The present analytical design of shrink fits typically results in an uneven stress condition that can lead to failure in a variety of manners. With increasing loads and the use of brittle materials, the optimization of the stresses in the shrink fit hence becomes increasingly necessary. Currently existing approaches do not solve the problem satisfactorily or increase the manufacturing and design effort. This paper therefore considers the implementation of an AI-based stress optimization using reinforcement learning, which performs stress optimization by geometrically contouring the interstice.
As part of the digital transformation towards Industry 4.0, the tasks of staff on the shop floor are changing. Despite increasing automation, complex assembly steps still have to be carried out by humans, especially when it comes to complex products rich in variants, whose assembly cannpt be fully automated for various reasons. Due to increasing individualization and the steadily growing complexity of products, providing the right information at the right time and in the right place is becoming more important. In this context, the visualization of information via novel technologies such as augmented reality plays a crucial role towards an efficient and error-free production process. This paper compiles existing challenges when using augmented reality as a visualization form for an assistance system. On the one hand, the challenges found originate from a systematic literature review and are organized according to predefined categories. On the other hand, these challenges are complemented and compared through findings gained from expert interviews, which are conducted with employees of two European commercial vehicle manufacturers in the field of production. The analysis of the two methods highlights the need for further research.
Due to the continuous progress in information technology, complex problems of machine elements can be investigated using numerical methods. The focus of these investigations and optimizations often aims to reduce the stresses that occur or to increase the forces and torques that can be transmitted. Interference fit connections are an essential machine element for drive technology applications and are characterized by their economical fabrication. The transmission of external loads over a large contact surface between the shaft and hub makes it less vulnerable to impact loads. These advantages contrast with disadvantages such as the limited transmittable power, the risk of friction fatigue, and stress peaks at the hub edges, which can lead to undesirable and sudden failure, especially in the case of brittle hub materials. Analytical approaches already exist for optimizing these connections, which are expensive, time-consuming, and complex, so a high degree of expert knowledge is required to apply these methods in practice successfully. This paper presents a novel method using the example of optimizing the pressure distribution in the interface of a shrink-fit connection.
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