The purpose of this study is to predict the trajectory of an envelope when conveyed between two flat belts in a mail sorting machine. Each of the two sides of the envelope is in contact with one belt. The friction coefficient can vary between the two sides, e.g. for the cases of a postcard or a plastic windowed envelope. The two belts are assumed to travel horizontally with the same velocities, but in real world small velocity differences can occur. Also, some deviation from the horizontality of the belts can be observed. These phenomena can lead to unexpected situations where the relative position of the envelope to the belt changes during transportation. The work focuses on the belt-envelope mechanical interactions in order to predict the envelope position during its conveying. A 2D model is developed which considers the dynamic equilibrium of the envelope and simulates the transient behavior at different locations in the sorting machine. In the dynamic friction model, the contact surfaces between the envelope sides and the belts have to be determined at each time step. The belt/envelope friction forces are applied at the centers of these contact surfaces One side of the envelope is considered stuck (in adhesion) to the belt while the other is considered slipping. The position of the envelope center of gravity and the angle with the horizontal axis are calculated. For evaluation of the proposed dynamic model, several cases of operation are simulated.
Robustness is the key to successful product design when many variation sources exist throughout the product lifecycle. Variations are of many sources such as material defects, machining errors, and use conditions of the product. Most of product performance simulations are traditionally carried out using the numerical model created in the CAD system. This model only represents the nominal information about the product. Thus, it is difficult to take these variations into account in product performance prediction. A method is proposed in this paper to allow integrating the effect of these variation sources into the product performance simulation. This method is based on a random design of experiment method. As a result, an image of the "real" performance of the product is determined.
