8 research outputs found
STARD 2015: An Updated List of Essential Items for Reporting Diagnostic Accuracy Studies.
Incomplete reporting has been identified as a major source of avoidable waste in biomedical research. Essential information is often not provided in study reports, impeding the identification, critical appraisal, and replication of studies. To improve the quality of reporting of diagnostic accuracy studies, the Standards for Reporting of Diagnostic Accuracy Studies (STARD) statement was developed. Here we present STARD 2015, an updated list of 30 essential items that should be included in every report of a diagnostic accuracy study. This update incorporates recent evidence about sources of bias and variability in diagnostic accuracy and is intended to facilitate the use of STARD. As such, STARD 2015 may help to improve completeness and transparency in reporting of diagnostic accuracy studies
High-precision motion system design by topology optimization considering additive manufacturing
In the design process of high-precision motion stages, the dynamic behavior is of paramount importance. Manual design of such a stage is a time-consuming process, involving many iterations between engineers responsible for mechanics, dynamics and control. By using topology optimization in combination with additive manufacturing, post-processing using traditional machining and parts assembly, it is possible to arrive at an optimal design in an automated manner. The printing, machining, and assembly steps are incorporated in the optimization in order to directly arrive at a manufacturable design. With a motion stage demonstrator optimized for maximum eigenfrequencies, it is shown that combining additive manufacturing and topology optimization at industry-relevant design precision is within reach and can be applied to high-performance motion systems.Structural Optimization and Mechanic
Realization and assessment of metal additive manufacturing and topology optimization for high-precision motion systems
The design of high-precision motion stages, which must exhibit high dynamic performance, is a challenging task. Manual design is difficult, time-consuming, and leads to sub-optimal designs that fail to fully exploit the extended geometric freedom that additive manufacturing offers. By using topology optimization and incorporating all manufacturing steps (printing, milling, and assembly) into the optimization formulation, high-quality optimized and manufacturable designs can be obtained in an automated manner. With a special focus on overhang control, minimum feature size, and computational effort, the proposed methodology is demonstrated using a case study of an industrial motion stage, optimized for maximum eigenfrequencies. For this case study, an optimized design can be obtained in a single day, showing a substantial performance increase of around 15% as compared to a conventional design. The generated design is manufactured using laser powder-bed fusion in aluminum and experimentally validated within 1% of the simulated performance. This shows that the combination of additive manufacturing and topology optimization can enable significant gains in the high-tech industry.Structural Optimization and MechanicsMechanical, Maritime and Materials Engineerin
High-precision motion system design by topology optimization considering additive manufacturing
In the design process of high-precision motion stages, the dynamic behavior is of paramount importance. Manual design of such a stage is a time-consuming process, involving many iterations between engineers responsible for mechanics, dynamics and control. By using topology optimization in combination with additive manufacturing, post-processing using traditional machining and parts assembly, it is possible to arrive at an optimal design in an automated manner. The printing, machining, and assembly steps are incorporated in the optimization in order to directly arrive at a manufacturable design. With a motion stage demonstrator optimized for maximum eigenfrequencies, it is shown that combining additive manufacturing and topology optimization at industry-relevant design precision is within reach and can be applied to high-performance motion systems.</p
The value of lead time reduction and stabilization: A comparison between traditional and collaborative supply chains
This work quantifies the financial impact of the mean and the variability of production and shipping lead times on multi-echelon supply chains. We combine agent-based modelling and Taguchi methods, through which we develop a framework for supporting entrepreneurial investment decisions. A throughput-based analysis reveals that decreasing mean lead times improves the internal operation of production and distribution systems, while reducing lead time variability enhances the satisfaction of consumers. In this regard, we contrast traditional and collaborative supply chains. We find that the latter are not only more profitable than the former, but also more robust to variations in lead times