is described in the introduction of the theory with subsequent explanation of methods and methodology of process modeling. The basic standards for process models creation is described in the next part of the thesis. The analyzed company will be introduced in the practical part of the paper and the method derived from the theoretical part will be applied. After modeling the recent status the necessary measures and changes will be introduced to eradicate the identified problems.

MBSE-Model-Based Systems Engineering wird als vielversprechender Ansatz gesehen, die steigende Komplexität heutiger Produktentwicklungsprozesse beherrschbar zu machen. Bei der Einführung und Umsetzung von MBSE existieren jedoch hohe Einstiegshürden, insbesondere, wenn formale Modellierungssprachen wie SysML für Modellierungsaktivitäten verwendet werden. Gleichzeitig bieten formale Modellierungssprachen jedoch Vorteile bei der Ermöglichung einer domänenübergreifenden Kommunikation und dem Informationsaustausch. Dieser Beitrag beschreibt einen Ansatz zur nutzer- und aufgabengerechten Unterstützung von Modellierungsaktivitäten mittels formaler Modellierungssprachen im Kontext des MBSE. Ziel des Ansatzes ist es, die Modellierung auf die Bedarfe und Aufgaben einzelner Anwender bzw. deren Rolle im Produktentwicklungsprozess zu fokussieren und somit einen gezielteren Zugang zur Modellierung zu ermöglichen. Hierzu werden Ansätze aus dem Bereich Architekturframeworks zur Strukturierung von Modellen mittels Bedarfs-getriebener Sichten mit einer Aktivitäts-getriebenen Formalisierung von Methoden des MBSE kombiniert. Methoden des MBSE werden in einzelne Modellierungsaktivitäten unterteilt und diese mit Sichten aus einem Architekturframework, die die Modellierungsaktivität unterstützen, verknüpft. Somit wird einerseits eine klare Strukturierung des Modells nach Sichten und andererseits eine gezielte und eindeutige Durchführung bedarfsgerechter Methoden des MBSE ermöglicht.

The efficiency of hydraulic drive systems in mobile machines is influenced by several factors, like the operators’ guidance, weather conditions, material respectively loading properties and primarily the working cycle. This leads to varying operation points, which have to be performed by the drive system. Regarding efficiency analysis, the usage of standardized working cycles gained through measurements or synthetically generated is state of the art. Thereby, only a small extract of the real usage profile is taken into account. This contribution deals with process pattern recognition (PPR) and frequency based efficiency evaluation to gain more precise information and conclusion for the drive design of mobile machines. By the example of an 18 t mobile excavator, the recognition system using Hidden – Markov - Models (HMM) and the efficiency evaluation process by means of backwards simulation of measured operation points will be described.