• Korean Journal of Computational Design and Engineering
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• v.18 no.6
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• pp.417-427
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• 2013

Assembly direction is used in order to confirm the generated assembly sequences in an automatic assembly sequence planning system. Moreover, assembly sequence planners can ascertain the feasibility of a sequence during simulation with assembly direction based in a CAD environment. In other words, assembly direction is essential for sequence optimizing and automatic generation. Based on the importance of assembly direction, this paper proposes a method to select the best direction for the generated assembly sequence using disassembly simulation and geometrical common area between assembled parts. Simultaneously, this idea can be applied to verify the generated assembly sequence. In this paper, the automatic selection of assembly direction and sequence correction system is designed and implemented. The developed algorithms and the implemented system are verified based on case study in the CAD environment.

• International Journal of Naval Architecture and Ocean Engineering
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• v.10 no.4
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• pp.450-457
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• 2018

The determination of assembly sequence in general mechanical assemblies plays an important role in terms of manufacturing cost, duration and quality. In the production of ships and offshore plants, the consideration of productivity factors and welding deformation is crucial in determining the optimal assembly sequence. In shipbuilding and offshore industries, most assembly sequence planning has been done according to engineers' decisions based on extensive experience. This may result in error-prone planning and sub-optimal sequence, especially when dealing with unfamiliar block assemblies composed of dozens of parts. This paper presents an assembly sequence planning method for block assemblies. The proposed method basically considers geometric characteristics of blocks to determine feasible assembly sequences, as well as assembly process and productivity factors. Then the assembly sequence with minimal welding deformation is selected based on simplified welding distortion analysis. The method is validated using an asymmetric assembly model and the results indicate that it is capable of generating an optimal assembly sequence.

• Journal of Korean Institute of Industrial Engineers
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• v.29 no.1
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• pp.49-64
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• 2003

Although assembly sequence planning is an essential task in assembly process planning, it is known as one of the most difficult and time consuming jobs because its complexity is increased geometrically when the number of parts in an assembly is increased. The purpose of this study is to develop a more efficient algorithm for generating assembly sequences automatically. By considering subassemblies, a new heuristic method generates a preferred parallel assembly sequence that can be used in robotic assembly systems. A parallel assembly sequence concept provides a new representation scheme for an assembly in which the assembly sequence precedence information is not required. After an user inputs both the directional mating relation information and the mating condition information, an assembly product is divided into subgroups if the product has cut-vertices. Then, a virtual disassembly process is executed to generate alternate parallel assembly sequences with intermediate assembly stability. Through searching parts relations in the virtual disassembly process, stable subassemblies are extracted from translation-free parts along disassembling directions and this extraction continues until no more subassemblies are existed. Also, the arithmetic mean parallelism formula as a preference criterion is adapted to select the best parallel assembly sequence among others. Finally a preferred parallel assembly sequence is converted to an assembly BOM structure. The results from this study can be utilized for developing CAAPP(Computer-Aided Assembly Process Planning) systems as an efficient assembly sequence planning algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1267-1270
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• 1997

An assembly sequence is considered to be optimal when it minimizes assembly cost while satisfying assembly constraints. to generate such sequences for robotic assembly, this paper proposes a method using a genetic algorithm (GA). This method denotes an assembly sequence as an individual, which is assigned a fitness related to the assembly cost. Then, a population consisting of a number of individuals evolves to the next generation through genetic operations of crossover and mutation based upon the fitness of the individuals. The population continues to repetitively evolve, and finally the fittest individual and its corresponding assembly sequence is found. Through case study for an electrical relay, the effectiveness of the proposed method is demonstrated. Also, the performance is evaluated by-comparing with those of previously presented approaches such as a neural-netowork-based method and a simulated annealing method.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.5 s.98
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• pp.29-39
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• 1999

Many industrial products can be assembled in various sequences of assembly operations. To save time and cost in assembly process and to increase the quality of products, it is very important to choose an optimal assembly sequence. In this paper, we propose a methodology that generates an optimal assembly sequence by using the knowledge of experts. First, a product is divided into several sub-assemblies. Next, the disassembly sequences of sub-assembly are generated using disassembly rules and special information can be extracted through the disassembly process. By combining every assembly sequence of sub-assemblies, we can generate all the possible assembly sequences of a product. Finally, the expert system evaluates all the possible assembly sequences and finds an optimal assembly sequence. It can be achieved under consideration of the parameters such as assembly operation, tool change, safety of part. basepart location, setup change, distance, and orientation. The developed system is applied to UBR(Unit Bath Room) example.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.7
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• pp.1881-1897
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• 1994

This paper presents a neural network-based computational scheme to generate the optimized robotic assembly sequence for an assembly product consisting of a number of parts. An assembly sequence is considered to be optimal when it meets a number of conditions : it must satisfy assembly constraints, keep the stability of in-process subassemblies, and minimize assembly cost. To derive such an optimal sequence, we propose a scheme using both the Hopfield neural network and the expert system. Based upon the inferred precedence constraints and the assembly costs from the expert system, we derive the evolution equation of the network. To illustrate the suitability of the proposed scheme, a case study is presented for industrial product of an electrical relay. The result is compared with that obtained from the expert system.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.6
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• pp.90-101
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• 1996

Determination of assembly sequence of components is a key issue in assembly operation. Although a number of articles dealing with assembly sequence determination have appeared, an efficient and general methodology for complex products has yet to appear. The objective of this paper is to present the problems and models used to generate assembly sequence from design data. An essential idea of this research is to acquire a finite number of voxels from any complex geometric entity, such as 3D planar polygons, hollow spheres, cylinders. cones, tori, etc. In order to find a feasible assembly sequence, the following four steps are needed: (1) The components composing of an assembly product are identified and then the geometric entities of each component are extracted. (2) The geometric entities extracted in the first step are translated into a number of voxels. (3) All the mating or coupling relations between components are found by considering relations between voxels. (4) The components to be disassembled are determined using CCGs (Component Coupling Graph).

• 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.

• International Journal of Precision Engineering and Manufacturing
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• v.1 no.2
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• pp.35-42
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• 2000

To save time and cost in assembly process and to improve th quality of products, it is very important to choose and optimal assembly sequence. In this paper, we propose a methodology that generates an optimal assembly sequence by using various methods and the knowledge of experts. To illustrate the effectiveness of the proposed methodology, a knowledge-based system is developed, The built system is applied to the case of UBR(Unit Bath Room). The applying result showed the applicability of the developed system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.11a
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• pp.295-296
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• 2010