In this chapter, an overview is given of the research work during the years 2007 until 2016 in the field of tolerance analysis, optimization and synthesis of mechanisms ([11] and [17]). At the beginning, the challenges related to mechanisms are highlighted, especially the time-dependent behaviour of a mechanism during its operation and the different kinds of deviation occuring during the production and the operation of the mechanism. After that, the integrated approach for the statistical tolerance analysis of mechanisms is described. This approach is then enlarged to a complete tolerance analysis, optimization and synthesis approach before its applicability is demonstrated in a case study. The chapter will end with a summary.

Diese Studie beschreibt die Entwicklung eines betriebsunabhängigen Simulationsmodells für elektrifizierte Druckgießereien, die ihren Energiebedarf mit Hilfe eines Smart Grid Systems decken. Das Modell verwendet reale Wetter- und Börsenstrompreisdaten für den Simulationszeitraum. Mit Hilfe des Modells können die Stromkosten für eine Produktion zu einem bestimmten Zeitpunkt (Tages- und Jahreszeit) sowie die Wirtschaftlichkeit verschiedener PV-Anlagen- und Stromspeichervarianten ermittelt und verglichen werden. Zudem ermöglicht es die Untersuchung des Anteils der verschiedenen Energieträger für die jeweilige Konfiguration. Dies kann mit Hilfe des Modells für Standorte in ganz Deutschland durchgeführt werden. Darüber hinaus werden in dieser Arbeit beispielhafte Simulationsstudien vorgestellt, die den breiten Anwendungsbereich des Modells aufzeigen. Aus den Ergebnissen kann ein erster Überblick über Einsparungs- und Optimierungsmöglichkeiten gewonnen werden. Perspektivisch stellt das Modell eine Grundlage dar, um mittels simulationsgestützter Optimierung optimale Anlagenlayouts und Produktionszeitpunkte zu ermitteln.

Purpose - This study aims to address challenges in the Laser Powder Bed Fusion process of polymers, focusing on the considerable amount of unsintered powder left post-printing. The objective is to understand the altered properties of this powder and find solutions to improve the process, reduce waste, and explore reusing reprocessed powder.

Design/methodology/approach - A novel methodology is employed to generate reprocessed powder without traditional printing, reducing time, cost, and waste. The approach mimics the aging effects during the printing process, providing insights into particle size distribution and thermal behavior.

Findings - Results reveal insights into artificial aging, showing an 8.2% decrease in particle size (60.256 - 69.183 μm) and a 9.1% increase in particle size (17.378 - 19.953 μm) compared to unsintered powder. Thermal behavior closely mirrors used powders, with variations in enthalpy of fusion (-0.55% to 2.69%) and degree of crystallinity (0.19% to 2.64%). The proposed methodology produces results that differ from those due to printing under 3% from a thermal point of view. The
new process reduces the time needed for aged powder, contributing to cost savings and waste reduction.

Originality/value - The study introduces a novel method for reprocessed powder generation, deviating from traditional printing. The originality lies in artificially aging powders, providing comparable results to actual printing. This approach offers efficiency, time savings, and waste reduction in the Laser Powder Bed Fusion process, presenting a valuable avenue for further research.

A reformulation of the dynamical component analysis (DyCA) via an optimization-free approach is presented. The original cost function approach is converted into a numerical linear algebra problem, i.e., the computation of coupled singular-value decompositions. A simple algorithm is presented together with numerical experiments to document the feasability of the approach. This methodology is able to recover the mixing and state matrices of multivariate signals from high-dimensional measured data fully.

This study describes the development of an operation-independent simulation model for an electrified die-casting foundry that uses a smart grid system to meet its energy needs. The model uses real weather and stock exchange electricity price data for the simulation period. The model can be used to determine and compare the cost of electricity for production at a given time (time of day and season) as well as the economics of different PV system and electricity storage options. It is also possible to analyze the share of different energy sources for each configuration. This can be done for sites throughout Germany. In addition, exemplary simulation studies are presented in this paper which demonstrate the wide range of applications of the model. The results provide an initial overview of the potential for savings and optimization. In the future, the model will provide a basis for determining optimum plant layouts and production times by means of simulation-based optimization.

The skilled trade industry is a significant driving force for the development and prosperity of society and constitutes the backbone of the German economy with its small and medium-sized enterprises. Currently, waiting times for craftsmen stand at approximately three months. This trend is on the rise due to the continued and severe shortage of apprentices and skilled workers. Potential trainees are representatives of Generation Z and best reached through social media channels. Consequently, many companies deliberately utilize corporate influencers in employer branding efforts to win young talents. Corporate influencers have the ability to present specifically job-related content and offer more authentic insights into the daily work environment. However, do they genuinely influence the career preferences of potential trainees? The aim of this study is to investigate if and to what extent corporate influencer influence the perception of the skilled trades industry and career preferences of potential applicants. To investigate the impact of corporate influencers on the perception of the skilled trade industry and the respective career preferences of potential applicants, we conducted a study with 66 students from a secondary school in Germany. (1) First, we measured the perception of the skilled trades industry and career preferences of the participants. (2) Then we exposed them to previously selected content of two corporate influencers from the skilled trades sector. (3) After the exposure, we measured the perception of the skilled trades industry and career preferences of the participants again. For the statistical analysis we used regression analyses and T-tests. The findings of the study show that corporate influencer on social media positively influenced both, the perception of the skilled trades industry and the career preferences of potential applicants. Particularly, insights into daily work routines prove to be effective. Simultaneously, the study reveals that the employer attractiveness of the skilled trades industry in general significantly influences the perception of the industry and enhances applicants' interest in craft professions.