ALBERT

Beschreibung: Recently, mechanical micro-milling is one of the most promising micro-manufacturing processes for productive and accurate complex-feature generation in various materials including metals, ceramics, polymers and composites. The micro-milling technology is widely adapted already in many high-tech industrial sectors; however, its reliability and predictability require further developments. In this paper, micro-milling related recent results and developments are reviewed and discussed including micro-chip removal and micro-burr formation mechanisms, cutting forces, cutting temperature, vibrations, surface roughness, cutting fluids, workpiece materials, process monitoring, micro-tools and coatings, and process-modelling. Finally, possible future trends and research directions are highlighted in the micro-milling and micro-machining areas.

Beschreibung: Rigorous emission regulations call for more efficient passive control catalysts for exhaust gas aftertreatment without affecting the internal combustion process and CO2 emissions. Although the state-of-art ceramic honeycomb substrate designs provide high surface area and a degree of flexibility for heat and mass transfer adaptations, additional emission reduction benefits can be achieved when more flexible designs to provide effective thermal management are introduced. The conventional cordierite honeycomb substrates are manufactured by extrusion; therefore, only substrates with straight channels can be fabricated. This study aims to highlight any design limitations of conventional substrates by employing additive manufacturing as the main method of manufacturing diamond lattice structures using DLP (digital light processing) technology. Both conventional substrates and diamond lattice structures are studied numerically and experimentally for flow through resistance and temperature distribution. Numerical predictions and experimental results showed good agreement. The results show the increase of the axial temperature distribution for diamond lattice structures and a significant decrease of the pressure drop (38–45%) in comparison with the benchmark honeycomb with similar surface area.

Beschreibung: A small series of ring compression tests were performed on BS970:708M40 alloy steel. The samples were tested using a 2-factor temperature variable, and a 4-factor lubricant variable, as the design parameters. Two differing soak temperatures were used, namely 1030 °C and 1300 °C respectively. The lubricants applied at the billet to tooling interface were synthetic water–based, graphite water–based, graphite and molybdenum disulphide viscous grease, and finally, unlubricated samples were tested. The ring compression tests were performed using a traditional drop forging hammer and induction heating to minimise any unintentional process variability. The impact that the two varying process parameters have upon the compression sample was then assessed by measuring each sample’s surface hardness and surface roughness prior to and post forging with fully calibrated equipment. It was demonstrated that the higher soak temperature of 1300 °C yielded a lower surface hardness value and higher surface roughness than the lower soak temperature, 1030 °C. The two water-based lubricants offered negligible change in results compared with the unlubricated forging, strongly suggesting that the lubricants were evaporated off the surface prior to forging. However, the results from the graphite–molybdenum disulphate grease do indicate in particular higher surface roughness than other lubricants, and a non-symmetric distortion pattern.

Beschreibung: A new hybrid cutting-abrasive machining tool (turn-grind) is detailed for high-quality machining of fibre reinforced polymer (FRP) composites, comprising single point carbide inserts electroplated with multi-layers of diamond abrasives 120 μm grain size, to form an abrasive region adjacent to an abrasive-free cutting edge. Experimental data are presented for turning tubes of CFRP and GFRP. The surface quality of workpieces after machining was evaluated through surface roughness measurements and SEM imaging. Cutting-only caused more defects such as delamination and fibre to pull out. Compared with cutting-only, contact and non-contact measurement of surface roughness (Ra) in both axial and radial directions showed an increase for CFRP and GFRP with roundness error reduced to 50%. No significant increase in cutting force was observed.

Beschreibung: A Correction to this paper has been published: https://doi.org/10.1007/s00170-020-06437-w

Beschreibung: This study is motivated by the need for a new advanced vibration-based bearing monitoring approach. The ARX-Laguerre model (autoregressive with exogenous) and genetic algorithms (GAs) use collected vibration data to estimate a bearing’s remaining useful life (RUL). The concept is based on the actual running conditions of the bearing combined with a new linear ARX-Laguerre representation. The proposed model exploits the vibration and force measurements to reconstruct the Laguerre filter outputs; the dimensionality reduction of the model is subject to an optimal choice of Laguerre poles which is performed using GAs. The paper explains the test rig, data collection, approach, and results. So far and compared to classic methods, the proposed model is effective in tracking the evolution of the bearing’s health state and accurately estimates the bearing’s RUL. As long as the collected data are relevant to the real health state of the bearing, it is possible to estimate the bearing’s lifetime under different operating conditions.

Beschreibung: This study presents a two-fold investigation on precision end-milling of stainless steel (AISI 316L). First, the impact of end-milling variables (cutting speed and feed rate) on the surface quality (surface roughness, microhardness, and surface morphology) was analyzed. The best surface quality with surface roughness (Ra) 0.65 ± 0.02 μm was observed for cutting speed of 140 m/min and 0.025 mm/tooth of feed rate. Microhardness was increased with increment in cutting speed. Second, the impact of surface roughness (Ra) on the stress corrosion cracking under two different mediums, i.e., body solutions (Hank’s solution) and 1 M hydrochloric acid solution, was studied. The investigations showed that the samples with higher surface roughness values were more prone to stress corrosion cracking.

Beschreibung: Human-robot interaction (HRI) promises to be a means whereby manufacturing companies will be able to address current challenges like a higher demand for customization. However, despite comparably low costs, there are only few applications in practice. To date, it remains unclear which factors facilitate or hinder the successful introduction of industrial collaborative robots (cobots). In a three-step approach, we first developed a comprehensive two-dimensional framework covering three separate phases and four essential components for human-robot working systems. Secondly, we reviewed related literature to identify relevant success factors. Thirdly, in an online survey we asked leading representatives of German manufacturing companies (n = 81) to assess the importance of these factors from a practical point of view. The results reveal that besides technology-related factors like occupational safety and appropriate cobot configuration, employee-centered factors like the fear of job loss and ensuring an appropriate level of trust in the robot are considered important. However, company representatives seem to underestimate the impact of subtle measures to increase employee acceptance which could be incorporated into internal communication strategies prior to and during the introduction of cobots. Comparative analysis based on three distinct application scenarios suggests that most success factors’ practical importance is independent of the motivation for implementing HRI. Furthermore, answers from practitioners in free-text fields reveal that success factors which intuitively come to their mind such as financial factors are not necessarily perceived most important. Finally, we argue for more application-oriented research that focuses on practically relevant factors to guide HRI research, inform cobot development, and support companies in overcoming apparent barriers.

Beschreibung: This work proposes a model for suggesting optimal process configuration in plunge centreless grinding operations. Seven different approaches were implemented and compared: first principles model, neural network model with one hidden layer, support vector regression model with polynomial kernel function, Gaussian process regression model and hybrid versions of those three models. The first approach is based on an enhancement of the well-known numerical process simulation of geometrical instability. The model takes into account raw workpiece profile and possible wheel-workpiece loss of contact, which introduces an inherent limitation on the resulting profile waviness. Physical models, because of epistemic errors due to neglected or oversimplified functional relationships, can be too approximated for being considered in industrial applications. Moreover, in deterministic models, uncertainties affecting the various parameters are not explicitly considered. Complexity in centreless grinding models arises from phenomena like contact length dependency on local compliance, contact force and grinding wheel roughness, unpredicted material properties of the grinding wheel and workpiece, precision of the manual setup done by the operator, wheel wear and nature of wheel wear. In order to improve the overall model prediction accuracy and allow automated continuous learning, several machine learning techniques have been investigated: a Bayesian regularized neural network, an SVR model and a GPR model. To exploit the a priori knowledge embedded in physical models, hybrid models are proposed, where neural network, SVR and GPR models are fed by the nominal process parameters enriched with the roundness predicted by the first principle model. Those hybrid models result in an improved prediction capability.