Set-up planning is an important step in manufacturing a part type, and it can be used to integrate the manufacturing functions of process planning and scheduling. While considering the problem from optimisation perspective, set-up planning involves several issues such as grouping the features, tool approach direction (TAD) and machining operations. Here, we have considered the minimisation of total manufacturing cost, makespan and maximisation of the machine utilisation to obtain an optimal set-up plan while satisfying all the constraints. The cross-machine adaptive set-up planning (ASP) for a part is a nested partition (NP)-hard problem with flexible machining resources. Also, its impact on the integration of process planning and scheduling is a crucial step. The NP-based approach, which partitions the solution space, selecting the most promising region according to the formulated objective function, is adapted and reported in this article. This approach clusters the computational effort in the most promising region and also generates an exact optimal solution for underlying various set-up planning. The proposed algorithm has been tested by taking an illustrative example, and the results are compared with genetic algorithm. Further, five diverse scenarios are studied to prove the efficiency of the proposed approach.
A nested partitioning-based approach to integrate process planning and scheduling in flexible manufacturing environment
MATTA, ANDREA;
2015-01-01
Abstract
Set-up planning is an important step in manufacturing a part type, and it can be used to integrate the manufacturing functions of process planning and scheduling. While considering the problem from optimisation perspective, set-up planning involves several issues such as grouping the features, tool approach direction (TAD) and machining operations. Here, we have considered the minimisation of total manufacturing cost, makespan and maximisation of the machine utilisation to obtain an optimal set-up plan while satisfying all the constraints. The cross-machine adaptive set-up planning (ASP) for a part is a nested partition (NP)-hard problem with flexible machining resources. Also, its impact on the integration of process planning and scheduling is a crucial step. The NP-based approach, which partitions the solution space, selecting the most promising region according to the formulated objective function, is adapted and reported in this article. This approach clusters the computational effort in the most promising region and also generates an exact optimal solution for underlying various set-up planning. The proposed algorithm has been tested by taking an illustrative example, and the results are compared with genetic algorithm. Further, five diverse scenarios are studied to prove the efficiency of the proposed approach.File | Dimensione | Formato | |
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