Diversified customer demands are raising importance of just-in-time and agile manufacturing much more than before. Accordingly, introduction of mixed-model assembly lines becomes popular to realize the small-lot-multi-kinds production. Since it produces various kinds on the same assembly line, a rational management is of special importance. With this point of view, this study focuses on a sequencing problem of mixed-model assembly line including a paint line as its preceding process. By taking into account the paint line together, reducing work-in-process (WIP) inventory between these heterogeneous lines becomes a major concern of the sequencing problem besides improving production efficiency. Finally, we have formulated the sequencing problem as a bi-objective optimization problem to prevent various line stoppages, and to reduce the volume of WIP inventory simultaneously. Then we have proposed a practical method for the multi-objective analysis. For this purpose, we applied the weighting method to derive the Pareto front. Actually, the resulting problem is solved by a meta-heuristic method like SA (Simulated Annealing). Through numerical experiments, we verified the validity of the proposed approach, and discussed the significance of trade-off analysis between the conflicting objectives.
We present a market-based decentralized approach which uses a market-oriented programming algorithm to obtain Pareto-optimal allocation of resources traded among agents which represent enterprise units in a supply network. The proposed method divides the network into a series of Walrsian markets in order to obtain procurement budgets for enterprises in the network. An interaction protocol based on market value propagation is constructed to coordinate the flow of resources across the network layers. The method mitigates the effect of product complementarity in convergent network by allowing for enterprises to hold private valuations of resources in the markets.
Minimal invasiveness and increasing of precision have recently become important issues in orthopedic surgery. The femur and tibia must be cut precisely for successful knee arthroplasty. The recent trend towards Minimally Invasive Surgery (MIS) has increased surgical difficulty since the incision length and open access area are small. In this paper, the result of deformation analysis of the robot and an active compensation method of robot deformation, which is based on an error map, are proposed and evaluated.
We propose a new method of environmental recognition around an autonomous vehicle using dual vision sensor and navigation control based on binocular images. We consider to develop a guide robot that can play the role of a guide dog as the aid to people such as the visually impaired or the aged, as an application of above-mentioned techniques. This paper presents a recognition algorithm, which finds out the line of a series of Braille blocks and the boundary line between a sidewalk and a roadway where a difference in level exists by binocular images obtained from a pair of parallelarrayed CCD cameras. This paper also presents a tracking algorithm, with which the guide robot traces along a series of Braille blocks and avoids obstacles and unsafe areas which exist in the way of a person with the guide robot.
We consider the defrost timing scheduling for refrigeration system, where it is required to reduce the peak consumption of electric power. The scheduling system is based on the two-stage genetic algorithm. We obtain the cyclic defrost timing at the first-stage, and improve the defrost timing at the second-stage modifying the cyclic defrost timing. The requirement on the undesirable defrost timing can be considered. The case study by using the data at the actual store is shown to verify the effectiveness.