The Master Production Schedule (MPS) is the link between the strategic plan and the operative production plan. Indeed, several authors claim that MPS is one of the most important input for MRP module and detailed scheduling. In this paper the authors propose a rolling horizon MPS model for production systems with multiple production lines in presence of multiple objective functions and minimum batch-sized production lot constraints. In order to achieve long and medium term planning in a flowshop production process, the authors developed an MPS tactical planner, which schedules jobs on a horizon varying from six to ten months, considering finite capacity constraints. The planning algorithm is composed by two main procedures: the first one chooses the best heuristic by the comparison of twelve different heuristics by using production input and stochastic sales forecasts; the second one performs the scheduling of the strategic production plan by using the best heuristic previously selected and deterministic inputs. As a result the MPS is derived by using a selected heuristic starting from a stochastic comparison, even if the final production plan is obtained trough deterministic input. For these reasons we are confident that the final MPS is both robust (stochastic validation) and realistic (based on a finite capacity planning).

Strategic planning and production control: deriving an useful master production schedule from sales forecasts.

MOSCA, ROBERTO;TONELLI, FLAVIO
2005-01-01

Abstract

The Master Production Schedule (MPS) is the link between the strategic plan and the operative production plan. Indeed, several authors claim that MPS is one of the most important input for MRP module and detailed scheduling. In this paper the authors propose a rolling horizon MPS model for production systems with multiple production lines in presence of multiple objective functions and minimum batch-sized production lot constraints. In order to achieve long and medium term planning in a flowshop production process, the authors developed an MPS tactical planner, which schedules jobs on a horizon varying from six to ten months, considering finite capacity constraints. The planning algorithm is composed by two main procedures: the first one chooses the best heuristic by the comparison of twelve different heuristics by using production input and stochastic sales forecasts; the second one performs the scheduling of the strategic production plan by using the best heuristic previously selected and deterministic inputs. As a result the MPS is derived by using a selected heuristic starting from a stochastic comparison, even if the final production plan is obtained trough deterministic input. For these reasons we are confident that the final MPS is both robust (stochastic validation) and realistic (based on a finite capacity planning).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/238959
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