Semiconductor manufacturing is mainly characterized by diversity of products, different process types, and random failures. It is extremely difficult to solve scheduling problems due to high frequency of disturbance occurrence. This paper proposes a new approach for the online manufacturing rescheduling method. Instead of having a dispatching process based on dispatching rules once again, we revise the existing schedule based on message passing principle once the disturbance occurs, and improve the performance of the revised schedule by the introduction of a quick local search according to permutations of processes on semi-critical paths. The proposed method can release the influence of disturbances in less than 1 second, and finish rescheduling process in less than 1 minute. Through the actual problems with about 200,000 processes, this method is evaluated to be more effective for actual manufacturing than the dispatching-rule based methods, some of which have been applied in many facilities

The job-shop scheduling problem (JSSP) is one of the most difficult NP-hard combinatorial optimization problems. It is extremely difficult to solve the complex job shop scheduling problems because of the disturbances of manufacturing environment. This paper proposes a new method based on the reaction-diffusion equation on a graph [Yuasa, H and Ito, M (1998)] to solve JSSP with disturbances. This method considers the operations of JSSP as the autonomous decentralized system elements. According to the definition of the local potential functions between two operations (two operations on the same machine or the same job), the original schedule can be revised to accommodate with the disturbances of manufacturing, such as machine breakdown, processing time variation, in a short time. The present method is tested for benchmark problems with disturbances.

Omnidirectional views of an indoor environment at different locations are integrated into a global map. A single camera swiveling about the vertical axis takes consecutive images and arranges them into a panoramic representation, which provides rich information around the observation point: a precise omnidirectional view of the environment and coarse ranges to objects in it. Using the coarse map, the system autonomously plans consecutive observations at the intersections of lines connecting object points, where the directions of the imaging are estimated easily and precisely. From two panoramic views at the two planned locations, a modified binocular stereo method yields a more precise, but with direction-dependent uncertainties, local map. New observation points are selected to decrease the uncertainty, and another local map is yielded, which is then integrated into a more reliable global representation of the world with the adjacent local maps.>

A method is proposed for obtaining precise range information by swivelling a conventional TV camera, and the experimental verification of the method is described. To realize the method, the blurring that occurs in the image as a result of aberrations of the TV camera lens is used. The direction to the object is measured with a subpixel-level precision which depends on the angular resolution of the camera controller. The uncertainties of the object locations measured by conventional stereo methods depend on the resolution of the image sensor. It is shown that the method can be used to locate objects with a precision depending on the angular resolution of the camera controller, which is 0 to 20 times better than the conventional imaging method.>

Presents a new sensing method, an omnidirectional stereo, to observe the environment around the robot. The omnidirectional stereo realized by swiveling a camera on the robot precisely yields a 2(1/2)D panoramic representation, a high resolution omnidirectional view with range estimates, of the world around the observation point. The panoramic representation is efficient as the vision of the mobile robot. An application of the panoramic representations in global map making by the mobile robot is discussed.>

A novel imaging method is presented for acquiring an omni-directional view with range information using a single camera. The difficult correspondence problem is solved by tracking each feature in the image sequence in the same manner as in epipolar plane image analysis. Although the equivalent camera distance is not long, the authors can obtain reliable estimates because of the high resolution of the panoramic views. The authors expect the resolution in locating sharp edges to be very fine, up to the resolution of camera rotation, 0.005 degree. A global map making procedure is also proposed which uses omni-directional views at different locations. Omni-directional binocular stereo is used to acquire a path-centered local map with direction-dependent uncertainty. By combining multiple local maps, it is possible to build a more reliable global map. Also explored is the possibility for using the panoramic stereo for map making by a robot.>