• Journal of the Korean Society for Precision Engineering
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• v.15 no.4
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• pp.111-117
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• 1998

In order to increase productivity of an assembly system composed of multiple robots along a conveyer line, an efficient sequence planning is necessary because the assembly time is dependent upon the assembly sequence. In this paper, a two-robot assembly system is considered in which two robots operate simultaneously and transfer parts from the part feeders to the workpiece on the conveyer one by one. In this case, the distance from the feeder to the workpiece varies with time because the workpiece moves at a constant speed on the conveyer. Hence, the sequence programming is not a trivial problem. Also, the two robots may interfere with each other kinematically and dynamically due to the simultaneous operation, so the sequence should be programmed to avoid the interferences. In this paper, the task sequence optimization problem is formulated and is solved by employing the simulated annealing which has been shown to be effective for solving large combinatorial optimizations.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.8
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• pp.1854-1868
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• 1995

An effective nesting algorithm has been proposed to allocate the arbitrary shapes on one or several raw sheets by applying the well-known simulated annealing algorithm as the optimization technique. In this approach, both the shapes to be allocated and the raw sheets are represented as the grid-based models. This algorithm can accommodate every possible situations encountered in cutting apparel parts from the raw leather sheets. In other words, the usage of the internal hole of a shape for other small shapes, handling of the irregular boundaries and the interior defects of the raw sheets, and the simultaneous allocation on more than one raw sheets have been tackled on successfully in this study. Several computational experiments are presented to verify the robustness of the proposed algorithm.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.5
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• pp.1183-1192
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• 1993

Since the punching time is strongly related to the productivity in sheet metal stamping, there have been a lot of efforts to obtain the optimal tool path. However, most of the conventional efforts have the basic limitations to provide the global optimal solution because of the inherent difficulties of the NP hard combinatorial optimization problem. The existing methods search the optimal tool path with limiting tool changes to the minimal number, which proves not to be a global optimal solution. In this work, the turret rotation time is also considered in addition to the bed translation time of the NCT machine, and the total punching time is minimized by the simulated annealing algorithm. Some manufacturing constraints in punching sequences such as punching priority constraint and punching accuracy constraint are incorporated automatically in optimization, while several user-interactions to edit the final tool path are usually required in commercial systems.