Scheduling of inventory releasing jobs to satisfy time-varying demand: an analysis of complexity

This paper studies a new class of single-machine scheduling problems, which are faced by Just-in-Time-suppliers satisfying a given demand. In these models the processing of jobs leads to a release of a predefined number of product units into inventory. Consumption is triggered by predetermined time-varying, and product-specific demand requests. While all demands have to be fulfilled, the objective is to minimize the resulting product inventory. We investigate different subproblems of this general setting with regard to their computational complexity. For more restricted problem versions strongly polynomial time algorithms are presented. In contrast to this, NP-hardness in the strong sense is proven for more general problem versions. Moreover, for the most general version, even finding a feasible solution is shown to be strongly NP-hard.     

Performance evaluation of unbalanced flow lines with general distributed processing times, failures and imperfect production

In this paper an analytical approximation for the performance of non-homogenous asynchronous Flow Production Systems (FPSs) with finite buffers is presented. Generally distributed stochastic processing times as well as breakdowns and imperfect production are considered. The procedure explicitly accounts for simultaneous blocking and starving. The approximation is based on the decomposition of an M-station-line into M — 1 two-station-lines which are analyzed with the help of a GI/G/I/N_max queueing model. Numerical comparisons with exact and simulation results for hypothetical as well as for real-life flow-lines indicate that the procedure provides accurate results.     

Development of a predictive simulation method for thin flash generation in flashless precision forging processes of aluminum parts using FEA and experiments

In this paper, the investigation of thin flash generation in precision forging process of an aluminum long flat part is described. The aim was to derive a predictive simulation method for thin flash generation in order to increase both process and part quality in the future. The forging processes were varied by use of different preforms with equal volumes but different mass distributions while using the same final part geometry. The experimentally forged parts were analyzed concerning the amount and part area of the generated thin flash. The conducted FE simulations were analyzed concerning the hydrostatic pressure values p in the part areas near to the tool gap between upper and lower die immediately before form-filling. For a more detailed comparison, single p values were included to hydrostatic pressure functions P. The comparison between the P functions and the experimentally determined thin flash height shows, that high pressure values as well as high gradients of the P functions indicate less thin flash generation. The method therefore allows a qualitative prediction of thin flash generation. It can provide two kind of information. First: The prediction of the specific locations where thin flash is likely to occur in one final part by use of one single preform. Second: The qualitative prediction of the specific final part areas were thin flash is likely to occur depending on different preform geometries. This method will decreases the necessity of time-consuming forging trials and can shorten the preform designing process in the future.     

Polyamides Derived from Terpenes: Advances in Their Synthesis,Characterization and Applications

Polyamides are very important polymers, with applications from commodities up to high-performance materials for, for example, fibers or for the biomedical sector. Nowadays, still most of them are synthesized from fossil resources. With regards to sustainability and bioeconomy, and especially regarding the new structures and properties that can thus be achieved, the preparation of polyamides (PAs) from natural precursors is getting more and more important. For this, especially the utilization of terpenes, a large and important group of natural products with different functions in nature (regulators, defense signals, etc.), is important, which is described herein. Similar approaches are interesting from a scientific point of view regarding, for example, structure-function-relations, but also with regards to different applications as, for example, high-performance or biomedical materials. Practical applications: Terpene-based polyamides can find many applications, from commodities up to high-performance fibers and special materials in (bio)medicine, for example, drug delivery, tissue engineering, etc.     

Prediction of fracture healing under axial loading,shear loading and bending is possible using distortional and dilatational strains as determining mechanical stimuli

Numerical models of secondary fracture healing are based on mechanoregulatory algorithms that use distortional strain alone or in combination with either dilatational strain or fluid velocity as determining stimuli for tissue differentiation and development. Comparison of these algorithms has previously suggested that healing processes under torsional rotational loading can only be properly simulated by considering fluid velocity and deviatoric strain as the regulatory stimuli. We hypothesize that sufficient calibration on uncertain input parameters will enhance our existing model, which uses distortional and dilatational strains as determining stimuli, to properly simulate fracture healing under various loading conditions including also torsional rotation. Therefore, we minimized the difference between numerically simulated and experimentally measured courses of interfragmentary movements of two axial compressive cases and two shear load cases (torsional and translational) by varying several input parameter values within their predefined bounds. The calibrated model was then qualitatively evaluated on the ability to predict physiological changes of spatial and temporal tissue distributions, based on respective in vivo data. Finally, we corroborated the model on five additional axial compressive and one asymmetrical bending load case. We conclude that our model, using distortional and dilatational strains as determining stimuli, is able to simulate fracture-healing processes not only under axial compression and torsional rotation but also under translational shear and asymmetrical bending loading conditions.     

Load and health monitoring in glass fibre reinforced composites with an electrically conductive nanocomposite epoxy matrix

Fibre reinforced polymers (FRPs) are an important group of materials in lightweight constructions. Most of the parts produced from FRPs, like aircraft wings or wind turbine rotor blades are designed for high load levels and a lifetime of 30 years or more, leading to an extremely high number of load cycles to sustain. Consequently, the fatigue life and the degradation of the mechanical properties are aspects to be considered. Therefore, in the last years condition monitoring of FRP-structures has gained importance and different types of sensors for load and damage sensing have been developed.

In this work a new approach for condition monitoring was investigated, which, unlike other attempts, does not require additional sensors, but instead is performed directly by the measurement of a material property of the FRP. An epoxy resin was modified with two different types of carbon nanotubes and with carbon black, in order to achieve an electrical conductivity. Glass fibre reinforced composites (GFRP) were produced with these modified epoxies by resin transfer moulding (RTM). Specimens were cut from the produced materials and tested by incremental tensile tests and fatigue tests and the interlaminar shear strength (ILSS) was measured. During the mechanical tests the electrical conductivity of all specimens was monitored simultaneously, to assess the potential for stress/strain and damage monitoring.

The results presented in this work, show a high potential for both, damage and load detection of FRP structures via electrical conductivity methods, involving a nanocomposite matrix.     

Influence of different carbon nanotubes on the mechanical properties of epoxy matrix composites – A comparative study

Carbon nanotubes (CNTs) in general are considered to be highly potential fillers to improve the material properties of polymers. However, questions concerning the appropriate type of CNTs, e.g., single-wall CNTs (SWCNT), double-wall CNTs (DWCNT) or multi-wall CNTs (MWCNT), and the relevance of a surface functionalisation are still to be answered. This first part of the study focuses on the evaluation of the different types of nanofillers applied, their influence on the mechanical properties of epoxy-based nanocomposites and the relevance of surface functionalisation. The nanocomposites produced exhibited an enhanced strength and stiffness and even more important, a significant increase in fracture toughness (43% at 0.5 wt% amino-functionalised DWCNT). The influence of filler content, the varying dispersibility, the aspect ratio, the specific surface area and an amino-functionalisation on the composite properties are discussed and correlated to the identified micro-mechanical mechanisms.     

Ergebnisse eines Ringversuchs zur Bestimmung magnetischer Streufelder in Elektronenstrahlmikroanalysatoren

Die Elektronenstrahlmikroanalyse ferromagnetischer Werkstoffe kann durch magnetische Streufelder, die infolge einer ungenügenden Abschirmung der elektromagnetischen Linsen auftreten, stark verfälscht werden. Es kommt zu Strahlauswanderungen, die, in Abhängigkeit vom Meßort auf der Probe, im Bereich von 100 μm liegen können. In einem Ringversuch des Arbeitskreises Elektronenstrahl-Mikroanalyse des VDEh wurden mit einer definierten Stahlprobe die Geräte der 13 beteiligten Labore auf magnetische Streufelder hin untersucht.     

Blockwise processing applied to brain microvascular network study

The study of cerebral microvascular networks requires high-resolution images. However, to obtain statistically relevant results, a large area of the brain (several square millimeters) must be analyzed. This leads us to consider huge images, too large to be loaded and processed at once in the memory of a standard computer. To consider a large area, a compact representation of the vessels is required. The medial axis is the preferred tool for this application. To extract it, a dedicated skeletonization algorithm is proposed. Numerous approaches already exist which focus on computational efficiency. However, they all implicitly assume that the image can be completely processed in the computer memory, which is not realistic with the large images considered here. We present in this paper a skeletonization algorithm that processes data locally (in subimages) while preserving global properties (i.e., homotopy). We then show some results obtained on a mosaic of three-dimensional images acquired by confocal microscopy.