• Journal of Institute of Control, Robotics and Systems
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• v.1 no.2
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• pp.112-118
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• 1995

In designing assembly lines, it is required that the lines should not only meet the demand of the product, but also minimize the assembly cost associated with the line. For such a purpose, numerous research efforts have been made on either the assembly sequence generation or the assembly line balancing. However, the works dealing with both the research problems have been seldom reported in literature. When assembly sequences are generated without consideration of line balancing, additional cost may be incurred, because the sequences may not guarantee the minimum number of workstations. Therefore, it is essential to consider line balancing in the generation of cost-effective assembly sequences. To incorporate the two research problems into one, this paper treats a single-model and deterministic (SMD) assembly line balancing (ALB) problem, and proposes a new method for generating line-balanced robotic assembly sequences by using a simulated annealing. In this method, an energy function is derived in consideration of the satisfaction of assembly constraints, and the minimization of both the assembly cost and the idle time. Then, the energy function is iteratively minimized and occasionally perturbed by the simulated annealing. When no further change in energy occurs, an assembly sequence with consideration of line balancing is finally found. To show the effectiveness of the proposed scheme, a case study for an electrical relay is presented.

• 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 Korean Institute of Industrial Engineers
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• v.33 no.3
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• pp.355-363
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• 2007

This paper presents a method of an automatic work time evaluation based on the verification of a disassemblability and assembly configuration. Even though a work time evaluation is an important field of concern for planning assembly lay-out, there are some limitations using cumbersome user query or approximated work time data without considering assembly condition. To overcome such restriction, this paper presents a method to mathematically verify assembly conditions based on the disassemblability, which is defined by the separability and stability cost. The separability cost represents a facility of the part disassembly operation, and the stability cost which represents a degree of the stability for the base assembly motion. Based upon the results, we propose a new approach of evaluating work time using neural networks. The proposed method provides an effective means of solving the work time evaluation problem and gives a design guidance of planning assembly lay-out in flexible manufacturing application. Example study is given to illustrate the concepts and procedure of the proposed schemes.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.7 s.196
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• pp.39-48
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• 2007

This paper presents a method of a line balanced assembly sequence generation based on the verification of a disassemblability and a work time. To derive the disassemblability for a part to be disassembled, first we inference collision free assembly directions by extracting separable directions fur the part. And we determine the disassemblability defined by the separability and stability cost. The separability cost represents a facility of the part disassembly operation, and the stability cost which represents a degree of the stability for the base assembly motion. Based upon the results, we propose a new approach of evaluating work time using neural networks. The proposed assembly sequence generation provides an effective means of solving the line balancing problem and gives a design guidance of planning assembly lay-out in flexible manufacturing application. Example study is given to illustrate the concepts and procedure of the proposed schemes.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.1
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• pp.213-221
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• 1996

An assembly sequence is considered to be optimal when is minimizes assembly cost while satisfying assembly constraints. To derive such an optimal sequence for robotic assembly, this paper proposes a method using a simulated annealing algorithm. In this method, an energy funciton is derived inconsideration of both the assembly constraints and the assembly cost. The energy function thus derived is iteratively minimized until no further change in energy occurs. During the minimization, the energy is occationally perturbed probabilistically in order to escape from local minima. The minimized energy yields an optimal assembly sequence. To show the effectiveness of the proposed method, case studies are presented for industrial products such as an electrical relay and an automobil alternator. The performance is analyzed by comparing the results with those of a neural network-based method, based upon the optimal solutions of an expert system.

• Journal of the Korea Safety Management & Science
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• v.3 no.3
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• pp.221-230
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• 2001

The assembly tolerance design methods have applied linear or nonlinear programming methods and used simulation method and search algorithms to optimize the tolerance allocation of each part in an assembly. However, those methods are only considered to the relationship between tolerance and manufacturing cost, which do not consider a quality loss cost for each part tolerance. In this paper, the integrated simulation model used genetic algorithm and the Monte-Carlo simulation method was developed for the allocation of the optimal tolerance considering the manufacturing cost and quality loss cost.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.7
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• pp.656-662
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• 2008

A cost-function based on manipulability and compatibility is designed to determine assembly motions of two cooperating manipulators. Assembly motions are planned along the direction maximizing performance indices to improve control performance of the two manipulators. This paper proposes bimanual task compatibility by defining cost functions. The proposed cost functions are applied and compared to the bimanual assembly task. The problem is formulated as a constrained optimization considering assembly constraints, position of the workpieces, and kinematics and redundancy of the bimanual robot. The proposed approach is evaluated with simulation of a peg-in-hole assembly with an L-shaped peg and two 3-dof manipulators.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.507-512
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• 1992

This paper presents a method for the automatic generation of assembly sequences based on the recursive extraction of a preferred part along with the verification of its disassemblability. To verify the disassemblability of the part we inference the geometric precedence constraints using a method of extracting separable directions for the part and determine the disassemblability cost by the separability and stability cost. The proosed method provides a local optimal solution of finding a cost effective assembly plan, and the feasibility of calculating robot motion programs by evaluating separable directions in flexible manufacturing application. A case study is given to illustrate the concepts and procedure of the proposed scheme.

• Journal of Korean Society for Quality Management
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• v.10 no.2
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• pp.10-17
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• 1982

Three different manual assembly techniques are evaluated by relating the effects of component quality to the total cost of the product. The results show that the choice of the scrapping or repairing the defective products or alternatively, salvaging the acceptable parts, may effect the total product cost by as much as 400 per cent. This paper emphasizes the need for accurate control quality of parts in assembly if low-cost manufacture is to be achieved.