Lightweight potential is a powerful indicator – but not as powerful as it could be. Current methods for analyzing a product's potential to be reduced in mass only deal with a few of the most important criteria for lightweight design. The amount of literature dealing with lightweight design is significant, yet it can help to understand these versatile criteria. Firstly, the literature on this topic will therefore be reviewed to derive a broad set of criteria used in contemporary lightweight design. Secondly, a further review will reveal the criteria used to derive lightweight potential. Subsequently, both sets will be compared to identify the missing criteria used for the derivation of lightweight potential. This will support designers in two ways. On the one hand, matching and combining both criteria sets will enable the most representative criteria for a particular design case to be chosen, thus leading to a more comprehensible derivation of lightweight potential. On the other hand, the combination set will provide a basis for designers and design teams to refine their understanding of their own motivations for conducting lightweight design.
Lightweight design methods help the engineer to design lighter products. However, none of the existing methods support lightweight design with regard to the state of motion of mass and the mass distribution. This paper presents an analytic method to fill this gap. The method uses kinetic and potential energies to determine an energy level factor. This factor enables the engineer to derive an optimization potential and order of all different product assemblies. Finally, a case study is performed on a processing machine to illustrate the effectiveness of the developed method.
Kinetic models of human motion rely on boundary conditions which are defined by the interaction of the body with its environment. In the simplest case, this interaction is limited to the foot contact with the ground and is given by the so called ground reaction force (GRF). A major challenge in the reconstruction of GRF from kinematic data is the double support phase, referring to the state with multiple ground contacts. In this case, the GRF prediction is not well defined. In this work we present an approach to reconstruct and distribute vertical GRF (vGRF) to each foot separately, using only kinematic data. We propose the biomechanically inspired force shadow method (FSM) to obtain a unique solution for any contact phase, including double support, of an arbitrary motion. We create a kinematic based function, model an anatomical foot shape and mimic the effect of hip muscle activations. We compare our estimations with the measurements of a Zebris pressure plate and obtain correlations of 0.39≤r≤0.94 for double support motions and 0.83≤r≤0.87 for a walking motion. The presented data is based on inertial human motion capture, showing the applicability for scenarios outside the laboratory. The proposed approach has low computational complexity and allows for online vGRF estimation.
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