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Deploying an airbag when a vehicle occupant is too close to it can cause injury. An adaptive Airbag Control Unit (ACU) would improve the effectiveness of the safety system, provided it is aware of the actual position of the occupants once the crash is going to occur. Occupants can be monitored with vision-based and radar-based sensing in the vehicle, but the research question is whether other reliable devices exist. In this research, a real seat is equipped with four sensors in the supports from the floor, as well as an Inertial Measurement Unit (IMU) and a microcontroller. The device is capable of identifying correct position or different Out of Position (OP) conditions and inform an adaptive ACU. The paper presents the seat layout in detail and its testing in extensive driving experiments with multiple participants. Depending on the position of the driver, the identification is correct 45–100% of the time. Monitoring the occupant position by a sensorized seat is feasible and can improve the reliability of the onboard safety system when integrated with other occupant monitoring devices. [ABSTRACT FROM AUTHOR]

Gravity sand casting simulations require accurate modelling of heat transfer phenomena to reliably evaluate the expected quality of the produced parts. Average model parameters can be easily retrieved from a validated database. However, these parameters are highly dependent on the specific sand used and the actual forming process in the foundry. Furthermore, the heat transfer from the solidifying alloy to the mould surfaces is not precisely known, so simulation models usually use typical values for overall heat transfer coefficients. Most research works investigate individual parameters, whereas heat transfer phenomena largely arise from their interaction together. Therefore, the present work describes a combined experimental and computational method based on genetic algorithm techniques for determining the most important parameters for heat transfer in a sand mould. The experiments examine both virgin and reused sand, as these are alternatively used in the foundry for mould forming. The density, thermal conductivity, and specific heat capacity of the different sands are identified, along with heat transfer coefficients. The counterproof simulations demonstrate that the standard parameters are quite reliable for virgin sand. However, in the case of reused sand, the identified parameters lead to more reliable results. [ABSTRACT FROM AUTHOR]

A die for Al alloy casting must be designed to achieve the expected quality levels. Moreover, the casting unit cost must be regarded as the objective function to be minimised. It can be expressed as a function of the quantity of materials and energy to be used, cycle time and equipment investment. This work compares the performance of the die with inserts manufactured using the usual 1.2343 steel with that of the innovative 1.2383. The latter is considered due to its enhanced thermal conductivity, despite being more expensive. Simulation experiments are designed to evaluate different die layouts. The quality design solutions are evaluated against the cost objective function in order to identify the optimal die choice. A case study on gravity die casting (GDC) of an AlSi7Mg0.3 engine head shows faster solidification dynamics when using 1.2383 instead of 1.2343 steel. This reduces the feeder volume, thus increasing the production yield and speeding up the cycle time with a leverage effect. The higher investment cost for the inserts is rapidly returned thanks to the reduction in variable costs. The Return On Investment (ROI) with the improved die in the new solution is short compared with the life of the die.

Featured Application: This paper presents how to develop a top-down design tool, namely a design archetype that stores knowledge and supports a designer in the selection and dimensions of the most suitable working principles to address the requirements of a project. Thanks to the integration between a knowledge-based approach and parametric three-dimensional (3D) computer-aided design (CAD) modeling, the design tool automatically generates CAD models of the mechanical components and the final assembly. The usability of the design tool is improved by a Graphical User Interface which is able to support designers during input data entry and output data management. Engineering design is a knowledge intensive activity for both new and mature technical systems, such as mechanical transmissions. However, design knowledge is often transferred with conservative and unstructured approaches, although knowledge management would be of the utmost importance for modern industries. In this work, we introduce a design tool, called design archetype, for collecting and managing knowledge in systematic design processes. The design archetype addresses input design requirements for different design concepts, therefore, improving awareness of the design process by interactively modifying the design solution due to different input requirements. Finally, the design archetype updates the parameters of a first embodiment computer-aided design model of the concept. A method for the development of design archetypes is presented and applied to two case studies of mechanical transmission subassemblies. The results demonstrate the effectiveness of a systematic design method based on design archetypes stored in the company database. [ABSTRACT FROM AUTHOR]

The reduction of energy consumption is today addressed with great effort in manufacturing industry. In this paper, we improve upon a previously presented method for robotic system scheduling. By applying dynamic programming to existing trajectories, we generate new energy optimal trajectories that follow the same path but in a different execution time frame. With this new method, it is possible to solve the optimization problem for a range of execution times for the individual operations, based on one simulation only. The minimum energy trajectories can then be used to derive a globally energy optimal schedule. A case study of a cell comprised of four six-link manipulators is presented, in which energy optimal dynamic time scaling is compared to linear time scaling. The results show that a significant decrease in energy consumption can be achieved for any given cycle time. [ABSTRACT FROM AUTHOR]

Reduction of energy consumption is important for reaching a sustainable future. This paper presents a novel method for optimizing the energy consumption of robotic manufacturing systems. The method embeds detailed evaluations of robots' energy consumptions into a scheduling model of the overall system. The energy consumption for each operation is modeled and parameterized as function of the operation execution time, and the energy-optimal schedule is derived by solving a mixed-integer nonlinear programming problem. The objective function for the optimization problem is then the total energy consumption for the overall system. A case study of a sample robotic manufacturing system and an experiment on an industrial robot are presented. They show that there exists a real possibility for a significant reduction of the energy consumption in comparison to state-of-the-art scheduling approaches. [ABSTRACT FROM PUBLISHER]