Aplicação de modelos de redes de filas abertas no projeto e planejamento de sistemas discretos de manufatura.

Abstract

The management of manufacturing systems have become more complex, once that new products are arising, product demands are uncertain, life cycles get shorter, and a wide variety of products compete for common resources. This thesis deals with the design and planning of discrete manufacturing systems, based on open queueing network models to support the decision making of capacity allocation. As manufacturing systems may be represented by generalized queueing networks, and there are no exact solution methods, here is employed the decomposition approximate method to evaluate the performance of systems under different configurations. It is shown in the thesis how these approximations are suitable and effective to estimate the work-in-process (WIP) and the production leadtime of an actual metallurgical industry queueing network. It is also shown that discrete capacity allocation models, based on the approximations, are effective to evaluate and optimize the performance of the case study under different configurations. Trade-off curves between capacity investment and WIP are generated and are useful not only to support a manager to estimate how much capacity he/she should allocate, but also to decide where it should be allocated in the queueing network. These curves also support the decision making in terms of capacity, if the variability of the external arrivals, the product mix and/or the throughput for the network change. Besides adding capacity, partitioning the facility is another alternative to reduce the system complexity. This thesis also approaches the focused factory design problem, involving the partition of the facility into smaller shops and the capacity allocation in each shop. Again, the decomposition approximations were employed to evaluate the system performance. Despite its importance, this problem has rarely been reported in the literature. In this thesis, the goal is to reduce the system complexity either from the product management point of view or from the workstation management point of view. From the product management point of view, a model whose complexity constraint is na upper limit on the production leadtime variance of the products passing through the network was studied. From the workstation management point of view, the complexity constraint of the model keeps constant the expected waiting time of a product at a workstation, once it waits for being served. It is shown through these models for some instances that the partition of the facility into smaller shops decreases the complexity system without necessary capacity additional investments. Futhermore, sometimes it is possible to keep the network performance (or even to improve it), partitioning the network into smaller shops which need less capacity than the original configuration with a single shop.