This paper investigates the performance of classical cellular manufacturing systems compared to other two systems proposed in literature: fractal cells and remainder cells. This paper proposes three strategies to control a cellular manufacturing system with remainder cell and how to configure and control a fractal manufacturing system. The performance measures of the manufacturing systems are analyzed when several unforeseen events occur as: machine breakdowns, production mix changes, demand fluctuations, and processing time variability. A simulation environment developed by Arena® package was used to investigate the three manufacturing system configurations. The performance measures investigated are: throughput, throughput times of the parts, work in process, manufacturing utilization, and due date performance (tardiness). The simulation results show how the fractal and remainder cells can be a valid alternative to cellular manufacturing systems in a very dynamic environment
International audienceCellular manufacturing systems are used when both production volume and product variety are at medium level. The fluctuations of volume and mix can reduce drastically the performance of classical cellular manufacturing systems. Therefore, several configurations have been proposed in literature as virtual manufacturing cells, fractal cells and remainder cells. This paper investigates the cell loading approaches in a manufacturing system composed of dedicated cells and a remainder cell. The remainder cell consists of machines able to manufacture all part families. The loading decision concerns the allocation of the parts to the remainder cell, instead of the dedicated cell. A simulation environment based on Rockwell ARENA® has been developed to test the proposed approaches. The performance measures are evaluated in a very dynamic environment characterized by volume oscillations, mix fluctuations and machine failures. A classical cellular manufacturing system is used as a benchmark for the performance measures analyzed. The simulation results show that the proposed policies lead to better performance when market fluctuations occur
Currently, there is a growing interest of industries in applying additive manufacturing (AM) technology for generating objects with high geometrical complexity and low weight, ensuring good performance, comparable to those ones of products realized by means of traditional techniques. Anyway, it is still usual to realize AM products without focusing on the morphology of the object, hence without exploiting all the advantages of the technique. Indeed, since the several suitable AM technologies, it should be useful to know the functional characteristics of the component for the best choice of the appropriate one and its constructive complexity. In this regard, the 3D modeling strategy is extremely crucial for a proper realization of AM products. The paper deals with a study of the geometrical complexity of dashboard components of a car, based on several techniques for evaluating the geometric complexity. The latter is a fundamental element for estimating the feasibility of AM in terms of production costs and the benefits with respect to traditional molding. In detail, the study focuses on comparing several geometrical complexity evaluation techniques in order to identify the one that simplifies the calculation and better approximates the most used in literature.
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