Abstract

The problem of operation sequencing is affected by geometrical parameters such as tool compatibility, feature symmetry, feature accessibility, feature orientation and non-geometrical parameters such as dimensional tolerance, geometric tolerance, location tolerance and surface finish. Operation sequences are determined after meeting the objective functions such as minimum setup changeover and tool changeover, maximum tool motion continuity and maximum loose precedence among features. Because of the conflicting nature of the objectives and constraints, it is a tedious task to formulate a single objective function that can meet the requirements of the problem. Thus in this paper, an attempt has been made to address this issue to an extent by developing operation sequencing rating index (OSRI) which is the weighted sum of four indices: setup changeover index, tool changeover index, motion continuity index and loose precedence index. Determination of setup changeover index involves datum selection and sequencing in addition to grouping features into setup. Owing to the combinatorial nature of the problem, the simulated annealing (SA) based algorithm has been employed to determine the optimal/near-optimal operation sequence by maximising OSRI. In the proposed methodology, a perturbation scheme named as modified shifting scheme (MSS) has been devised to generate a feasible neighbourhood sequence that minimizes the search space and helps the algorithm to escape from local optima. A new approach for temperature variation in the SA algorithm is also incorporated in which the temperature is assumed to be parabolic. The advantage and effectiveness of the proposed methodology in terms of its algorithmic implementation have been verified on four test parts.

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