Hitachi, Ltd.

Computer and Automation Research Institute, Hungarian Academy of Sciences

Yoichi Nonaka

Hisaya Ishibashi

Takahiro Nakano

Lengyel Attila

Makoto Ono

Yuuichi Suginishi

Satoshi Nagahara

Attila Lengyel

Laszlo Monostori

Kadar Botond

Monostori Laszlo

Tamas Kis

Botond Kadar

In devices for generating a path of a tool of a processing machine by way of computer simulation, an NC program is created using a generated processing path. The NC program used to be corrected by verification of actually moving the processing machine. In contrast, the disclosed processing path generation device has been constituted to be provided with a means for calculating a closest distance and direction from a relationship of a position and posture between a tool and a work at an arbitrary point upon the processing path; a means for imparting a color determined by the closest distance and the direction calculated at the point upon the processing path; a means for panoramically displaying the color imparted to the work; and a means for correcting the relationship of the a position and posture between the tool and the work on the basis of information from a display device.

Path interference and generation device and method

Priority can be calculated for works-in-process which are not in demand. A priority calculation device () comprises a priority calculation unit () which specifies a queue of lots in each production stage, a product category wherein the lot is to be used, and the number of components included in the lot, on the basis of information stored in a queue information storage area (), and allocates priority for each lot so that when the specified lot is supplied to the production stage, a lot, by which a ratio of a component, in each product category, contained in a lot which is in a process subsequent to the process of the production stage is made closer to the ratio of demand in each product category specified by the information stored in a demand information storage area (), is supplied into the production stage with higher priority.

Priority calculation device, program, priority calculation system, and priority calculation method

A control unit () of a production index information generating device () groups, based on log information of a production device, processing targets to generate groups for which end time of processing falls within a predetermined interval, classifies the processing targets contained in the groups into classes based on a number of the processing targets contained in each of the groups, generates cycle time information for each of the classes, which specifies cycle time of each of the processing targets contained in corresponding one of the classes, and determines a production capability of the production device. Accordingly, an index specifying a capability of the production device may be obtained with ease.

Production index information generating device, program therefore, and production information generating method

A dynamic maintenance planning apparatus including a maintenance planning device and a priority calculating device is provided. The maintenance planning device determines a maintenance date and time on and at which the throughput of a manufacturing system is maximum from among possible maintenance dates and times based on a simulation result in which a specific manufacturing apparatus on a manufacturing system is stopped at a specified maintenance date and time, and, for the maintenance at the determined maintenance date and time, specifies a lot whose completion is predicted to be delayed. The priority calculating device calculates a priority of the lot whose completion is predicted to be delayed so as to prevent waiting time of the lot during the maintenance.

Dynamic maintenance planning apparatus

A method and system of specifying a device that is the root cause of impeding productivity of a production line in consideration of even mutual influence among processes of production fluctuation with respect to the subject of specifying a device in which productive capacity is reduced due to a problem that the productive capacity of the device is changed due to production that one machine works for multiple process and a problem that the productive capacity of device is changed due to high product mix and low product volume production. A measure for changing productive capacity of devices intentionally and simulating influence to the whole production system, a measure for measuring mutual influence among processes of production fluctuation produced by the simulation and a measure for specifying a device that is the root cause of impeding the productivity on the basis of the measured result are provided.

Bottleneck device extracting method and bottleneck device extracting assistance device

The present teaching is intended to observe the delivery date of a product and decrease the number of workpieces in a merger process. A treatment sequence calculator included in manufacturing instruction equipment identifies an in-process part being worked in each process, and calculates the delivery-date allowance of the in-process part. In-process parts whose delivery-date allowances fall below a predetermined threshold are inputted to each process in ascending order of delivery-date allowances. In-process parts whose delivery-date allowances are equal to or larger than the predetermined threshold are inputted to each process in ascending order by a minimum value of remaining treatment times which the in-process parts take to reach the merger process.

Manufacturing instruction equipment, program, manufacturing instruction system, and manufacturing instruction method

A parts-combining method having high quality or yield for a product having a large number of parts. First entering an identification number group of nondefective completed products, a table of a product identification number group and a parts identification number group, a characteristic data group of parts A with respect to identification numbers of the parts A and a characteristic data group of parts B with respect to identification numbers of the parts B, and calculating a nondefective product space. Before a new product is manufactured, entering a characteristic data group of parts A with respect to identification numbers of the parts A and a characteristic data group of parts B with respect to identification numbers of the parts B, and conducting calculations on statistical distances and combinatorial computations between the parts. Finally outputting a combination table having the identification numbers of both the parts A and the parts B.

Growing community of inventors

Yokohama, Japan

Yoichi Nonaka