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Resumo Este trabalho apresenta uma revisão das metodologias mais utilizadas como ferramentas de apoio ao planejamento da produção de sistemas de manufatura. Dentre elas destacam-se as práticas industriais conhecidas como técnicas avaliativas de soluções e os métodos de otimização conhecidos como técnicas gerativas de solução. Procura-se discutir como estas técnicas trabalham e analisar as vantagens e desvantagens de cada uma delas. Na conclusão a otimização é apresentada como uma ferramenta complementar para superar certas deficiências encontradas durante a aplicação das práticas industriais, tornando-se assim essencial ao planejamento da produção.Palavras-chave: MRP, JIT, programação matemática, planejamento da produção.

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A stochastic linear production planning problem with chanceconstraints is introduced in order to provide a production plan that optimizes a reverse logistics system. Such a system is composed of two channels: in the forward channel, new and remanufactured products are produced and stored into a serviceable unit, while, in the reverse channel, used products collected from market are stored into a returnable unit. The uncertainties about fluctuation of demand and amount of returnable are the reason of the stochastic nature of the problem. Since global optimal solution is not easy to be achieved, near-optimal solutions become viable alternatives to be explored. In this paper, an equivalent deterministic version of the stochastic problem is presented. This equivalent problem provides an open-loop solution that is used to provide production scenarios. An example illustrates the applicability of this methodology by creating two distinct production scenarios in order to answer the following question: "Is it possible to reduce the total production cost of a company by increasing the return rate of collecting, even knowing that the cost for remanufacturing is greater than the cost for manufacturing new products?

Abstract:In this paper, an aggregate production planning problem is formulated as a chance-constrained stochastic control problem under imperfect information of states (i.e., the inventory levels). Using the Kalman filter device, the mean and covariance of state variables are estimated. Then the certainty equivalence principle is applied, resulting in a deterministic problem that is equivalent to the original formulation. In order to provide a sequential optimal solution to the equivalent problem, the Naive Feedback Controller (NFC) approach is used. It provides a revised sub-optimal production policy to the stochastic problem. An example illustrates the applicability of this approach. Copyright@2005 IFAC